From b2b6bd23125c24e63852b97ebdbcc45a49b5f9a6 Mon Sep 17 00:00:00 2001 From: pete Date: Thu, 21 May 2026 15:22:54 +0300 Subject: [PATCH 01/20] added injection scripts --- .gitignore | 2 +- scripts/injection/README.md | 68 ++++++++ scripts/injection/explore_test_name.sh | 163 ++++++++++++++++++ scripts/injection/injection_extraction.sh | 87 ++++++++++ scripts/injection/parquet/make_parquet.sql | 39 +++++ .../injection/parquet/make_tsv_gzipped.sql | 36 ++++ scripts/injection/parquet/run.sh | 11 ++ 7 files changed, 405 insertions(+), 1 deletion(-) create mode 100644 scripts/injection/README.md create mode 100644 scripts/injection/explore_test_name.sh create mode 100644 scripts/injection/injection_extraction.sh create mode 100644 scripts/injection/parquet/make_parquet.sql create mode 100644 scripts/injection/parquet/make_tsv_gzipped.sql create mode 100644 scripts/injection/parquet/run.sh diff --git a/.gitignore b/.gitignore index 818e20a..353d9e0 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,5 @@ finngen_qc/test/ -/scripts/ +/scripts/test/ #EMACS FILES \#*\# diff --git a/scripts/injection/README.md b/scripts/injection/README.md new file mode 100644 index 0000000..6fdd14c --- /dev/null +++ b/scripts/injection/README.md @@ -0,0 +1,68 @@ +# Unit injection exploration + +The goal is to identify lab measurements that have a numeric value but are missing a unit, and to characterise the unit distribution of the matching records that do have a unit — so that a unit can be confidently assigned to the missing ones. + +## Usage + +```bash +bash explore_test_name.sh +``` + +- ``: path to the input parquet file (INJECT.parquet) +- ``: minimum number of no-unit records a TEST_NAME+TEST_ID pair must have to be included + +Each output file is skipped if it already exists. + +--- + +## Step 1 — Injection targets (`test_name_id_counts.tsv`) + +Counts records where at least one source value is present (`MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_HARMONIZED IS NOT NULL`) but the unit prefix is absent (`MEASUREMENT_UNIT_PRE_FIX IS NULL`), grouped by `(TEST_NAME, TEST_ID)`. Only pairs with count > `min_count` are kept. + +Columns: `TEST_NAME`, `TEST_ID`, `COUNT` + +These are the records we want to assign a unit to. + +--- + +## Step 2 — Reference population (`test_name_id_details.tsv`) + +For every TEST_NAME that appears in Step 1, describes the unit distribution of the records that already have both a value and a unit (`MEASUREMENT_VALUE_MERGED IS NOT NULL AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL`), grouped by `(TEST_NAME, TEST_ID)`. Note that this covers all TEST_IDs for those TEST_NAMEs, not just the ones above the threshold in Step 1. + +Columns: `TEST_NAME`, `TEST_ID`, `COUNT`, `UNIT`, `PREVALENCE_DICT` + +- `COUNT`: number of reference records for this pair +- `UNIT`: the most frequent unit for this pair +- `PREVALENCE_DICT`: JSON-like string with the top-3 units and their percentage share, e.g. `{mmol/l:98.5,umol/l:1.5}` + +These records are the basis for deciding which unit to inject. + +--- + +## Step 3 — Plotting tables and scatter plots + +Two intermediate tables are built in Python by merging Steps 1 and 2, then a two-panel scatter plot is saved. Before any computation, Step 2 data is restricted to the `(TEST_NAME, TEST_ID)` pairs present in Step 1, so the plots only reflect injection-target pairs. + +### `plot_name_id_level.tsv` + +One row per `(TEST_NAME, TEST_ID)` from Step 1. Joined with the top unit prevalence from the reference population (Step 2) where available. + +- `COUNT`: number of injection-target records +- `top_prevalence`: prevalence (%) of the dominant unit in the reference population for this pair; 0 if no reference records exist +- `has_unit_data`: whether any reference records exist for this pair + +### `plot_name_level.tsv` + +One row per `TEST_NAME`, aggregated from `plot_name_id_level.tsv`. + +- `total_count`: sum of injection-target counts across all TEST_IDs +- `top_prevalence`: COUNT-weighted mean of `top_prevalence` across TEST_IDs that have reference records (TEST_IDs with no reference records are excluded from the average) + +### `test_names_exploration_scatter.png` + +Two scatter plots (log x-axis): + +- **Left**: one dot per `(TEST_NAME, TEST_ID)` — x = injection-target count, y = top unit prevalence in reference population +- **Right**: one dot per `TEST_NAME` — x = total injection-target count, y = weighted top unit prevalence + +Points in the top-right are high-volume tests with a consistent unit in the reference population — the best candidates for automated unit injection. diff --git a/scripts/injection/explore_test_name.sh b/scripts/injection/explore_test_name.sh new file mode 100644 index 0000000..02ffc9f --- /dev/null +++ b/scripts/injection/explore_test_name.sh @@ -0,0 +1,163 @@ +#!/bin/bash + +F="$1" +MIN_COUNT="$2" + +OUT_COUNTS="test_name_id_counts.tsv" +OUT_DETAILS="test_name_id_details.tsv" +PLOT="test_names_exploration_scatter.png" + +# --- Query 1: TEST_NAME, TEST_ID, COUNT for all pairs with count > threshold --- +if [[ ! -f "$OUT_COUNTS" ]]; then + clickhouse -q " + SELECT + TEST_NAME, + TEST_ID, + count() AS COUNT + FROM file('$F') + WHERE (MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_HARMONIZED IS NOT NULL) + AND MEASUREMENT_UNIT_PRE_FIX IS NULL + GROUP BY TEST_NAME, TEST_ID + HAVING COUNT > $MIN_COUNT + ORDER BY COUNT DESC + FORMAT TSVWithNames + " > "$OUT_COUNTS" + echo "Wrote $OUT_COUNTS" +else + echo "$OUT_COUNTS already exists, skipping." +fi + +# --- Query 2: TEST_NAME, TEST_ID, COUNT, UNIT, PREVALENCE_DICT --- +# Include all TEST_NAMEs present in Query 1 output +if [[ ! -f "$OUT_DETAILS" ]]; then + OUT_COUNTS_ABS="$(realpath "$OUT_COUNTS")" + clickhouse -q " + WITH + global_names AS ( + SELECT DISTINCT TEST_NAME + FROM file('$OUT_COUNTS_ABS', TSVWithNames) + ), + top3_units AS ( + SELECT + TEST_NAME, TEST_ID, + argMax(MEASUREMENT_UNIT_PRE_FIX, unit_cnt) AS UNIT, + concat('{', arrayStringConcat(groupArray(unit_json), ','), '}') AS PREVALENCE_DICT + FROM ( + SELECT TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX, unit_cnt, unit_json + FROM ( + SELECT + TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX, unit_cnt, + ROW_NUMBER() OVER (PARTITION BY TEST_NAME, TEST_ID ORDER BY unit_cnt DESC) AS rn, + concat( + MEASUREMENT_UNIT_PRE_FIX, ':', + toString(round(100.0 * unit_cnt / SUM(unit_cnt) OVER (PARTITION BY TEST_NAME, TEST_ID), 2)) + ) AS unit_json + FROM ( + SELECT TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX, count() AS unit_cnt + FROM file('$F') + WHERE MEASUREMENT_VALUE_MERGED IS NOT NULL + AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL + GROUP BY TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX + ) AS sub + ) AS ranked + WHERE rn <= 3 + ) AS top3 + GROUP BY TEST_NAME, TEST_ID + ), + total_counts AS ( + SELECT TEST_NAME, TEST_ID, count() AS COUNT + FROM file('$F') + WHERE MEASUREMENT_VALUE_MERGED IS NOT NULL + AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL + GROUP BY TEST_NAME, TEST_ID + ) + SELECT + t.TEST_NAME AS TEST_NAME, + t.TEST_ID AS TEST_ID, + t.COUNT AS COUNT, + u.UNIT AS UNIT, + u.PREVALENCE_DICT AS PREVALENCE_DICT + FROM total_counts t + LEFT JOIN top3_units u USING (TEST_NAME, TEST_ID) + INNER JOIN global_names g ON t.TEST_NAME = g.TEST_NAME + ORDER BY t.COUNT DESC + FORMAT TSVWithNames + " > "$OUT_DETAILS" + echo "Wrote $OUT_DETAILS" +else + echo "$OUT_DETAILS already exists, skipping." +fi + +# --- Python: build plotting tables and scatter plots --- +if [[ -f "$PLOT" ]]; then + echo "Plot '$PLOT' already exists, skipping." + exit 0 +fi + +python3 - <<'EOF' +import re +import pandas as pd +import matplotlib.pyplot as plt + +def parse_top_prevalence(d): + if pd.isna(d): + return None + pcts = re.findall(r':(\d+\.?\d*)[,}]', str(d)) + if not pcts: + return None + return max(float(p) for p in pcts) + +counts = pd.read_csv("test_name_id_counts.tsv", sep="\t") +details = pd.read_csv("test_name_id_details.tsv", sep="\t") + +# restrict details to (TEST_NAME, TEST_ID) pairs present in Query 1 +details = details.merge(counts[["TEST_NAME", "TEST_ID"]], on=["TEST_NAME", "TEST_ID"], how="inner") + +# ---- TEST_NAME + TEST_ID level ---- +details["top_prevalence"] = details["PREVALENCE_DICT"].apply(parse_top_prevalence) + +plot_name_id = counts.merge( + details[["TEST_NAME", "TEST_ID", "top_prevalence"]], + on=["TEST_NAME", "TEST_ID"], how="left" +) +plot_name_id["has_unit_data"] = plot_name_id["top_prevalence"].notna() +plot_name_id["top_prevalence"] = plot_name_id["top_prevalence"].fillna(0) +plot_name_id.to_csv("plot_name_id_level.tsv", sep="\t", index=False) +print(f"Built plot_name_id_level.tsv ({len(plot_name_id)} rows)") + +# ---- TEST_NAME level (COUNT-weighted mean over rows WITH unit data only) ---- +def weighted_prevalence(d): + valid = d[d["has_unit_data"]] + if valid.empty: + return 0.0 + return (valid["top_prevalence"] * valid["COUNT"]).sum() / valid["COUNT"].sum() + +g = plot_name_id.groupby("TEST_NAME") +plot_name = pd.DataFrame({ + "total_count": g["COUNT"].sum(), + "top_prevalence": g.apply(weighted_prevalence), +}).reset_index() +plot_name.to_csv("plot_name_level.tsv", sep="\t", index=False) +print(f"Built plot_name_level.tsv ({len(plot_name)} rows)") + +# ---- Scatter plots ---- +fig, axes = plt.subplots(1, 2, figsize=(18, 7)) + +ax1 = axes[0] +ax1.scatter(plot_name_id["COUNT"], plot_name_id["top_prevalence"], alpha=0.5, s=20) +ax1.set_xlabel("Count (value, no unit)") +ax1.set_ylabel("Top unit prevalence (%)") +ax1.set_title("TEST_NAME + TEST_ID level") +ax1.set_xscale("log") + +ax2 = axes[1] +ax2.scatter(plot_name["total_count"], plot_name["top_prevalence"], alpha=0.5, s=20) +ax2.set_xlabel("Total count (value, no unit)") +ax2.set_ylabel("Weighted top unit prevalence (%)") +ax2.set_title("TEST_NAME level") +ax2.set_xscale("log") + +plt.tight_layout() +plt.savefig("test_names_exploration_scatter.png", dpi=150) +print("Saved test_names_exploration_scatter.png") +EOF diff --git a/scripts/injection/injection_extraction.sh b/scripts/injection/injection_extraction.sh new file mode 100644 index 0000000..5ff14da --- /dev/null +++ b/scripts/injection/injection_extraction.sh @@ -0,0 +1,87 @@ +#!/bin/bash +set -e + +# === CONFIGURE PATHS === +BASE_DIR="/mnt/disks/data/kanta/test" +PARQUET_DATA="$BASE_DIR/kanta_v3_harmonized_2026_03_06_formatted.parquet" +PARQUET_TESTS="$BASE_DIR/finngen_R14_kanta_lab_1.0_extended_columns.parquet" + +OUT_CF_COUNTS="$BASE_DIR/omop_convfactor_counts.tsv" +OUT_AMBIGUOUS="$BASE_DIR/ambiguous_omop_cf_ids_sorted.txt" +OUT_TEST_COUNTS="$BASE_DIR/testname_omopid_count_sorted.tsv" +OUT_INJECTION="$BASE_DIR/injection_candidates.txt" + +echo "FETCH AMBIGUOUS IDS/CONVERSION FACTORS" +clickhouse -q " +SELECT + OMOP_CONCEPT_ID, + CONVERSION_FACTOR, + count() AS cnt +FROM file('$PARQUET_DATA', 'Parquet') +WHERE MEASUREMENT_UNIT_CLEANED IS NOT NULL + AND MEASUREMENT_VALUE_HARMONIZED IS NOT NULL + AND CONVERSION_FACTOR IS NOT NULL +GROUP BY OMOP_CONCEPT_ID, CONVERSION_FACTOR +ORDER BY OMOP_CONCEPT_ID, cnt DESC +" --format=TabSeparated > "$OUT_CF_COUNTS" +wc "$OUT_CF_COUNTS" +head "$OUT_CF_COUNTS" + +echo "BUILD AMBIGUOUSNESS TABLE BASED ON CONVERSION FACTOR PREVALENCE > 5% (INCLUDE TOTAL COUNT)" +python3 -c " +from collections import defaultdict +d, t = defaultdict(list), defaultdict(int) +with open('$OUT_CF_COUNTS') as f: + for l in f: + omop, cf, cnt = l.rstrip().split('\t') + cnt = int(cnt) + d[omop].append((cf, cnt)) + t[omop] += cnt +for omop in sorted(d, key=int): + shares = {cf: round(c / t[omop], 2) for cf, c in d[omop]} + threshold = 0.05 + ambiguous = 1 if len(shares) > 1 and sorted(shares.values(), reverse=True)[1] > threshold else 0 + total = t[omop] + print(f'{omop}\t' + '{' + ','.join(f'\"{cf}\":{v}' for cf, v in shares.items()) + f'}}\t{ambiguous}\t{total}') +" | sort > "$OUT_AMBIGUOUS" +head "$OUT_AMBIGUOUS" +wc "$OUT_AMBIGUOUS" + +echo "GET ALL EXTRACTED TESTS COUNTS" +clickhouse -q " +SELECT + TEST_NAME, + OMOP_CONCEPT_ID, + count() AS COUNT +FROM file('$PARQUET_TESTS', 'Parquet') +WHERE MEASUREMENT_VALUE_EXTRACTED IS NOT NULL +GROUP BY TEST_NAME, OMOP_CONCEPT_ID +ORDER BY COUNT DESC +" --format=TabSeparated | sort -k2,2 > "$OUT_TEST_COUNTS" + +wc "$OUT_TEST_COUNTS" +head "$OUT_TEST_COUNTS" + + +echo "JOIN AND FILL MISSING" +join -t $'\t' -1 2 -2 1 -a 1 "$OUT_TEST_COUNTS" "$OUT_AMBIGUOUS" \ +| sort -grk3 \ +| awk -F'\t' -v OFS='\t' '{for(i=1;i<=5;i++) if($i=="") $i=0; print $1,$2,$3,$4,$5}' > "$OUT_INJECTION" + +echo "SAMPLE JOINT OUTPUT" +head "$OUT_INJECTION" +wc "$OUT_INJECTION" + +echo "SUM & RELATIVE FRACTION OF PROBLEMATIC VS UNPROBLEMATIC (BY COLUMN 5)" + +awk -F'\t' ' +{ + # $3 = count, $5 = ambiguous flag + if ($5==1) prob+=$3; else nonprob+=$3 +} +END { + total = prob + nonprob; + printf "Problematic: %d (%.2f%%)\n", prob, (prob/total*100); + printf "Non-problematic: %d (%.2f%%)\n", nonprob, (nonprob/total*100); +} +' "$OUT_INJECTION" diff --git a/scripts/injection/parquet/make_parquet.sql b/scripts/injection/parquet/make_parquet.sql new file mode 100644 index 0000000..c909fb4 --- /dev/null +++ b/scripts/injection/parquet/make_parquet.sql @@ -0,0 +1,39 @@ +SELECT + ROW_ID :: Int64 AS ROW_ID, -- Cast to Int64 to ensure numerical sorting + FINNGENID, + SEX, + EVENT_AGE :: Float64 AS EVENT_AGE, + concat(APPROX_EVENT_DATETIME, ':00') :: DateTime64(3, 'UTC') AS APPROX_EVENT_DATETIME, + + -- OMOP harmonization + nullIf(OMOP_CONCEPT_ID, 'NA') :: Nullable(String) AS OMOP_CONCEPT_ID, + + -- Test identification + TEST_ID, + TEST_ID_IS_NATIONAL :: Bool AS TEST_ID_IS_NATIONAL, + + -- Test names + TEST_NAME, + TEST_NAME_SOURCE, + + -- Measurement values + nullIf(MEASUREMENT_UNIT_HARMONIZED, 'NA') :: Nullable(String) AS MEASUREMENT_UNIT_HARMONIZED, + nullIf(MEASUREMENT_VALUE_HARMONIZED, 'NA') :: Nullable(Float64) AS MEASUREMENT_VALUE_HARMONIZED, + nullIf(MEASUREMENT_VALUE_EXTRACTED, 'NA') :: Nullable(Float64) AS MEASUREMENT_VALUE_EXTRACTED, + nullIf(MEASUREMENT_VALUE_MERGED, 'NA') :: Nullable(Float64) AS MEASUREMENT_VALUE_MERGED, + nullIf(MEASUREMENT_UNIT_CLEANED, 'NA') :: Nullable(String) AS MEASUREMENT_UNIT_CLEANED, + nullIf(MEASUREMENT_UNIT_PRE_FIX, 'NA') :: Nullable(String) AS MEASUREMENT_UNIT_PRE_FIX, + nullIf(MEASUREMENT_VALUE_SOURCE, 'NA') :: Nullable(Float64) AS MEASUREMENT_VALUE_SOURCE, + nullIf(MEASUREMENT_UNIT_SOURCE, 'NA') :: Nullable(String) AS MEASUREMENT_UNIT_SOURCE, + + -- Coding systems + nullIf(CODING_SYSTEM_ORG, 'NA') :: Nullable(String) AS CODING_SYSTEM_ORG, + nullIf(CODING_SYSTEM_OID, 'NA') :: Nullable(String) AS CODING_SYSTEM_OID + +FROM file({filePathCleanTxtGz:String}, TSVWithNames) + +FORMAT Parquet +SETTINGS + input_format_tsv_use_best_effort_in_schema_inference = 0, + output_format_parquet_compression_method = 'zstd', + output_format_parquet_string_as_string = 1; diff --git a/scripts/injection/parquet/make_tsv_gzipped.sql b/scripts/injection/parquet/make_tsv_gzipped.sql new file mode 100644 index 0000000..4b5c785 --- /dev/null +++ b/scripts/injection/parquet/make_tsv_gzipped.sql @@ -0,0 +1,36 @@ +SELECT + ROW_ID :: Int64 AS ROW_ID, -- Cast to Int64 to ensure numerical sorting + FINNGENID, + SEX, + EVENT_AGE, + APPROX_EVENT_DATETIME, + + -- OMOP harmonization + if(`harmonization_omop::OMOP_ID` IN ('-1', '0'), 'NA', `harmonization_omop::OMOP_ID`) AS OMOP_CONCEPT_ID, + -- Test identification + TEST_ID, + TEST_ID_IS_NATIONAL, + + -- Test names (both cleaned and source) + `cleaned::TEST_NAME_ABBREVIATION` AS TEST_NAME, + `source::TEST_NAME_ABBREVIATION` AS TEST_NAME_SOURCE, + + `cleaned::MEASUREMENT_UNIT` AS MEASUREMENT_UNIT_CLEANED, + `cleaned-pre-fix::MEASUREMENT_UNIT` AS MEASUREMENT_UNIT_PRE_FIX, + + -- Measurement values (harmonized, extracted, merged, and source) + `harmonization_omop::MEASUREMENT_UNIT` AS MEASUREMENT_UNIT_HARMONIZED, + `harmonization_omop::MEASUREMENT_VALUE` AS MEASUREMENT_VALUE_HARMONIZED, + `extracted::MEASUREMENT_VALUE` AS MEASUREMENT_VALUE_EXTRACTED, + `extracted::MEASUREMENT_VALUE_MERGED` AS MEASUREMENT_VALUE_MERGED, + `source::MEASUREMENT_VALUE` AS MEASUREMENT_VALUE_SOURCE, + `source::MEASUREMENT_UNIT` AS MEASUREMENT_UNIT_SOURCE, + -- Coding systems + CODING_SYSTEM_MAP AS CODING_SYSTEM_ORG, + CODING_SYSTEM AS CODING_SYSTEM_OID + FROM file({filePathMungedTxtGz:String}, TSVWithNames) kanta_lab_table +-- Set output format to TSV-gzipped with a header +FORMAT TSVWithNames + +-- Disable data type inference from TSV text file +SETTINGS input_format_tsv_use_best_effort_in_schema_inference = 0 diff --git a/scripts/injection/parquet/run.sh b/scripts/injection/parquet/run.sh new file mode 100644 index 0000000..7e79ddf --- /dev/null +++ b/scripts/injection/parquet/run.sh @@ -0,0 +1,11 @@ +INPUT_FILE="/home/pete/fg-3/kanta_v3/core/kanta_dev_2026_03_09.txt.gz" +TXT_GZ_FILE="INJECT.txt.gz" +TXT_QUERY="/home/pete/Dropbox/Projects/kanta_lab_preprocessing/scripts/injection/parquet/make_tsv_gzipped.sql" + + +clickhouse --param_filePathMungedTxtGz $INPUT_FILE --param_outputFile $TXT_GZ_FILE --queries-file $TXT_QUERY | gzip -c > $TXT_GZ_FILE + + +PARQ="INJECT.parquet" +PARQ_QUERY="/home/pete/Dropbox/Projects/kanta_lab_preprocessing/scripts/injection/parquet/make_parquet.sql" + clickhouse --param_filePathCleanTxtGz "$TXT_GZ_FILE" --queries-file $PARQ_QUERY > $PARQ From fa0f7da7f0181457326c80153d02954252c1e413 Mon Sep 17 00:00:00 2001 From: pete Date: Thu, 21 May 2026 15:26:15 +0300 Subject: [PATCH 02/20] added figures --- scripts/injection/README.md | 2 + scripts/injection/data/plot_name_id_level.tsv | 2763 +++++++++++++++++ scripts/injection/data/plot_name_level.tsv | 1026 ++++++ .../data/test_names_exploration_scatter.png | Bin 0 -> 121856 bytes 4 files changed, 3791 insertions(+) create mode 100644 scripts/injection/data/plot_name_id_level.tsv create mode 100644 scripts/injection/data/plot_name_level.tsv create mode 100644 scripts/injection/data/test_names_exploration_scatter.png diff --git a/scripts/injection/README.md b/scripts/injection/README.md index 6fdd14c..e13451a 100644 --- a/scripts/injection/README.md +++ b/scripts/injection/README.md @@ -66,3 +66,5 @@ Two scatter plots (log x-axis): - **Right**: one dot per `TEST_NAME` — x = total injection-target count, y = weighted top unit prevalence Points in the top-right are high-volume tests with a consistent unit in the reference population — the best candidates for automated unit injection. + +![Scatter plot](data/test_names_exploration_scatter.png) diff --git a/scripts/injection/data/plot_name_id_level.tsv b/scripts/injection/data/plot_name_id_level.tsv new file mode 100644 index 0000000..8e8ba99 --- /dev/null +++ b/scripts/injection/data/plot_name_id_level.tsv @@ -0,0 +1,2763 @@ +TEST_NAME TEST_ID COUNT top_prevalence has_unit_data +b-eryt 1341 2046474 100.0 True +b-leuk 2218 2031768 100.0 True +b-trom 2791 1835388 100.0 True +b-hkr 1358 1108179 52.67 True +p-tt-inr 4520 827663 92.6 True +b-neut 3238 560729 99.5 True +p-inr 4520 465614 100.0 True +ab-ph 1527 375883 98.69 True +b-hkr 3001358 364840 84.79 True +b-leuk 3002218 348425 100.0 True +b-eryt 3001341 339178 100.0 True +e-mch 3001558 338725 100.0 True +e-mcv 3001357 338615 100.0 True +b-trom 3002791 338540 100.0 True +b-hb 3001552 322284 100.0 True +b-eos 1330 320814 99.8 True +b-monos 3230 310738 99.57 True +b-hb 1552 306395 100.0 True +b-baso 3157 301099 99.84 True +b-ly 3223 298815 99.33 True +u-ph 1530 291005 98.78 True +b-erblast 8518 290470 100.0 True +s-ph 8523 283517 0.0 False +p-k 1999 269981 100.0 True +e-mcv 1357 247360 100.0 True +e-mch 1558 243479 99.77 True +p-inr 3004520 234554 0.0 False +p-k 3001999 229082 100.0 True +p-na 3003622 222257 100.0 True +p-na 3622 192896 100.0 True +b-hb 1001552 187110 100.0 True +b-hkr 1001358 186638 100.0 True +b-leuk 1002218 186134 100.0 True +b-eryt 1001341 185621 100.0 True +e-mcv 1001357 185288 100.0 True +b-trom 1002791 185060 100.0 True +e-mch 1001558 184982 100.0 True +e-mchc 3001557 176587 100.0 True +u-suhti 2715 174960 92.52 True +p-inr 6004520 171649 0.0 False +pt-gfreepi 645140 163298 0.0 False +p-alat 1024 161208 100.0 True +vb-ph 1531 159518 100.0 True +e-rdw 619260 158705 100.0 True +b-hba1c 6128 147505 100.0 True +fp-gluk 1468 147429 99.97 True +p-krea 1002143 145767 100.0 True +u-ph 21701 143491 0.0 False +u-leuk 2221 139384 99.76 True +u-eryt 1344 137185 99.44 True +u-lier 19006 136425 100.0 True +p-tt-inr 3004520 133612 100.0 True +u-levyep 20524 133277 100.0 True +u-pienep 20525 133093 100.0 True +pt-gfreepi 5589849 129232 100.0 True +p-krea 605262 121923 100.0 True +p-na 1003622 120981 100.0 True +p-k 1001999 120976 100.0 True +p-tsh 4831 119706 97.99 True +ph 595 118639 0.0 False +p-crp 4594 116644 100.0 True +p-krea 4600 114156 100.0 True +p-alat 1001026 111476 100.0 True +b-erybla 19978 109544 100.0 True +fp-gluk 3001468 109118 100.0 True +pt-gfreepi 13470 108305 96.59 True +pt-gfre 6354 108215 100.0 True +pt-gfreepi 6002 106731 0.0 False +e-rdw 19976 103098 100.0 True +cb-ph 1528 99671 100.0 True +p-inr 604913 90412 0.0 False +p-alat 3001024 86716 100.0 True +pt-gfreepi 6354 82046 100.0 True +fp-kol-ldl 4599 81995 100.0 True +fp-gluk 1001469 77927 100.0 True +p-tsh 1002832 76678 100.0 True +b-hkr 6001358 75405 100.0 True +b-hb 6001552 75081 100.0 True +b-eryt 6001341 75069 100.0 True +fb-leuk 6002218 75037 100.0 True +e-mch 6001558 75032 100.0 True +e-mcv 6001357 75026 100.0 True +p-alat 605242 75005 100.0 True +e-mchc 6001557 74961 100.0 True +b-tromb 6002791 74939 100.0 True +p-kol-ldl 6433 73834 100.0 True +p-t4-v 4832 71144 100.0 True +fp-kol 4515 65814 100.0 True +fp-kol-ldl 1002099 65634 100.0 True +e-rdw 20408 65406 100.0 True +fp-kol 1002095 64459 100.0 True +p-crp 1001216 63280 100.0 True +fp-trigly 1002770 61758 100.0 True +p-kol 6429 61539 100.0 True +b-hba1c 620426 60186 100.0 True +fp-kol-hdl 2002097 60152 100.0 True +hdl/kol 1000505 59638 100.0 True +p-kol-hdl 6431 59251 100.0 True +pt-gfre 645275 58891 100.0 True +p-crp 3005293 58707 100.0 True +p-trigly 4530 58273 100.0 True +u-ph 6001530 57665 0.0 False +non-hdl 10168 56603 0.0 False +fp-kol-ldl 3005319 55612 100.0 True +p-krea 2142 55491 100.0 True +p-crp 605241 55433 100.0 True +fp-kol 3004515 55271 100.0 True +fp-kol-hdl 3004516 55080 100.0 True +u-suhti 6002715 54926 0.0 False +fp-trigly 3004568 54792 100.0 True +fp-trigly 4568 54491 100.0 True +p-afos 4587 52626 100.0 True +p-krea 1604748 51450 100.0 True +b-erybla 649167 51200 100.0 True +e-rdw 649166 50665 100.0 True +p-tsh 606115 49589 100.0 True +b-la 2203 49373 100.0 True +fp-kol-hdl 4516 49231 100.0 True +p-tt-inr 601976 48880 0.0 False +s-ph 11554 48701 0.0 False +p-k 6001999 48059 100.0 True +p-na 6003622 48019 100.0 True +b-hba1c 607918 47333 100.0 True +b-neut 3003238 46036 100.0 True +fp-kol-ldl 605259 45772 100.0 True +b-la 3002203 45470 100.0 True +kol/hdlsuh 10067 44001 0.0 False +p-t4-v 606116 43479 100.0 True +b-la 1002203 42660 100.0 True +p-inr 1607047 41919 0.0 False +p-t4-v 1002836 41305 100.0 True +pt-gfreepi 21218 40596 100.0 True +-h-ind 20536 39809 0.0 False +p-afos 1001046 39414 100.0 True +u-ph-o 3667 39137 0.0 False +p-tromboplastiiniaika,inr-tulostus 4520 38382 100.0 True +p-krea 3002142 37240 100.0 True +e-mchc 1557 36967 100.0 True +p-gt 4597 36019 100.0 True +s-ph 50100 34663 0.0 False +p-alat 1605001 34228 100.0 True +p-tsh 649821 32953 100.0 True +p-ferrit 4826 30887 100.0 True +u-suhti-o 0715 30337 0.0 False +p-afos 605244 30073 100.0 True +b-eos 3001330 29841 100.0 True +pt-gfreepi 11326 29761 100.0 True +u-krea 2145 29249 98.94 True +u-keto-o 3001122 29010 100.0 True +p-afos 3005282 28039 100.0 True +u-gluk-o 3001479 27975 100.0 True +kolesteroli/hdl-suhde 10067 27781 0.0 False +hdl/kol 505 27161 100.0 True +u-alb-o 3001030 26863 100.0 True +u-ph 13039 26642 0.0 False +fp-kol 605256 26455 100.0 True +fp-kol-hdl 605257 26256 100.0 True +p-gt 1001489 26228 100.0 True +fp-trigly 605258 26182 100.0 True +ab-be 10083 25881 100.0 True +u-nitr-o 3003094 25800 100.0 True +p-psa 4869 25083 100.0 True +u-ph. 21701 23871 0.0 False +u-suhti. 21702 23384 0.0 False +fp-gluk 6001468 23324 100.0 True +u-eryt-o 3001345 23075 100.0 True +b-trom 2629414 23064 100.0 True +b-ly 3003223 23009 100.0 True +b-monos 3003230 23009 100.0 True +b-baso 3003157 23009 100.0 True +l-eos(a) 3001332 23006 100.0 True +l-lymf(a) 3009235 23006 100.0 True +l-mono(a) 3000399 23006 100.0 True +l-neut(a) 3000398 23006 100.0 True +l-baso(a) 3001168 23006 100.0 True +kol/hdlsuh 10037 22867 0.0 False +fp-kol-ldl 1605024 22609 100.0 True +b-retik 2581 22598 100.0 True +b-hba1c 650105 22516 100.0 True +p-happamuusaste(ionis.ca) 595 22410 0.0 False +fp-kol 1605022 22188 100.0 True +p-alb 4586 22154 100.0 True +fs-ph 50100 22040 0.0 False +ph 1000595 21958 0.0 False +u-nitr-o 3094 21869 100.0 True +fs-folaat 1416 21758 100.0 True +u-albkre 4511 21642 100.0 True +u-ph 3667 21609 0.0 False +s-b12-tc2 1142 21574 100.0 True +pt-gfre 656400 21550 0.0 False +u-krea 3002145 21319 93.49 True +u-gluk-o 1479 21143 100.0 True +u-ph 3001530 21058 0.0 False +fp-kol-hdl 1605023 20836 100.0 True +pt-gfreepi 0232 20834 100.0 True +p-tsh 1605042 20670 100.0 True +vb-be 9074 20573 100.0 True +fp-trigly 1605041 20454 100.0 True +p-gluk 1471 20310 100.0 True +u-leuk-o 3002223 20119 100.0 True +b-leuk 1629408 19981 0.0 False +b-eryt 1629409 19962 0.0 False +e-rdw 1631804 19908 0.0 False +b-trom 1629414 19870 0.0 False +u-keto-o 1122 19716 95.16 True +ca-ion 1000597 19146 0.0 False +ca++/7.40 1000596 19140 0.0 False +p-crp 1605013 19124 100.0 True +p-t4v 1605037 18942 100.0 True +p-psa 2003642 18865 100.0 True +p-t4-v 649822 18774 100.0 True +b-neut 1003238 18307 100.0 True +u-leuk-o 2223 18164 100.0 True +ph 9018 17842 0.0 False +s-k/l-s-v 20113 17806 100.0 True +b-leuk 3629408 17552 100.0 True +u-suhteellinentiheys 2715 17548 100.0 True +b-eryt 3629409 17499 100.0 True +p-inr 607047 17490 0.0 False +p-gt 3005292 17319 100.0 True +p-krea 645274 17118 100.0 True +u-eryt-o 1345 17072 100.0 True +s-apob/apoa1-suhde 0623 16804 0.0 False +p-probnp 4760 16554 100.0 True +u-krea 10458 16442 100.0 True +p-krea 605305 15848 100.0 True +u-alb 3001029 15705 100.0 True +ab-be 50030 15686 99.94 True +u-suhti 21702 15672 0.0 False +e-rdw 3635986 15504 0.0 False +u-krea 1010458 15417 0.0 False +p-inr 600493 15107 0.0 False +-l-ind 20537 15069 0.0 False +s-tsh 3002832 14964 100.0 True +p-k 101999 14906 100.0 True +b-eryt 2629409 14818 100.0 True +p-na 103622 14701 100.0 True +p-tfr 4720 14678 100.0 True +p-inr-hy 7355261 14671 0.0 False +u-alb-o 1030 14540 100.0 True +p-gt 605248 14228 100.0 True +p-bil 4592 13960 100.0 True +s-ph 3008523 13864 0.0 False +e-mch 2629412 13628 100.0 True +e-mchc 2629413 13626 100.0 True +p-krea 604429 13625 100.0 True +e-mcv 2629411 13624 100.0 True +p-psa 606117 13586 100.0 True +b-be 105 13570 100.0 True +b-ghb-a1c 1001560 13570 100.0 True +e-rdw 606834 13559 0.0 False +p-krea 2605305 13533 100.0 True +u-suhtih 0352 13353 0.0 False +u-alb 1029 13089 100.0 True +b-ghb-a1c 3001560 12943 100.0 True +b-hba1c 620261 12911 100.0 True +b-neut 6003238 12889 100.0 True +p-d-25 1001220 12837 0.0 False +u-suhti-o 600748 12537 0.0 False +u-ph 600817 12513 0.0 False +s-b12-vit 3001137 12395 100.0 True +cb-be 151 12224 100.0 True +fe-folaat 1001414 12140 100.0 True +p-inr 2607047 11963 0.0 False +p-ferrit 606675 11905 0.0 False +b-la 6002203 11845 100.0 True +p-probnp 611261 11741 0.0 False +u-suhti 0730 11634 0.0 False +s-b12-tc2 616408 11610 0.0 False +hdl/kol. 14578 11548 100.0 True +p-alb 605243 11507 100.0 True +oma-gluk 256 11472 0.0 False +b-lymfos 3223 11425 95.72 True +ntkmom 20758 11282 0.0 False +pappakmom 20757 11279 0.0 False +l-lymfos 191 11276 100.0 True +l-lymf(a) 9235 11241 100.0 True +b-eos 1001330 11218 100.0 True +hcgbvkmom 20756 11204 0.0 False +p-k 2101999 11202 100.0 True +l-eosin 598 11163 100.0 True +l-monos 197 11118 100.0 True +baso 1000599 11034 100.0 True +baso 1003157 11033 100.0 True +b-eosin 1330 11027 100.0 True +eos 1000598 11022 100.0 True +b-basof 3157 11017 100.0 True +lymf 1003223 11005 100.0 True +lymf 1000191 11002 100.0 True +mono 1000197 10995 100.0 True +mono 1003230 10979 100.0 True +b-neutr 3238 10973 97.48 True +neut 1000612 10966 100.0 True +p-bil 1001185 10881 100.0 True +p-uraat 4533 10864 98.62 True +b-erblast 602870 10860 100.0 True +b-hb-a1c 1605248 10849 100.0 True +l-basof 599 10834 100.0 True +l-neutr 612 10825 100.0 True +vb-ph 8270 10807 0.0 False +b-hba1c 7037277 10779 100.0 True +b-erytrosyytit,tilavuusosuus 1358 10629 77.48 True +fs-trfesat 10100 10586 100.0 True +p-ca 605254 10486 100.0 True +p-psa-v 4900 10483 100.0 True +l-mono(a) 399 10383 100.0 True +p-inr 104520 10380 0.0 False +p-psa 615989 10243 100.0 True +p-ca-albk 613776 10182 100.0 True +u-ph-huu 8869 10033 0.0 False +l-eos(a) 1332 10031 100.0 True +u-ominp-h 20567 10003 0.0 False +s-ca(akt) 3005097 9965 100.0 True +s-ca(7.4) 3005099 9951 100.0 True +p-afos 1605000 9948 100.0 True +p-antifxa 3828 9909 55.18 True +s-d-25 1220 9900 100.0 True +s-ph(akt) 3005098 9886 100.0 True +-i-ind 20538 9849 0.0 False +p-ferrit 1001395 9800 100.0 True +p-ca 4598 9683 100.0 True +u-albkre 2010455 9660 100.0 True +p-na 2103622 9653 100.0 True +u-alb 1010457 9615 0.0 False +pt-gfreepi 2917425 9579 0.0 False +l-neut(a) 398 9540 100.0 True +cp-gluk-hy 0589 9537 100.0 True +p-gluk 3001471 9483 100.0 True +p-tromboplastiiniaika,inr,tt 4520 9455 0.0 False +oma-crp 462 9415 100.0 True +p-inr 601850 9385 0.0 False +non-hdl 10138 9376 0.0 False +u-alb 10457 9359 100.0 True +p-bil 3005299 9162 100.0 True +u-prot-o 2529 9022 0.0 False +b-hba1c 7036281 8950 100.0 True +u-ph 0375 8890 0.0 False +l-baso(a) 1168 8791 100.0 True +p-alat 604418 8789 100.0 True +pt-gfreepi 1662604 8649 0.0 False +u-suhtih 0373 8539 0.0 False +p-tfr 1001949 8538 100.0 True +l-lymf 46 8470 100.0 True +cb-be 10191 8455 100.0 True +l-eos 690 8445 100.0 True +b-neutr 1003238 8441 0.0 False +b-basof 1003157 8427 0.0 False +b-neut 689 8421 100.0 True +b-eosin 1001330 8409 0.0 False +b-lymfos 1003223 8392 0.0 False +b-monos 1003230 8357 0.0 False +p-tnt 4532 8290 99.98 True +l-basof 1000599 8256 0.0 False +b-hkr 0639 8250 0.0 False +l-eosin 1000598 8245 0.0 False +l-lymfos 1000191 8204 0.0 False +l-monos 1000197 8170 0.0 False +l-neutr 1000612 8132 0.0 False +p-tromboplastiiniaika,inr-tulos 4520 8123 100.0 True +fp-gluk 2101468 8115 100.0 True +p-tsh 604895 8112 100.0 True +b-lymf 43 8077 100.0 True +p-psa-v 1004254 8055 100.0 True +s-t4-v 3002836 8052 100.0 True +fp-kol-ldl 604453 8045 100.0 True +ca++/7.40 596 8031 100.0 True +p-asat 4591 7931 100.0 True +p-amyl 4589 7910 100.0 True +fs-ph 0683 7870 0.0 False +oma-crp 5567927 7821 0.0 False +fp-transf 4567 7798 100.0 True +s-b12-vit 1137 7786 100.0 True +b-monos 42 7780 100.0 True +psa-v/psa 1010792 7743 0.0 False +b-eos 39 7740 100.0 True +fp-kol 604452 7719 100.0 True +l-monos 693 7709 100.0 True +l-baso 692 7698 100.0 True +fp-trigly 604454 7693 100.0 True +fp-kol-hdl 604451 7692 100.0 True +u-albkre 605850 7676 0.0 False +fp-kol-ldl 2605269 7672 100.0 True +ca-ion 597 7662 100.0 True +b-pvk+t 2474 7644 0.0 False +p-tnt 607465 7620 100.0 True +b-baso 40 7617 100.0 True +fs-ca++/7.40 596 7616 0.0 False +fs-ca-ion 597 7610 100.0 True +l-neut 688 7435 100.0 True +inr-vieri 603043 7407 0.0 False +p-psa-v 631060 7364 100.0 True +s-tsh 2832 7316 71.35 True +p-inr 606000 7295 0.0 False +b-neut 1103238 7241 100.0 True +crp 0113 7205 0.0 False +s-iglck-v 4966 7204 100.0 True +p-d-25 6401 7190 100.0 True +b-neut 2103238 7172 0.0 False +pt-gfreepi 4605 7034 0.0 False +b-trom 3629414 7028 100.0 True +s-ttgaba 1885 7011 91.32 True +s-iglcl-v 4950 7000 100.0 True +crp,tk 602087 6993 0.0 False +raskauksienmäärä,g Ras001 6870 0.0 False +b-erytroblastit 50610 6765 100.0 True +l-neut(a) 3629125 6740 0.0 False +l-lymf(a) 3629126 6737 0.0 False +l-mono(a) 3629127 6736 0.0 False +p-ferrit 617876 6735 100.0 True +l-eos(a) 3629128 6734 0.0 False +l-baso(a) 3629129 6728 0.0 False +p-uraat 1002884 6716 100.0 True +b-monos 2103230 6701 0.0 False +b-baso 2103157 6667 0.0 False +s-b12-tc2 617336 6642 100.0 True +p-alb 3005318 6638 100.0 True +cb-be 5400 6637 100.0 True +l-neut(a) 2629125 6627 0.0 False +p-gluk,tk 602079 6621 0.0 False +l-lymf(a) 2629126 6620 0.0 False +p-tnt 615402 6615 0.0 False +l-mono(a) 2629127 6615 0.0 False +l-eos(a) 2629128 6606 0.0 False +l-baso(a) 2629129 6602 0.0 False +b-monos 1103230 6564 0.0 False +fp-gluk 101468 6555 100.0 True +p-tt-inr 3576 6546 0.0 False +b-baso 1103157 6522 0.0 False +p-afos 1605265 6512 0.0 False +vb-be 5386 6466 100.0 True +p-alb 1001028 6456 100.0 True +pt-gfreepi 3653122 6405 0.0 False +p-d-25 1220 6393 100.0 True +s-k/l-s-v 9319 6363 100.0 True +s-ca-ion 9010 6361 100.0 True +p-bil 605249 6352 100.0 True +p-amyl 1001078 6319 100.0 True +snabb-inr 0743 6267 0.0 False +p-crp 604422 6213 100.0 True +p-mg 4601 6178 100.0 True +u-ph 100325 6168 0.0 False +b-hba1c 606590 6161 100.0 True +b-hb-a1c 604449 6157 100.0 True +fp-kol-ldl 605269 6150 0.0 False +s-ca(7.4) 5099 6137 100.0 True +fe-folaat 4001414 6129 100.0 True +cb-pco2 1622 6119 100.0 True +p-psa 1605032 6073 100.0 True +p-afos 2605265 6055 0.0 False +p-amyl 3005208 6052 100.0 True +non-hdl(paasto) 10138 6004 0.0 False +kolesteroli/hdl-suhde 10037 6002 0.0 False +s-ph(akt) 5098 5988 100.0 True +s-ca-ion 597 5881 0.0 False +p-tsh 1663381 5873 0.0 False +synnytystenmäärä,p Ras002 5868 0.0 False +s-ca++/7.40 596 5861 0.0 False +p-inr 4004520 5803 0.0 False +u-suhtih 100323 5732 0.0 False +fp-fe 4529 5720 100.0 True +p-d-25 632020 5675 100.0 True +pt-gfreepi 622040 5635 0.0 False +oma-p-crp 7037327 5623 100.0 True +b-leukosyytit 2218 5619 100.0 True +cb-tt-inrp 602165 5576 0.0 False +p-inr-hy 50285 5557 0.0 False +b-ly 1605097 5514 100.0 True +p-inr-vt 10757 5501 100.0 True +p-tsh 3657914 5475 0.0 False +fe-folaat 3014140 5457 100.0 True +p-uraat 605270 5451 100.0 True +p-inr 602670 5440 0.0 False +u-ph-o 13039 5438 0.0 False +b-ghb-a1c 1560 5330 100.0 True +s-ph 45093 5321 0.0 False +u-happamuusaste 1530 5304 0.0 False +p-tfr 605894 5294 0.0 False +fp-kol-hdl 2605268 5285 100.0 True +fp-kol-hdl 605268 5275 0.0 False +fp-trigly 2605285 5259 100.0 True +vb-be 50032 5232 100.0 True +14272 14272 5212 0.0 False +fp-trigly 605285 5194 0.0 False +b-erblast 3629130 5193 0.0 False +u-osmoest 606697 5188 87.05 True +nu-albkrea 618158 5154 100.0 True +p-uraat 3004533 5133 100.0 True +b-erblast 2629130 5130 0.0 False +p-tfr 617378 5088 100.0 True +p-tt-inr 1605218 5071 0.0 False +s-ttgaba 3001885 5066 100.0 True +vp-ph 1531 5059 0.0 False +p-asat 605247 5051 100.0 True +s-ca-iona 8524 5048 100.0 True +b-hba1c,tk 606670 5039 0.0 False +cb-hco3-st 154 5012 100.0 True +p-fidd 4113 5011 100.0 True +p-crp 605304 5001 100.0 True +s-fsh 1422 4996 51.01 True +-trfesat 4606 4851 100.0 True +p-tsh 622558 4847 0.0 False +p-psa-suh 4868 4811 99.68 True +s-ca-iona 3008524 4794 100.0 True +s-ca-ion 4009010 4788 100.0 True +s-ca-ion 2019 4747 100.0 True +e-retik 2582 4736 100.0 True +u-osmole 626820 4685 100.0 True +b-hba1c,t 606670 4683 0.0 False +u-ph 0067 4678 0.0 False +b-ghb-a1c 600221 4645 0.0 False +u-lier 2630671 4632 0.0 False +fp-pi 1431 4623 100.0 True +psa-v/psa 10792 4619 100.0 True +u-eryt 1101344 4619 0.0 False +u-leuk 1102221 4598 100.0 True +p-urea 4534 4590 100.0 True +mononukleaariset Mon1223 4588 0.0 False +neutrofiilit Neu1222 4535 0.0 False +s-cdt 4101 4511 100.0 True +b-erybla 644813 4508 100.0 True +pt-gfreepi 621337 4507 100.0 True +p-t4-v 604894 4480 100.0 True +p-gt 604424 4455 100.0 True +b-hba1c 3636046 4443 0.0 False +e-rdw 644812 4417 100.0 True +p-crp-o 7035803 4405 100.0 True +zb-ph 1532 4383 0.0 False +p-b12-vit 1001137 4382 100.0 True +p-psa-suh 606119 4330 100.0 True +p-psa-v 606118 4329 100.0 True +u-ominaispaino 18811 4321 0.0 False +b-hba1c 607475 4297 100.0 True +p-tt 3001731 4288 100.0 True +p-ph 50099 4275 0.0 False +s-ccpab 4744 4273 82.87 True +cb-inrc-c 0113 4271 0.0 False +b-eos 6001330 4262 100.0 True +u-ph 0325 4255 0.0 False +pappakmom 620902 4251 0.0 False +ntkmom 620900 4251 0.0 False +hcgbvkmom 620904 4251 0.0 False +u-suhtih 0323 4246 0.0 False +p-pi 4595 4227 100.0 True +ab-be 9224 4217 100.0 True +p-t4-v 1663382 4194 0.0 False +vb-be 9220 4185 100.0 True +pt-gfre 643362 4171 100.0 True +fp-ca 1002013 4162 100.0 True +inr-pika 868 4158 0.0 False +b-ghb-a1c,tk 600221 4155 0.0 False +f-calpro 4803 4155 100.0 True +u-gluk-0 1479 4154 0.0 False +pituus(cm) Pit484 4130 0.0 False +p-psa-suh 1605034 4125 100.0 True +cb-tt-inrpika 602165 4095 0.0 False +b-monos 1605103 4068 100.0 True +b-baso 1605100 4068 100.0 True +pt-gfreepi 3960575 4060 0.0 False +s-k/l-s-v 11927 4016 0.0 False +p-asat 3005281 4016 100.0 True +pt-gfreepi 622237 4011 0.0 False +pt-gfreepi 635156 3935 0.0 False +b-ghba1cp 0591 3927 100.0 True +b-erybla 7716 3907 0.0 False +p-ca-albk 8293 3905 100.0 True +cd4/cd8 10825 3896 0.0 False +p-ck 4517 3884 100.0 True +p-bil 1605005 3880 100.0 True +p-rf 8849 3828 100.0 True +fp-pth 4560 3819 79.63 True +e-retik 3002582 3806 100.0 True +p-iga 5577788 3796 0.0 False +ph 1530 3794 0.0 False +fs-kol 2095 3794 100.0 True +fs-kol-ldl 2099 3772 100.0 True +u-ph 0105 3763 0.0 False +u-leuk 3002221 3757 100.0 True +cp-glukoosi,ihopistosn,vieritestihoitoyksikössä 0589 3716 0.0 False +p-probnp 603605 3695 0.0 False +u-osmest 3000292 3639 100.0 True +p-ck 1002134 3634 100.0 True +b-neut 14272 3631 100.0 True +b-hba1c 1632264 3626 0.0 False +b-erytroblastit 19978 3614 100.0 True +eosinofiil. Eos1224 3566 0.0 False +vb-be 8273 3561 100.0 True +u-bact 21015 3529 0.0 False +p-tsh 630117 3525 0.0 False +pt-gfreepi 4076549 3515 0.0 False +u-albkre 9522 3486 100.0 True +p-ck 3004517 3477 100.0 True +pt-gfre 1672520 3457 0.0 False +fp-urea 4573 3447 100.0 True +u-ph 0614 3445 0.0 False +ab-ph(t) 11128 3425 0.0 False +oma-p-crp 57377 3405 0.0 False +u-suhtih 0612 3401 0.0 False +u-kemseul,ph 103268_4 3399 0.0 False +p-k 1002001 3397 100.0 True +u-kemseul,ph 609625_3 3392 0.0 False +pt-fib-4 21799 3385 0.0 False +p-na 1002382 3378 100.0 True +p-afos 605265 3378 0.0 False +u-krea 6002145 3355 100.0 True +p-probnp 1604551 3326 100.0 True +p-amyl 1605003 3308 100.0 True +p-inr 605212 3296 0.0 False +oma-gluk 57048 3291 0.0 False +u-krea 1606670 3286 0.0 False +u-krea 0510 3281 100.0 True +u-epit 2630670 3275 0.0 False +ab-ph 3001527 3269 0.0 False +p-gluk-vt 10756 3258 100.0 True +pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava 11326 3256 100.0 True +p-bil-kj 605250 3253 100.0 True +sy-leuk 3080 3253 99.73 True +p-tnt 1605039 3186 100.0 True +fp-krea 603104 3173 0.0 False +u-epit 615359 3164 100.0 True +u-lier 615358 3161 100.0 True +p-gt 1605018 3159 100.0 True +p-t4-v 622559 3156 0.0 False +b-neut 103238 3150 99.97 True +p-iga 4827 3149 100.0 True +u-leuk 615357 3136 100.0 True +oma-gluk 4601160 3124 0.0 False +u-eryt 615356 3120 100.0 True +u-ph-o 103667 3097 0.0 False +u-lier 3630671 3096 0.0 False +u-eryt 2101344 3083 0.0 False +p-ck 1605010 3082 100.0 True +cb-ph 1001528 3067 0.0 False +p-tnt 603603 3065 0.0 False +u-leuk 2102221 3059 0.0 False +p-ck-mbm 1004236 3054 100.0 True +li-leuk 2219 3052 100.0 True +b-ly 1103223 3048 100.0 True +li-eryt 1342 3048 100.0 True +u-kemseul,omin.p 103268_2 3045 0.0 False +p-ph 8522 3036 0.0 False +fs-trigly 2770 3024 100.0 True +p-amylp 605246 3021 100.0 True +vb-be 10085 3014 100.0 True +b-neut 5597073 3007 0.0 False +fs-kol-hdl 2097 3005 100.0 True +fp-pth 1002457 2996 100.0 True +p-psa-suh 631061 2982 100.0 True +fb-leuk 2218 2978 100.0 True +s-k/l-s-v 50207 2977 0.0 False +u-epit 607576 2974 0.0 False +p-t4-v 630118 2973 0.0 False +u-eryt 607597 2964 0.0 False +b-ph 1531 2963 0.0 False +p-alb 1605002 2961 100.0 True +s-testo 2735 2947 99.97 True +p-inr-pika 606328 2945 0.0 False +b-hba1c 623599 2943 0.0 False +u-lier 607577 2943 0.0 False +u-eryt 11344 2934 100.0 True +crp(päiv.hoitaja) akiea0002 2927 100.0 True +p-uraat 1605043 2924 100.0 True +pt-gfre 10055629 2920 100.0 True +fs-ca-ion 1000597 2886 0.0 False +fs-ca++/7.40 1000596 2879 0.0 False +p-crp-vt 10759 2870 100.0 True +b-hkr 4001358 2868 100.0 True +u-suhtih 2715 2861 0.0 False +cb-pco2 1001622 2859 100.0 True +u-epit 980 2847 100.0 True +cb-be 1000151 2836 100.0 True +p-inr-pi 606328 2836 0.0 False +s-li 3002260 2834 100.0 True +e-retik 1002582 2828 100.0 True +b-eryt 4001341 2825 100.0 True +e-mcv 4001357 2825 100.0 True +b-hb 4001552 2825 100.0 True +b-leuk 4002218 2825 100.0 True +e-rdw 615255 2825 100.0 True +e-mch 4001558 2825 100.0 True +e-mchc 4001557 2824 100.0 True +b-trom 4002791 2821 100.0 True +u-lier 981 2816 100.0 True +cb-hco3-st 1000154 2814 100.0 True +cb-crp 101217 2782 0.0 False +s-tshrab 4965 2775 84.77 True +f-calpro 613422 2753 0.0 False +p-mg 605264 2747 100.0 True +fs-folaat 1001416 2731 100.0 True +u-suhti-o 715 2722 0.0 False +b-hba1c 606591 2696 100.0 True +fp-gluk 603107 2696 100.0 True +p-ck-mbm 1605011 2673 100.0 True +erytroblastit 8518 2654 100.0 True +p-krea 1605262 2652 100.0 True +pt-kt/v1 15024 2648 0.0 False +fp-krea 2142 2634 100.0 True +s-ph 1606713 2634 0.0 False +p-t3-v 1002775 2622 0.0 False +p-ck 605261 2609 100.0 True +s-apob/a1 02249 2604 0.0 False +u-albkre 604448 2599 100.0 True +b-baso 103157 2598 100.0 True +p-uraat 1605306 2597 0.0 False +p-cmvnh 4777 2592 82.64 True +pt-gfre 10066523 2588 100.0 True +fp-kol-ind 633151 2587 0.0 False +s-klotsa 609927 2569 100.0 True +s-ph 2606713 2552 0.0 False +b-monos 103230 2542 100.0 True +s-norklot 609913 2537 100.0 True +l-neut(a) 1629125 2534 0.0 False +l-lymf(a) 1629126 2531 0.0 False +l-eos(a) 1629128 2529 0.0 False +l-mono(a) 1629127 2529 0.0 False +l-baso(a) 1629129 2527 0.0 False +u-veri-o 2947 2498 0.0 False +u-krea 2606670 2492 0.0 False +lieriöt 40527 2485 100.0 True +fp-kol-ind 6518 2479 0.0 False +pt-gfre 2928608 2478 0.0 False +s-ph 7368425 2475 0.0 False +ab-emäsylimäärä 10083 2472 100.0 True +b-la 102203 2468 100.0 True +p-k 4001999 2440 100.0 True +u-ph-hy 0368 2439 0.0 False +seeruminhappamuusaste 8523 2429 0.0 False +fp-ca 4514 2426 100.0 True +p-gluk 6001471 2422 100.0 True +p-bnp 4709 2420 99.98 True +b-la 2102203 2414 100.0 True +fp-pi 1001432 2410 100.0 True +b-crp-vt 6592 2408 100.0 True +vb-pco2 1623 2408 100.0 True +li-igg-ind 3450 2406 100.0 True +p-afos 604419 2405 100.0 True +vb-po2 1537 2405 100.0 True +p-d-25 607216 2394 0.0 False +p-na 4003622 2385 100.0 True +l-eos 1332 2379 100.0 True +s-igg4 4228 2367 100.0 True +b-hba1c 604640 2366 100.0 True +ly-cd4/cd8 9270 2357 0.0 False +zb-be 11453 2350 0.0 False +b-inr-pik 8120 2340 100.0 True +u-albkrea 4511 2339 100.0 True +s-psa 3642 2336 100.0 True +pt-gfre 626572 2320 100.0 True +p-ca-iona 3000335 2305 100.0 True +s-k/l-s-v 10747 2302 0.0 False +p-pi 605252 2296 100.0 True +p-ca 7368221 2282 100.0 True +b-eos 632777 2278 0.0 False +b-baso 632778 2278 0.0 False +b-ly 632780 2278 0.0 False +l-baso 632773 2278 0.0 False +b-neut 632776 2278 0.0 False +l-neut 632771 2278 0.0 False +l-eos 632772 2278 0.0 False +b-mono 632779 2278 0.0 False +l-ly 632775 2278 0.0 False +l-mono 632774 2278 0.0 False +p-ca-ion. 3013900 2258 100.0 True +s-valpr 3003681 2253 100.0 True +p-t4-v 3657915 2253 0.0 False +s-prl 3002507 2247 100.0 True +ab-pco2 3001621 2242 100.0 True +ab-be 3009224 2242 100.0 True +ab-hco3-st 3009314 2242 100.0 True +p-b12-vit 608792 2241 100.0 True +ab-po2 3001535 2237 100.0 True +p-igg 4828 2235 100.0 True +p-alat 1605242 2229 100.0 True +f-calpro 606035 2216 0.0 False +s-mkomp-1 9982 2215 100.0 True +e-rdw 2644100 2199 100.0 True +fp-kol-ldl 2629664 2194 0.0 False +vp-happamuusaste 1531 2193 0.0 False +crp-pika 9011 2188 100.0 True +vb-ph 3001531 2182 0.0 False +oma-inr 617344 2181 0.0 False +u-osmole 2900806 2178 100.0 True +fp-kol-hdl 1002097 2171 100.0 True +hdl/kol 602250 2171 100.0 True +pt-gfre 3663121 2170 0.0 False +p-tsh 2917625 2158 100.0 True +p-probnp 609847 2150 100.0 True +b-hba1cvt 11246 2149 82.01 True +p-alat 101024 2137 100.0 True +p-krea 628929 2137 100.0 True +pt-gfre 628930 2130 100.0 True +f-calpro 616027 2127 100.0 True +p-gluk 1001473 2123 0.0 False +u-lieriö 9244 2104 100.0 True +p-tsh 613256 2093 100.0 True +pt-gfreepi 626168 2078 100.0 True +u-lieriöt 40527 2067 100.0 True +p-tnt 602562 2054 100.0 True +pf-leuk 2220 2053 99.08 True +u-osmest 292 2048 100.0 True +p-inr-vt 621377 2039 0.0 False +p-ca-iona 335 2036 100.0 True +fp-gluk 4001468 2033 100.0 True +p-fidd 621300 2032 100.0 True +s-mypnabm 4151 2032 0.0 False +b-erblast 1629130 2028 0.0 False +pf-eryt 1343 2022 99.97 True +u-alb 6001029 2008 100.0 True +p-kysc 4507 1998 100.0 True +s-ca(akt) 5097 1998 100.0 True +p-psa 604836 1997 100.0 True +s-cdt 3004101 1997 100.0 True +vb-happamuusaste 1531 1984 0.0 False +s-trigly 6427 1983 100.0 True +p-tsh 2664021 1983 0.0 False +u-epit 3630670 1982 0.0 False +s-kol-hdl 6430 1972 100.0 True +p-tsh 603956 1972 100.0 True +p-crp-o 613895 1963 100.0 True +s-k 2001 1963 100.0 True +s-hcgbv/d 620903 1962 100.0 True +s-pappa 620901 1961 100.0 True +l-mono 0905 1954 100.0 True +pika-inr 607101 1953 0.0 False +u-ph akiosa0004 1943 0.0 False +l-eos 0902 1930 100.0 True +p-ca-ion. 13900 1918 100.0 True +u-alb 0129 1917 100.0 True +s-d-25 649206 1915 0.0 False +p-t3-v 6362 1914 100.0 True +pt-gfreepi 645275 1913 0.0 False +p-t4-v 613257 1907 100.0 True +s-igg1 4225 1897 100.0 True +s-prot 2516 1897 100.0 True +s-igg2 4226 1893 100.0 True +p-crp 7010044 1892 100.0 True +crp,tk 70001 1890 0.0 False +p-alat 7010034 1888 100.0 True +p-inr 603120 1885 0.0 False +s-dnanab. 12610 1881 100.0 True +b-tacro 4360 1877 100.0 True +s-cdt 617036 1876 100.0 True +vb-emäsylimäärä 50032 1871 100.0 True +s-b12-tc2 1101142 1870 100.0 True +u-epit 10096 1855 100.0 True +s-igg3 4227 1853 100.0 True +s-iga 3001666 1832 100.0 True +e-rdw 3631804 1829 0.0 False +u-ph-huu 606264 1823 0.0 False +s-testo 3002735 1823 100.0 True +fp-kol-ldl 1605259 1823 100.0 True +l-neutr 0901 1798 100.0 True +s-pr3ab 4160 1796 76.4 True +s-kol-ldl 6432 1796 100.0 True +nu-albkrea 23572 1796 100.0 True +pappakmom 5568787 1793 0.0 False +ntkmom 5568790 1792 0.0 False +p-tt-inr 3575 1792 0.0 False +hcgbvkmom 5568788 1792 0.0 False +u-osmol 2444 1792 100.0 True +l-lymf 0907 1790 100.0 True +s-testo 1002735 1790 100.0 True +b-hba1c 603372 1782 100.0 True +u-ominp-h 618136 1775 0.0 False +s-rf 3003550 1770 100.0 True +p-t4-v 603957 1753 100.0 True +p-ld 1002194 1741 100.0 True +cp-gluk-po 8716 1736 0.0 False +-nt 617897 1730 100.0 True +s-crp-o 1217 1730 100.0 True +fp-fe 3005323 1727 100.0 True +p-t4-v 2664022 1726 0.0 False +p-cea 6363 1719 100.0 True +cp-gluk 0350 1718 100.0 True +sao2 600605 1715 0.0 False +p-inr-pik 603692 1713 0.0 False +e-erytrosyytit,kokojakauma 11086 1709 100.0 True +vb-ph 0531 1708 0.0 False +u-ph-0 3367 1707 0.0 False +pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava 13470 1706 100.0 True +p-uraat 2605306 1704 0.0 False +l-baso 1168 1702 99.99 True +p-fidd 1004113 1700 100.0 True +cb-phpika 14234 1696 0.0 False +fp-laktaat 3002184 1693 100.0 True +p-d-25 2101220 1682 0.0 False +crp-pika 602611 1680 0.0 False +s-immunoglobuliini,kevyetketjut,vapaat,kappa-lambda-suhde 11927 1672 0.0 False +fp-transf 3004567 1666 100.0 True +l-lymf 9235 1666 100.0 True +u-tutk-1-oma,ph 1605222_4 1647 0.0 False +b-inr-pik 1630673 1646 0.0 False +pt-ekg-12 6001270 1646 0.0 False +fp-kol 7010048 1643 100.0 True +u-osmole 20479 1642 100.0 True +b-be 0105 1641 100.0 True +u-tutk-1-,ph 1605222_4 1640 0.0 False +p-amylp 4590 1639 100.0 True +fp-kol-ldl 7010050 1638 100.0 True +u-suhtih 0715 1630 100.0 True +s-enaab 3022 1628 100.0 True +p-inr 601708 1624 0.0 False +fp-kol 1605256 1618 100.0 True +p-crp-o 1217 1613 100.0 True +pt-gfreepi 2663222 1612 0.0 False +l-eos 604160 1608 100.0 True +b-monos 604163 1608 100.0 True +l-ly 607191 1608 100.0 True +b-baso 604164 1608 100.0 True +b-neut 607193 1608 100.0 True +l-monos 607192 1608 100.0 True +b-ly 604162 1608 100.0 True +b-eos 607194 1608 100.0 True +l-baso 604161 1607 100.0 True +l-neut 607190 1607 100.0 True +s-ca-ion 622231 1606 100.0 True +cb-be 4923 1595 100.0 True +fp-fe 1002566 1595 100.0 True +s-digoks 1256 1584 96.73 True +p-psa 2628984 1582 100.0 True +fe-folaat 1414 1571 100.0 True +b-retik 3025810 1562 100.0 True +p-glukpoc 9439 1562 100.0 True +p-psa 1628984 1561 0.0 False +s-pappa 4549 1550 100.0 True +p-ld 3004526 1550 100.0 True +s-mypnabg 4150 1535 99.91 True +p-luakptt 4426 1534 100.0 True +u-albkre 603497 1526 100.0 True +p-psa 3628984 1516 100.0 True +b-hba1c 616356 1512 100.0 True +u-kemseul,u-ph 101881_5 1507 0.0 False +b-inrpika 94520 1503 100.0 True +p-crp 1605304 1496 100.0 True +fp-ca 3004514 1494 100.0 True +s-cdt 1004101 1489 0.0 False +b-crp-o 9343 1485 0.0 False +s-hcgbv/d 20754 1479 100.0 True +pt-gfreepi 41320 1474 0.0 False +p-ferrit 2630464 1473 100.0 True +fp-transf 1002756 1471 100.0 True +l-mon 399 1466 100.0 True +u-epipien 50203 1465 100.0 True +paastoseeruminph 50100 1457 0.0 False +u-suhti 617971 1456 0.0 False +b-hba1c,tk 70003 1453 0.0 False +-nt 20248 1448 100.0 True +s-tsh 102832 1446 96.13 True +b-hba1c 10017548 1444 100.0 True +u-leuk-bv 637391 1442 100.0 True +hba1c-pika 870 1437 0.0 False +s-prot 1002516 1436 100.0 True +p-fidd 3004113 1425 100.0 True +s-prealb 1002494 1420 100.0 True +fp-trigly 1605258 1418 100.0 True +s-igg-sum 9115 1410 100.0 True +fp-kol-hdl 1605257 1402 100.0 True +p-ca-albk 7368224 1400 100.0 True +p-mg 3005285 1400 100.0 True +p-psa-v 1635178 1396 0.0 False +s-van 3277 1396 100.0 True +s-tfr 6001949 1394 100.0 True +happamuusaste,virtsasta 13039 1393 0.0 False +tffesat 4606 1386 100.0 True +e-rdw 630871 1382 100.0 True +u-tutk-1-oma,sg 1605222_3 1372 0.0 False +u-kemseul,u-suhti 101881_3 1362 0.0 False +gt-cdt-ind 50526 1349 0.0 False +cb-ph 0528 1349 0.0 False +s-chpnabm 4204 1348 88.46 True +p-korsol 1002129 1346 100.0 True +pt-gfre 633141 1345 0.0 False +hemolyysi-indeksi 20536 1344 0.0 False +oma-p-gluk 4601160 1343 0.0 False +fp-kol-hdl 7010049 1342 100.0 True +fp-glukoosi 1468 1341 99.93 True +fp-trigly 7010320 1339 100.0 True +s-ccpab 603704 1339 0.0 False +s-cea 3002034 1339 100.0 True +tffesat 2010359 1334 0.0 False +oma-u-tutk,u-ph 4601161_1 1333 0.0 False +u-tutk-1-,sg 1605222_3 1332 0.0 False +b-leuk 2629408 1325 100.0 True +u-osmole 0574 1324 0.0 False +fp-urea 1002888 1322 100.0 True +p-bil-kj 4593 1319 100.0 True +ab-be 5382 1317 100.0 True +p-mg 1002303 1315 100.0 True +e-rdw 7370521 1313 100.0 True +b-hba1c 615779 1313 100.0 True +b-crp 0801 1312 0.0 False +p-ld 4526 1311 100.0 True +b-b-cd19 8374 1310 100.0 True +s-b12-tc2 2101142 1310 0.0 False +tromboplastiiniaika,inr-tulostus,plasmasta 4520 1310 100.0 True +b-ly/abs 9060 1306 100.0 True +s-korsol 3002129 1306 100.0 True +b-ba/abs 9062 1306 100.0 True +u-krea 1002145 1303 100.0 True +pt-gfre 3969737 1302 0.0 False +u-epilevy 50200 1298 100.0 True +p-tsh 7010179 1297 100.0 True +eos 598 1295 100.0 True +emäsylimäärä,laskimoveri 5386 1291 0.0 False +p-asat 604421 1290 100.0 True +u-leuk 102221 1286 100.0 True +u-krea 606670 1286 0.0 False +b-hba1c 2897005 1285 100.0 True +u-a1miglo 15132 1280 0.0 False +u-eryt 101344 1277 100.0 True +cb-be 10084 1275 100.0 True +l-neut 620537 1264 0.0 False +b-crp-o 1217 1252 100.0 True +e-rdw 643282 1251 100.0 True +b-hba1c 2897006 1245 100.0 True +p-tsh 10015837 1245 100.0 True +i-stathct akiea0019 1240 0.0 False +b-hkr 1333 1237 0.0 False +p-igm 4829 1233 100.0 True +pappakmom 12973 1232 0.0 False +u-ph 325 1232 0.0 False +ntkmom 12976 1231 0.0 False +hcgbvkmom 12974 1231 0.0 False +i-statna akiea0021 1231 100.0 True +i-statk akiea0020 1230 0.0 False +i-statcrea akiea0017 1228 0.0 False +oma-hba1c 5592308 1226 0.0 False +s-prot 3002516 1225 100.0 True +b-leuk 625424 1225 100.0 True +ph,seerumista,osatutk 11554 1224 0.0 False +s-rf 3550 1222 72.46 True +cb-po2 1536 1218 100.0 True +p-crp-hy 7035741 1217 100.0 True +p-gfreepi 11326 1212 100.0 True +p-amyl 605245 1202 100.0 True +p-tsh 10015842 1202 100.0 True +b-tbifng 54254 1200 100.0 True +u-lier 1630671 1194 0.0 False +s-ttgaba 6001885 1191 100.0 True +p-t4-v 10015838 1185 100.0 True +p-ferrit 1605017 1182 100.0 True +b-hkr 602706 1179 100.0 True +p-psa-v 3636304 1178 0.0 False +p-iga 616267 1177 100.0 True +oma-crp-pi 610504 1174 0.0 False +p-tsh 603267 1173 100.0 True +b-hba1c 3636047 1169 0.0 False +b-la 603144 1168 0.0 False +b-lymf 3000043 1167 0.0 False +b-neut 650867 1167 0.0 False +p-gfrtest 15326 1165 0.0 False +l-baso 3000692 1164 0.0 False +l-eos 3000690 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100.0 True +fp-trfesat 3009906 1077 100.0 True +u-ominaispaino 616 1077 0.0 False +p-t4-v 603268 1077 100.0 True +pt-gfreepi 107310 1077 0.0 False +b-retind 3009200 1075 100.0 True +pt-gfreepi 637332 1072 100.0 True +fp-pi 3001431 1071 100.0 True +p-kol-ldl 633118 1067 0.0 False +u-suhti 0352 1067 0.0 False +u-albkre 7033173 1061 100.0 True +u-krea 100274 1058 100.0 True +oma-crp-pika 610504 1056 0.0 False +u-ph 9102 1056 0.0 False +b-pvk+tkd,leuk 102475_1 1051 100.0 True +nu-albkrea 2630765 1048 0.0 False +u-tutk-1,ph 103268_5 1048 0.0 False +s-tpoab 4028 1047 56.22 True +oma-crp 613992 1045 0.0 False +s-mpoabg 4149 1044 98.78 True +b-crp-pik 4052989 1042 0.0 False +cb-be 0769 1042 100.0 True +p-krea 1605305 1038 100.0 True +s-ca-ion 1604774 1036 100.0 True +eos 1000602 1035 0.0 False +bla 1000342 1034 0.0 False +baso 1000603 1034 0.0 False +oma-crp 604324 1033 0.0 False +lymf 1000600 1031 0.0 False +p-prl 1002507 1029 100.0 True +metam 1000345 1025 0.0 False +mono 1000601 1025 0.0 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True +b-ghb-a1c 4001560 683 100.0 True +b-crp 1217 681 100.0 True +ab-ph 10730 681 0.0 False +l-myel 344 681 100.0 True +s-prl 2507 676 94.07 True +l-eos 602 676 100.0 True +b-crp-pika 4052989 675 0.0 False +l-ly 10465 674 100.0 True +p-uraat 605306 673 0.0 False +l-lymf 45080 672 0.0 False +l-baso 603 672 100.0 True +s-t3-v 3002775 669 100.0 True +-cd4-solujensuhdecd8-soluihin 10825 665 0.0 False +b-neut 10754 665 100.0 True +l-monos 10466 662 100.0 True +s-prealb 3002494 661 100.0 True +l-mono 601 657 100.0 True +l-bla 342 657 100.0 True +cu-alb-mi 3004084 656 100.0 True +l-neut 10459 652 100.0 True +s-cdt 1104101 651 0.0 False +p-kol 649647 651 0.0 False +u-osmole 4055509 651 0.0 False +pt-gfreepi 647682 650 0.0 False +pt-gfreepinosatutkimus 15326 649 0.0 False +crp-pika 90 648 0.0 False +u-osmole 3636281 647 0.0 False +u-ph-pika 4053012 647 0.0 False +l-nst 346 646 100.0 True +p-kol-ldl 649649 644 0.0 False +s-pappa 619548 643 100.0 True +s-hcgbv 619549 643 100.0 True 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600319 619 100.0 True +neut 600315 619 100.0 True +eos 600318 619 100.0 True +mono 600323 619 100.0 True +fp-kol-ldl 1605269 619 100.0 True +lymf 600316 619 100.0 True +p-fsh 6368 618 100.0 True +s-ige 3001673 617 100.0 True +s-ca-i7.4 631497 616 0.0 False +s-ca-iona 631498 614 0.0 False +u-osmest 633075 613 0.0 False +b-crp 5568387 613 0.0 False +oma-u-tutk,u-nitr-o 4601161_2 612 0.0 False +mb-ph 9242 612 0.0 False +glukoosi(päiv.hoitaja) akiea0005 611 0.0 False +p-inr-vt 9103 610 0.0 False +s-ph 631499 609 0.0 False +p-bkvnh 6001 607 63.26 True +s-ferrit 1395 606 100.0 True +u-alb 1101029 605 100.0 True +s-dnaab 8092 605 100.0 True +p-urea 605271 603 100.0 True +p-psa-v 2900846 602 100.0 True +s-valpr 1003681 602 100.0 True +s-sappih 3379 599 100.0 True +l-eos 9214 598 100.0 True +p-prealb 4618 598 99.21 True +cb-crp 1217 598 0.0 False +u-ph 647864 597 0.0 False +pt-gfreepi 7310 594 0.0 False +s-lzm 2289 593 100.0 True +s-crp 1216 592 100.0 True +ntkmom 2897206 591 0.0 False 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True +pt-gfre 2673263 516 0.0 False +l-monos 3230 516 98.19 True +s-cdt 6004101 516 100.0 True +p-tfr 603042 514 0.0 False +s-mkomp-2 8957 514 100.0 True +u-alb 606901 514 0.0 False +p-asat 2605264 513 100.0 True +b-hb 0121 513 0.0 False +p-ck-mbm 607466 511 100.0 True +s-mkomp-3 8958 510 100.0 True +u-leuk 606691 510 100.0 True +s-k/l-s-v 616263 510 0.0 False +b-la 4002203 508 100.0 True +p-psa 613258 506 100.0 True +fp-trigly 1605285 505 100.0 True +l-lymf 0366 505 100.0 True +s-mkomp-4 8959 504 100.0 True +du-ca 1002011 502 100.0 True +s-ana 1002819 501 0.0 False +s-ca-iona 11564 501 100.0 True +b-hba1c/pi 1632285 501 0.0 False +p-haptog 1001545 500 100.0 True +fs-folaat 101416 498 100.0 True +u-suhtih 647862 498 0.0 False +pikau-stix,u-ph 602556_4 498 0.0 False +p-crp-o 8818 496 100.0 True +s-epo 1339 495 68.57 True +b-hkr 101358 495 61.52 True +p-shbg 1002737 495 100.0 True +oma-ghb-a1c 473 494 0.0 False +fp-kol-hdl 1605268 494 100.0 True +nu-alb 4836 494 100.0 True +p-tnt 621002 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0.0 False +p-psa-suh 609297 413 0.0 False +b-inr-pik 2630673 412 0.0 False +p-uraat 1605270 412 100.0 True +b-hb-a1c 7010327 411 100.0 True +fp-b6-vit 6080 411 100.0 True +p-fidd 104113 411 100.0 True +kolesterolinjahdl-kolesterolinsuhde VI0020 411 0.0 False +p-psa 1615989 410 100.0 True +nu-albkrea 3630765 410 0.0 False +oma-crp 10011274 410 0.0 False +p-afos 1605244 410 100.0 True +pt-audio/i 2279505 410 0.0 False +b-mono 9231 409 99.98 True +p-tfr 604443 408 100.0 True +p-igg 616268 408 100.0 True +p-c3 4545 408 100.0 True +l-lymf(a) 4009235 407 100.0 True +cp-gluk 1605207 407 100.0 True +b-ly 4003223 407 100.0 True +b-monos 4003230 407 100.0 True +l-baso(a) 4001168 407 100.0 True +l-mono(a) 4000399 407 100.0 True +pappakmom 3945256 407 0.0 False +b-hb 101552 407 100.0 True +l-eos(a) 4001332 407 100.0 True +ntkmom 3945255 407 0.0 False +b-baso 4003157 407 100.0 True +l-neut(a) 4000398 407 100.0 True +hcgbvkmom 3945258 406 0.0 False +p-korsol 7037273 406 100.0 True +p-bil 1605325 405 100.0 True +s-dmklots 4208 405 60.81 True +u-leuk-o 6002223 405 0.0 False +pt-ekg-12 1270 405 0.0 False +punasolujenerittelylaskenta 20408 404 0.0 False +l-mono 9213 403 100.0 True +fs-folaat 2101416 401 100.0 True +u-prot-o 6001030 400 0.0 False +u-kemseul,omin.p 1881_OMIN.P 399 0.0 False +s-psa-v/t 622478 398 0.0 False +s-k/l-s-v 0339 396 100.0 True +b-konedif,lymf 603012_2 395 0.0 False +b-konedif,eos 603012_4 395 0.0 False +b-konedif,neutro 603012_1 395 0.0 False +b-konedif,baso 603012_5 395 0.0 False +u-alb 4001029 395 100.0 True +p-pct 6462 395 100.0 True +b-konedif,monos 603012_3 395 0.0 False +b-hba1c/pika 1632285 393 0.0 False +p-kol-ldl 1674162 392 0.0 False +b-qr-crp 5017728 392 100.0 True +p-fsh 7037272 390 100.0 True +s-c1inh 1209 390 100.0 True +mittaustulos(mg/l) Mit403 390 0.0 False +p-c-reaktiivinenproteiinipikahoitoyksiköt 8518 389 100.0 True +s-ttgaba 1020053 387 100.0 True +s-tpoab 6004028 387 100.0 True +b-leuk 102218 386 100.0 True +vb-ahco3vt 11581 386 100.0 True 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True +u-levyep 3967098 333 0.0 False +s-toxoabg 2749 333 100.0 True +p-urea 1605077 331 100.0 True +p-tromboplastiiniaika-pika,inrpika-tulos 50489 331 0.0 False +p-tnt 1629464 331 0.0 False +s-t4-v 4002836 329 100.0 True +nu-alb 2606685 329 0.0 False +u-epit 1630670 329 0.0 False +l-mono 0915 328 100.0 True +du-prot 3002513 328 95.76 True +u-osmole 1635090 328 0.0 False +l-lymf 9212 327 100.0 True +l-lymf 0903 327 100.0 True +p-preurea 11500 326 100.0 True +p-non-hdl 7908 326 0.0 False +inr-vieri 96 326 0.0 False +p-amylp 1634830 326 0.0 False +li-gluk 1470 326 100.0 True +u-osmole 617905 326 100.0 True +b-leuk-vt 6589 326 100.0 True +s-afp 1001040 326 100.0 True +p-igm 616269 325 100.0 True +ab-ph(t) 0007 325 0.0 False +l-eos 0912 324 100.0 True +s-ige 6001673 324 100.0 True +p-t4-v 3959916 324 100.0 True +vb-bepika 14233 324 100.0 True +p-d-25 609559 324 0.0 False +psa-v/psa 610015 323 100.0 True +p-psa-v 610014 323 100.0 True +u-albkre 604312 323 100.0 True +b-hba1c 3632264 323 0.0 False +p-pc 3003435 322 100.0 True +s-timotee 7009 321 100.0 True +s-ca19-9 3003412 321 100.0 True +p-prl 1605031 320 100.0 True +u-phstix 9004 318 0.0 False +b-ly 7010064 318 100.0 True +u-ph 101530 318 0.0 False +ab-be 0204 317 100.0 True +u-levyep 3658861 316 0.0 False +u-albkre 603121 316 100.0 True +s-dgpabg 618505 316 0.0 False +oma-fp-glu 602182 316 0.0 False +u-sakka,leuk 102600_2 316 0.0 False +s-prot 6002516 316 100.0 True +u-pienep 3658862 315 0.0 False +u-huum-7,ph 606595_8 315 0.0 False +pappakmom 3897207 313 0.0 False +cu-alb-mi 4084 313 100.0 True +ntkmom 3897206 313 0.0 False +hcgbvkmom 3897209 313 0.0 False +u-sakka,epit 102600_3 311 0.0 False +s-tpoab 3004028 311 67.55 True +p-inr 3576 311 0.0 False +p-reninm 6339 311 100.0 True +p-haptog 617396 309 100.0 True +p-inr-vt 653 308 0.0 False +u-krea 1102145 306 100.0 True +u-ph 10099 305 0.0 False +u-sakka,makrof 102600_4 305 0.0 False +b-lymf 9230 305 100.0 True +sao2 9743 305 0.0 False +p-kol 1674160 304 0.0 False +u-ph 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True +u-eryt. 14056 292 100.0 True +s-ca12-5 3003414 291 100.0 True +u-ph 600334 291 0.0 False +u-albkrea 606080 291 0.0 False +p-t4-v 2738612 291 0.0 False +epit.solut 14058 291 0.0 False +p-tni 621001 289 0.0 False +u-osmol 3002444 289 100.0 True +s-borrabm 4096 289 100.0 True +sy-leuk 1003080 289 100.0 True +fs-pth 1603680 289 0.0 False +s-dnanab 1261 288 58.48 True +b-retik 7354422 288 100.0 True +b-baso 7010065 288 100.0 True +b-monos 7010066 288 100.0 True +pt-fvspido 618833 288 0.0 False +pt-fvspiro 1002680 287 0.0 False +l-myelos 676 286 100.0 True +s-klotsa 602622 285 100.0 True +fp-trfesat 8855 285 100.0 True +u-leuk-o 0222 284 0.0 False +cb-inr-oma 21392 284 0.0 False +s-vlseabm 618440 284 0.0 False +p-omagluk 600554 284 0.0 False +p-t4-v 4077050 283 100.0 True +b-inr-vt 6597 283 0.0 False +s-hepyabg 3003954 282 100.0 True +s-li 6002260 282 100.0 True +p-bnp 620999 282 0.0 False +p-myogl 615783 282 0.0 False +emäsylimäärä,koneveri 5429 281 0.0 False +pt-gfreep 21218 281 0.0 False +b-la 1102203 281 100.0 True +u-kemseul,ph 103268_5 279 0.0 False +s-k/l-s-v 9055 279 0.0 False +p-amyl 1605266 279 100.0 True +kol/hdl 5008 278 0.0 False +p-crp 2605304 278 100.0 True +fp-c-pept 616725 278 0.0 False +baso 3157 277 100.0 True +u-phv 1364 275 0.0 False +b-hba1c/pi 3657981 275 0.0 False +fs-transferiininrautakyllästeisyys 10100 275 0.0 False +p-tt 615925 275 0.0 False +s-hcgbv/d 608216 274 0.0 False +p-kol-hdl 1674161 274 0.0 False +s-papp-a 2628524 274 0.0 False +fe-folaat 604293 274 100.0 True +emäsylimäärä,laskimoverestä,pikatesti 14233 273 0.0 False +lieriöt 14059 273 100.0 True +u-suhtih 373 272 0.0 False +s-k/l-s-v 0626 272 0.0 False +ab-ph 9452 272 0.0 False +l-promyel 675 272 100.0 True +sy-solut 3002658 272 0.0 False +p-rf 1605251 271 100.0 True +-transf 20426 269 100.0 True +du-iglck 98320 269 0.0 False +p-probnp 2897325 269 0.0 False +p-tt-inr 104520 268 100.0 True +kolesterolinjahdl-kolest.suhde 0020 268 0.0 False 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False +b-lymf 3223 252 100.0 True +fb-folaat 609485 251 100.0 True +p-rf 605269 251 100.0 True +s-tshrab 606133 251 0.0 False +u-krea 617804 251 0.0 False +b-eosinofiilit 10753 250 100.0 True +fs-fe 2566 248 100.0 True +fp-nh4-ion 1001071 248 100.0 True +l-neut 0905 248 100.0 True +p-psa-suh 613260 247 100.0 True +virtsam. 637191 247 0.0 False +p-psa-v 613259 247 100.0 True +b-eryt 600774 246 100.0 True +b-leuk 600773 246 100.0 True +cb-hbo2sat 1534 246 100.0 True +b-leuk-vt 622078 246 0.0 False +b-trom 600777 246 100.0 True +leukosyytit 2218 246 100.0 True +pt-glomerulustensuodatusnopeus,estimoitu,mdrd-kaava 6000 246 100.0 True +p-c-pept 576 246 100.0 True +b-hb 600775 246 100.0 True +p-psa-v 104254 245 100.0 True +s-igm 1688 245 100.0 True +l-ly 1605113 245 100.0 True +s-klotsa 2003964 245 100.0 True +l-neut 1605331 244 100.0 True +fe-folaat 1101414 244 100.0 True +cb-gluk-vt 3616 243 100.0 True +l-baso 0913 243 100.0 True +ly-cd4/cd8 0869 242 0.0 False +s-hcgbv/d 2897208 242 100.0 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148 100.0 True +vb-be 0347 148 100.0 True +u-alb/kre,u-alb 601384_2 148 0.0 False +s-hcg-b-v 613101 148 100.0 True +p-bnp 3658241 148 0.0 False +pt-glomerulussuodosnopeus,estimoituckd-epikaavallakystatiinic:stä 21904 147 100.0 True +b-hkr 11358 147 0.0 False +f-calpro 1665000 146 0.0 False +p-tt-inr 44520 146 0.0 False +b-hkr 2101358 146 100.0 True +s-hbsab 1001608 146 0.0 False +s-ph 627274 146 0.0 False +u-huum-10,ph 630291_11 146 0.0 False +b-baso 9227 145 99.99 True +u-suhteellinentiheys,osatutkimus 2715 145 0.0 False +s-testo 6002735 145 100.0 True +s-mypnabg 600469 145 0.0 False +pt-paino 10015 145 0.0 False +s-ruokaer 3000508 144 0.0 False +p-pc 3435 144 100.0 True +p-posturea 11501 144 100.0 True +14593 14593 144 0.0 False +s-prot 1102516 144 100.0 True +s-achr-ab 3427 143 100.0 True +u-seulonta,ph 32681_PH 143 0.0 False +u-k 3002004 143 100.0 True +pt-gfre 10055630 143 100.0 True +s-tpoab 1104028 142 0.0 False +s-mkomp-3 5597580 142 0.0 False +b-hb-a1c 626068 142 100.0 True 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False +s-ohkarba 3003957 127 100.0 True +leukpika 0109 127 0.0 False +s-psa-v/t 10096 127 100.0 True +fs-fe 622597 127 0.0 False +fs-e-vit 3169 127 100.0 True +omaastmatesti 620126 127 0.0 False +b-eryt 1101341 126 100.0 True +p-digoks 604892 126 0.0 False +fs-transf 3002756 126 100.0 True +s-afsuol2 633100 125 0.0 False +b-hb-co 1566 125 100.0 True +s-afsuol1 633121 125 100.0 True +fe-folaat 14140 125 100.0 True +b-tnt-o 104464 125 0.0 False +s-afsuol3 633101 125 100.0 True +s-afos 3001046 125 100.0 True +b-hba1c/pika 61289 125 0.0 False +u-bakt-vi 1155 125 0.0 False +s-afmakro 602864 125 100.0 True +p-probnp 10010875 125 100.0 True +s-afmaksa 602862 125 100.0 True +s-afluust 602861 125 100.0 True +s-t4-vdi 1000811 124 100.0 True +s-mtx 2346 124 100.0 True +p-luakptt 607079 124 0.0 False +p-luakrvv 607078 124 0.0 False +pd-leuk 902 123 100.0 True +s-hcg-b-v 604532 123 100.0 True +b-hba1c 614611 123 100.0 True +vb-he-tase,vb-be.b 101543_2 123 0.0 False +b-hba1c-om 2632285 123 0.0 False 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+s-hcgbv/d 2644960 118 0.0 False +s-afp 3001040 118 57.58 True +u-suhti 0349 118 0.0 False +ua-ph 8915 118 0.0 False +s-b2miglo 3001171 118 100.0 True +monos 1602925 118 100.0 True +s-clahere 7121 118 100.0 True +timotei 1000973 118 100.0 True +s-ebvabg 1336 117 100.0 True +s-pct 1773 117 100.0 True +p-tnt 602456 117 100.0 True +p-tfr 10015175 117 100.0 True +l-baso 6001168 117 100.0 True +s-vzvabg 3004467 116 0.0 False +crpvieritesti 9041 116 0.0 False +sy-muutsol 3000284 116 100.0 True +p-lh 7037274 116 100.0 True +sy-lymf 3000283 116 100.0 True +sy-gran 3000272 116 100.0 True +b-cya 1003606 116 100.0 True +p-krea 648008 115 100.0 True +oma-fp-glu 610095 115 0.0 False +s-koirae 3000431 115 0.0 False +p-ca-albk 1613776 115 100.0 True +metam 345 115 100.0 True +inr,tk 604590 115 0.0 False +s-normet 2407 114 99.87 True +f-calpro 605777 114 0.0 False +s-viseabg 20607 114 0.0 False +p-na-vt 629738 114 0.0 False +p-ck-mb 3004524 114 100.0 True +p-k-vt 629757 114 0.0 False +s-aldos 627663 114 0.0 False +p-mb/ck 3009364 114 0.0 False +p-ca12-5 7037269 114 100.0 True +oma-hba1c 630432 113 0.0 False +ab-be 9216 113 100.0 True +p-gluk-o 13975 113 100.0 True +s-piiinp 3682 113 98.49 True +u-huum-10,ominaispaino 630291_12 113 0.0 False +u-levyep 3000291 113 100.0 True +s-hbsab 3001608 113 98.86 True +p-lh/fsh 615523 113 0.0 False +p-igg 1605020 113 100.0 True +mono 601 113 100.0 True +b-leuk 1600041 112 100.0 True +s-kissae 3000430 112 0.0 False +s-c3 3002106 112 100.0 True +b-tnt-o 4464 112 99.91 True +s-afos 11046 112 100.0 True +u-albkre 625978 112 100.0 True +cb-tt-inr 9520 112 100.0 True +cb-be 50031 112 100.0 True +p-probnp 3945215 111 0.0 False +tromboplastiiniaika,inr-tulostus,kapillaariverestä 10757 111 0.0 False +p-tnt 600822 111 100.0 True +e-mch 3629412 111 100.0 True +s-lamotri 3004328 111 100.0 True +s-c4 3002107 111 100.0 True +l-eos 0012 111 0.0 False +p-korsol 604893 110 100.0 True +l-liusk 9202 110 100.0 True +p-aptt 6002783 110 100.0 True +p-ferrit 10016494 110 100.0 True +p-il6 10779 110 100.0 True +myel 344 110 100.0 True +f-calpro 630232 110 0.0 False +e-rdw 10838 110 100.0 True +b-hba1c 2632265 110 0.0 False +p-at3-spr 3011103 109 100.0 True +testo/shbg 828 109 0.0 False +ly-t-cd4/cd8,t-auttaja/estäjäsolujensuhde 50009 109 0.0 False +ab-po2 0322 109 100.0 True +oma-b-fid 7351887 109 0.0 False +cb-emäsylimäärä 10191 108 100.0 True +pika-virtsaliuska,u-ph 602140_5 108 0.0 False +p-fviii 1097 108 100.0 True +f-calpro 3658782 108 0.0 False +fs-fe 3002566 108 100.0 True +fp-gluk/pi 2606304 108 0.0 False +p-psa-suh 3946036 108 100.0 True +vb-emäsylimäärä 11584 108 0.0 False +pika-virtsaliuska,u-suhti-o 602140_3 108 0.0 False +fs-trfesat 4008498 108 100.0 True +s-psa-v 104254 107 100.0 True +b-trom 1102791 107 100.0 True +fp-fe 602776 107 0.0 False +s-hs-crp 8022 107 100.0 True +s-klotsa 619537 107 0.0 False +s-trypt 9872 107 100.0 True +phadiatop 970 107 100.0 True +p-hcyst 1867 106 100.0 True +s-psa-t 603280 106 100.0 True +ph 5010 106 0.0 False +ps-crp 100110 106 0.0 False +e-mchc 3629413 106 100.0 True +s-gliadie 14063 106 0.0 False +s-ccpab 610918 106 100.0 True +p-probnp 602403 106 100.0 True +cb-gluk-v 1469 105 0.0 False +fluor,nat,fl-clue 1621921_3 105 0.0 False +b-erytrosyytit 1341 105 100.0 True +s-bopeaba 3003311 105 100.0 True +u-sakka,leuk 2600_LEUK 105 0.0 False +b-leuk-hoi 9911018 105 0.0 False +u-ph. 4083929 105 0.0 False +fluor,nat,fl-hiiva 1621921_2 105 0.0 False +du-metnef 3002336 105 100.0 True +ab-pco2 0321 105 100.0 True +fp-gluk0 9542 105 100.0 True +s-vzvabm 1806 105 0.0 False +fs-transf 2756 105 100.0 True +s-mpoab 4148 105 65.9 True +fp-transf 603428 104 0.0 False +b-lymf 604947 104 100.0 True +s-bopeabg 3003312 104 100.0 True +l-mono 604944 104 100.0 True +b-baso 625831 104 100.0 True +l-neut 604941 104 100.0 True +l-eos 605029 104 100.0 True +pt-lämpöt 6000612 104 100.0 True +l-lymf 604942 104 100.0 True +s-risper 605908 104 0.0 False +u-suhti. 4083930 104 0.0 False +u-osmole 3635090 104 0.0 False +fluor,nat,muuta 1621921_4 104 0.0 False +du-normet 3002406 104 100.0 True +l-baso 604945 104 100.0 True +p-t3-v 106362 104 0.0 False +baso 603 104 100.0 True +b-mono 604948 104 100.0 True +p-mg 604431 103 100.0 True +p-d-25 1101220 103 100.0 True +s-osmol 3002443 103 100.0 True +s-koivue 3000415 103 0.0 False +pf-prot 2515 103 100.0 True +s-gadab 3004400 103 100.0 True +p-ph 45094 102 0.0 False +p-d-25 4001220 102 100.0 True +f-calpro 1631884 102 0.0 False +fluor,nat,fl-leuk 1621921_1 102 0.0 False +cb-be 0206 102 100.0 True +s-pujoe 3000419 102 100.0 True +s-alfgale 13772 102 100.0 True +du-krea 2141 102 100.0 True +p-c3 1010790 102 0.0 False +b-fidd-o 13042 102 100.0 True +s-igf1 1003253 101 0.0 False +s-antitry 3001038 101 100.0 True +cb-be 0418 101 100.0 True +p-rf 1629868 101 0.0 False +fp-renin 3003603 101 100.0 True +s-d-25 625400 101 100.0 True +u-prot 3002519 101 71.93 True diff --git a/scripts/injection/data/plot_name_level.tsv b/scripts/injection/data/plot_name_level.tsv new file mode 100644 index 0000000..bf062cc --- /dev/null +++ b/scripts/injection/data/plot_name_level.tsv @@ -0,0 +1,1026 @@ +TEST_NAME total_count top_prevalence +-cd4-solujensuhdecd8-soluihin 665 0.0 +-cdt 239 100.0 +-crppikatesti 196 0.0 +-cyp4f2 1093 0.0 +-glutamyylitransferaasi-desialotransferriini-indeksi 720 0.0 +-h-ind 39809 0.0 +-i-ind 9849 0.0 +-kt/v,daugirdaksenkaava 176 0.0 +-l-ind 15069 0.0 +-nt 5011 100.0 +-ph 903 0.0 +-s.yht. 844 0.0 +-slco1b1 869 0.0 +-transf 269 100.0 +-trfesat 5306 100.0 +120mp-glu 228 100.0 +14272 5212 0.0 +14593 144 0.0 +5400 373 0.0 +6820 170 0.0 +:glutamyylitransferaasi-desialotransferriini-indeksi 268 0.0 +ab-ahco3vt 157 100.0 +ab-be 52398 99.98203824573457 +ab-be-vt 210 0.0 +ab-caionvt 122 100.0 +ab-emäsylimäärä 3580 100.0 +ab-hco3-st 2478 100.0 +ab-pco2 3058 99.99767495094834 +ab-pco2-vt 170 0.0 +ab-ph 380522 98.68999999999998 +ab-ph(t) 4545 0.0 +ab-ph-vt 168 0.0 +ab-po2 3071 99.99763920547053 +ab-po2-vt 179 0.0 +as-eryt 767 100.0 +as-leuk 773 100.0 +astmatesti 136 0.0 +b-6-me-mp 488 0.0 +b-6-tgn 482 0.0 +b-angap 138 100.0 +b-b-cd19 1310 100.0 +b-ba/abs 1306 100.0 +b-baso 357874 99.8588409835393 +b-basof 19444 100.0 +b-be 15770 100.0 +b-co 483 100.0 +b-cr 456 100.0 +b-crp 3350 100.0 +b-crp-o 3079 100.0 +b-crp-os 462 0.0 +b-crp-ospkl 477 0.0 +b-crp-pik 1042 0.0 +b-crp-pika 798 0.0 +b-crp-v 202 100.0 +b-crp-vt 3956 100.0 +b-cya 116 100.0 +b-eos 381192 99.82971040616191 +b-eosin 19436 100.0 +b-eosinofiilit 250 100.0 +b-erblast 314346 100.0 +b-erybla 169159 100.0 +b-eryt 2702180 100.0 +b-erytroblastit 10379 100.0 +b-erytrosyytit 105 100.0 +b-erytrosyytit,tilavuusosuus 10924 77.48 +b-erytrosyytit,tilavuusosuus,pikahoitoyksiköt 196 0.0 +b-fidd-o 102 100.0 +b-fidd-vt 150 0.0 +b-fosfatidyylietanoli 344 0.0 +b-ghb-a1c 38232 100.0 +b-ghb-a1c,tk 5295 0.0 +b-ghba1c/p 183 0.0 +b-ghba1cp 3927 100.0 +b-gluk 295 0.0 +b-gluk-vt 154 0.0 +b-glukoosi,hoitoyksikönvieritesti,kokoveri 521 0.0 +b-hb 895386 100.0 +b-hb,tk 528 0.0 +b-hb-a1c 18829 99.88999628233044 +b-hb-co 125 100.0 +b-hb-hoi 136 0.0 +b-hb-met 133 100.0 +b-hb-pika 281 0.0 +b-hb-vt 1252 100.0 +b-hba1c 355680 100.0 +b-hba1c,t 4683 0.0 +b-hba1c,tk 6492 0.0 +b-hba1c-om 123 0.0 +b-hba1c-oma 239 0.0 +b-hba1c/pi 961 0.0 +b-hba1c/pika 867 0.0 +b-hba1cvt 3104 83.51364179104479 +b-hkr 1750455 66.66232347980981 +b-hkrhoi 155 0.0 +b-inr-pik 5420 100.0 +b-inr-vt 283 0.0 +b-inrpika 1503 100.0 +b-inrvieri 218 0.0 +b-k 420 0.0 +b-keto/pik 358 0.0 +b-konedif,baso 395 0.0 +b-konedif,eos 395 0.0 +b-konedif,lymf 395 0.0 +b-konedif,monos 395 0.0 +b-konedif,neutro 395 0.0 +b-krea 421 0.0 +b-la 156187 100.0 +b-laktevt 563 100.0 +b-leuc-v 538 0.0 +b-leuk 2609979 100.0 +b-leuk-hoi 105 0.0 +b-leuk-vt 806 100.0 +b-leuk/pi 367 0.0 +b-leukosyytit 5619 100.0 +b-ly 334997 99.39827286689368 +b-ly/abs 1306 100.0 +b-lymf 9905 100.0 +b-lymfos 19817 95.72 +b-mono 2791 99.98405458089668 +b-monos 373170 99.61871550051363 +b-multiplateadp 150 0.0 +b-na 418 0.0 +b-neut 678675 99.57806235359783 +b-neutr 19414 97.48 +b-neutrofiilit 257 100.0 +b-pco2 559 100.0 +b-peth 1406 100.0 +b-ph 3521 100.0 +b-po2 558 100.0 +b-pvk+t 7644 0.0 +b-pvk+tkd 782 0.0 +b-pvk+tkd,leuk 1051 100.0 +b-qr-crp 392 100.0 +b-retik 25381 100.0 +b-retind 1699 100.0 +b-t-cd4 128 100.0 +b-tacro 1877 100.0 +b-tbifng 1582 98.5439570164349 +b-ti 295 100.0 +b-tnt-o 237 99.91 +b-trom 2413261 100.0 +b-tromb 74939 100.0 +baso 25346 100.0 +bla 1034 0.0 +c-reaktiivinenproteiini,tk:ntekemä 201 0.0 +c6-indeksi 333 0.0 +ca++/7.40 27372 100.0 +ca++/ph7.4 343 100.0 +ca-ion 27146 100.0 +cb-ahco3 177 100.0 +cb-be 36509 100.0 +cb-bepika 634 0.0 +cb-crp 3380 0.0 +cb-emäsylimäärä 421 100.0 +cb-gluk-v 105 0.0 +cb-gluk-vt 243 100.0 +cb-hb 340 100.0 +cb-hbo2sat 246 100.0 +cb-hco3-st 7826 100.0 +cb-inr,pikamääritys 193 0.0 +cb-inr-oma 284 0.0 +cb-inrc-c 4271 0.0 +cb-inrpika 463 0.0 +cb-leuk-hy 187 100.0 +cb-pco2 8978 100.0 +cb-ph 104777 100.0 +cb-phpika 1696 0.0 +cb-po2 1218 100.0 +cb-tt-inr 112 100.0 +cb-tt-inrp 5576 0.0 +cb-tt-inrpika 4841 0.0 +cd4/cd8 3896 0.0 +cp-c-reaktiivinenproteiini,ihopiston,hoitoyksikössä 261 0.0 +cp-crp-hy 942 100.0 +cp-gluk 2125 100.0 +cp-gluk-hy 9537 100.0 +cp-gluk-po 1736 0.0 +cp-glukoosi,ihopistosn,vieritestihoitoyksikössä 3716 0.0 +cp-inr-hy 181 0.0 +cp-inr-vt 369 0.0 +crp 7205 0.0 +crp(päiv.hoitaja) 2927 100.0 +crp(vo:nyhteydessäotettu),tth 1267 100.0 +crp,tk 8883 0.0 +crp-pika 5345 100.0 +crppika 470 100.0 +crpvieri 571 100.0 +crpvieritesti 116 0.0 +cu-alb 1604 100.0 +cu-alb-mi 1340 100.0 +cu-kesto 767 100.0 +cu-tilav 770 100.0 +cu-vm 706 100.0 +cyp4f2-geeninnukleotidivariaatiot,dna-tutkimus 424 0.0 +du-ca 1118 99.2278175313059 +du-iglck 269 0.0 +du-iglcl 170 0.0 +du-krea 263 100.0 +du-metnef 235 100.0 +du-normet 235 100.0 +du-prot 1593 91.78401757689893 +du-tilav 338 100.0 +e-erytrosyytit,kokojakauma 1709 100.0 +e-mch 859143 99.9348185692021 +e-mchc 305071 100.0 +e-mcv 862958 100.0 +e-punasolujenkokojakauma 870 100.0 +e-rdw 444914 100.0 +e-retik 11832 100.0 +emäsylimäärä,kapillaariveri 991 0.0 +emäsylimäärä,koneveri 281 0.0 +emäsylimäärä,laskimoverestä,pikatesti 273 0.0 +emäsylimäärä,laskimoveri 1291 0.0 +emäsylimäärä,valtimoveri 346 100.0 +eos 14128 100.0 +eosin 441 100.0 +eosinofiil. 3566 0.0 +epit.solut 291 0.0 +epiteelit 152 100.0 +erblast 744 0.0 +erytroblastit 2654 100.0 +f-calpro 12541 100.0 +f-elast1 1570 100.0 +fb-folaat 251 100.0 +fb-gluk 302 100.0 +fb-leuk 78137 100.0 +fe-folaat 26985 100.0 +fibrosis-4-indeksi 458 0.0 +fibrosis-4indeksi 162 0.0 +fluor,nat,fl-clue 105 0.0 +fluor,nat,fl-hiiva 105 0.0 +fluor,nat,fl-leuk 102 0.0 +fluor,nat,muuta 104 0.0 +fosfatidyylietanoli 121 0.0 +fp-b6-vit 411 100.0 +fp-c-pept 477 100.0 +fp-ca 8237 100.0 +fp-ctx 253 0.0 +fp-fe 11013 100.0 +fp-gluk 377752 99.98829160401532 +fp-gluk,t 708 0.0 +fp-gluk/pi 108 0.0 +fp-gluk0 105 100.0 +fp-glukoosi 1341 99.93 +fp-kol 245681 100.0 +fp-kol-hdl 235216 100.0 +fp-kol-ind 5066 0.0 +fp-kol-ldl 300072 100.0 +fp-kolesteroli 562 100.0 +fp-krea 6187 100.0 +fp-laktaat 2177 100.0 +fp-nh4-ion 774 100.0 +fp-pi 8730 100.0 +fp-pth 9057 91.41072871811858 +fp-renin 101 100.0 +fp-renin-p 134 100.0 +fp-transf 12440 100.0 +fp-trfesat 2145 100.0 +fp-trigly 239085 100.0 +fp-urea 5197 100.0 +fs-a-vit 227 100.0 +fs-ace 202 100.0 +fs-c-pept 942 100.0 +fs-ca++/7.40 10495 0.0 +fs-ca-ion 10496 100.0 +fs-ca-ion/ph7.40 122 100.0 +fs-ca-iona 134 100.0 +fs-cga 167 99.82 +fs-e-vit 127 100.0 +fs-fe 483 100.0 +fs-folaat 26281 100.0 +fs-kol 3794 100.0 +fs-kol-hdl 3005 100.0 +fs-kol-ldl 3772 100.0 +fs-ph 30288 0.0 +fs-pi 803 100.0 +fs-pth 450 0.0 +fs-rf 293 100.0 +fs-sappih 1213 100.0 +fs-transf 231 100.0 +fs-transferiininrautakyllästeisyys 275 0.0 +fs-trfesat 10694 100.0 +fs-trigly 3024 100.0 +gluk-pika 1002 100.0 +glukoosi(päiv.hoitaja) 611 0.0 +glukoosi,pikatesti,veri 214 0.0 +glukoosi,vieritutkimus 140 0.0 +glukvieri 188 0.0 +gt-cdt-ind 2058 0.0 +happamuusaste 377 0.0 +happamuusaste,virtsasta 1393 0.0 +happamuusaste,virtsasta,vieritesti 122 0.0 +hb(päiv.hoitaja) 816 0.0 +hb-pika 345 100.0 +hba1c-pika 1437 0.0 +hcgbvkmom 20354 0.0 +hdl/kol 88970 100.0 +hdl/kol. 11548 100.0 +hemolyysi-indeksi 1344 0.0 +hoiglukstx 185 0.0 +i-statcl 574 0.0 +i-statcrea 1228 0.0 +i-statglu 573 0.0 +i-stathb 437 0.0 +i-stathct 1240 0.0 +i-statk 1230 0.0 +i-statna 1231 100.0 +i-staturea 522 0.0 +iga/prealb 1082 0.0 +ihopisto 206 0.0 +inr,tk 115 0.0 +inr-pika 4278 0.0 +inr-vieri 8630 0.0 +inr/hoito 1127 0.0 +inrpika 166 0.0 +kalium,hoitoyksikönvieritesti,veri 191 0.0 +koivu 123 100.0 +kol/hdl 397 0.0 +kol/hdl-su 945 0.0 +kol/hdlsuh 66868 0.0 +kolesteroli/hdl-suhde 33783 0.0 +kolesterolinjahdl-kolest.suhde 268 0.0 +kolesterolinjahdl-kolesterolinsuhde 549 0.0 +kt/v 168 0.0 +l-baso 16704 99.99862029831388 +l-baso(a) 48061 100.0 +l-basof 19090 100.0 +l-bla 1576 100.0 +l-blastit 295 100.0 +l-eos 20712 100.0 +l-eos(a) 49313 100.0 +l-eosin 19408 100.0 +l-liusk 110 100.0 +l-ly 5324 94.98890676296783 +l-lymf 17718 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g7fSyx4%JFgnlsV!c!}=WX>#Ev2aXzL?05O)KOrlrI{*Lx literal 0 HcmV?d00001 From cdc40b6bccb48fc8cb41e5f899bf1b12ed3f9af0 Mon Sep 17 00:00:00 2001 From: pete Date: Tue, 26 May 2026 16:10:53 +0300 Subject: [PATCH 03/20] improved logic of categorization and injection. adde bimodaliuty --- scripts/injection/README.md | 158 +- scripts/injection/data/plot_name_id_level.tsv | 2763 ----------------- scripts/injection/data/summary_table.md | 9 + .../data/test_names_exploration_scatter.png | Bin 121856 -> 87646 bytes scripts/injection/explore_test_name.py | 813 +++++ scripts/injection/explore_test_name.sh | 163 - scripts/injection/injection_engine.py | 661 ++++ scripts/injection/injection_extraction.sh | 87 - scripts/injection/parquet/run.sh | 11 - scripts/injection/plot_exploration.py | 66 + 10 files changed, 1676 insertions(+), 3055 deletions(-) delete mode 100644 scripts/injection/data/plot_name_id_level.tsv create mode 100644 scripts/injection/data/summary_table.md create mode 100644 scripts/injection/explore_test_name.py delete mode 100644 scripts/injection/explore_test_name.sh create mode 100644 scripts/injection/injection_engine.py delete mode 100644 scripts/injection/injection_extraction.sh delete mode 100644 scripts/injection/parquet/run.sh create mode 100644 scripts/injection/plot_exploration.py diff --git a/scripts/injection/README.md b/scripts/injection/README.md index e13451a..4364d75 100644 --- a/scripts/injection/README.md +++ b/scripts/injection/README.md @@ -2,69 +2,165 @@ The goal is to identify lab measurements that have a numeric value but are missing a unit, and to characterise the unit distribution of the matching records that do have a unit — so that a unit can be confidently assigned to the missing ones. +## Summary + +![scatter](test_names_exploration_scatter.png) + +*Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements* + +| Threshold | UNAMBIGUOUS test names | UNAMBIGUOUS measurements | AMBIGUOUS test names | AMBIGUOUS measurements | NO_DATA test names | NO_DATA measurements | +| --- | ---: | ---: | ---: | ---: | ---: | ---: | +| 95% | 434 (60.7%) | 26,508,342 (82.9%) | 79 (11.0%) | 4,345,264 (13.6%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 98% \* | 413 (57.8%) | 24,979,594 (78.2%) | 100 (14.0%) | 5,874,012 (18.4%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 99% | 392 (54.8%) | 22,954,996 (71.8%) | 121 (16.9%) | 7,898,610 (24.7%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 100% | 275 (38.5%) | 12,745,902 (39.9%) | 238 (33.3%) | 18,107,704 (56.7%) | 202 (28.3%) | 1,108,898 (3.5%) | +| **TOTAL** | **715** | | | || | + +--- + ## Usage ```bash -bash explore_test_name.sh +python3 explore_test_name.py [options] ``` - ``: path to the input parquet file (INJECT.parquet) -- ``: minimum number of no-unit records a TEST_NAME+TEST_ID pair must have to be included +- `--min-count INT`: minimum no-unit records a TEST_NAME must have to be included in plots and injection (default: 1000) +- `--prevalence-threshold FLOAT`: min dominant-unit prevalence (%) to classify a TEST_NAME as UNAMBIGUOUS (default: 98) +- `--min-target-n INT`: minimum reference records a unit must have; tests below this are classified NO_DATA (default: 30) +- `--dump-dir PATH`: cache directory for per-test `.npy` arrays (default: `/mnt/disks/data/kanta/inject/tmp/`) +- `--inject`: run the injection engine (unambiguous + ambiguous + no_data passes) +- `--dip-threshold FLOAT`: Hartigan dip test p-value threshold for bimodality (default: 0.05) +- `--test`: small-sample mode — one test per COUNT decile (unambiguous) and top 10 by volume (ambiguous) -Each output file is skipped if it already exists. +### Caching behaviour + +`test_name_counts.tsv` and `test_name_details.tsv` are cached after the first ClickHouse query and reused on subsequent runs — delete them to force a re-query. They are always queried with a fixed baseline of `COUNT > 50`; `--min-count` is applied as a post-load filter in Python, so changing it never requires a re-query. + +`plot_name_level.tsv`, `test_names_exploration_scatter.png`, and `summary_table.md` are always recomputed from the filtered data. + +Per-test `.npy` arrays are always cached in `--dump-dir` and reused across runs. --- -## Step 1 — Injection targets (`test_name_id_counts.tsv`) +## Step 1 — Injection targets (`test_name_counts.tsv`) -Counts records where at least one source value is present (`MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_HARMONIZED IS NOT NULL`) but the unit prefix is absent (`MEASUREMENT_UNIT_PRE_FIX IS NULL`), grouped by `(TEST_NAME, TEST_ID)`. Only pairs with count > `min_count` are kept. +Counts records where at least one value is present (`MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_SOURCE IS NOT NULL`) but the unit prefix is absent (`MEASUREMENT_UNIT_PRE_FIX IS NULL`), grouped by `TEST_NAME`. Cached with `COUNT > 50`; further filtered to `--min-count` at runtime. -Columns: `TEST_NAME`, `TEST_ID`, `COUNT` +Columns: `TEST_NAME`, `COUNT` + +--- -These are the records we want to assign a unit to. +## Step 2 — Reference population (`test_name_details.tsv`) + +For every TEST_NAME in Step 1, describes the unit distribution of the records that already have both a value and a unit (`MEASUREMENT_VALUE_SOURCE IS NOT NULL AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL`). + +Columns: `TEST_NAME`, `COUNT`, `UNIT`, `PREVALENCE_DICT` + +- `COUNT`: total reference records for this TEST_NAME (across all units) +- `UNIT`: the most frequent unit +- `PREVALENCE_DICT`: top-3 units and their percentage share, e.g. `{mmol/l:98.5,umol/l:1.5}` --- -## Step 2 — Reference population (`test_name_id_details.tsv`) +## Step 3 — Plotting table, scatter plot, and classification + +Steps 1 and 2 are merged in Python to produce `plot_name_level.tsv`, a scatter plot, and a summary table. Each TEST_NAME is assigned a `CATEGORY` that drives which injection pass it enters. + +### `plot_name_level.tsv` + +One row per TEST_NAME. Columns include `COUNT`, `N_WITH_UNIT`, `top_prevalence`, `CATEGORY`, and exploratory `CATEGORY_{95,98,99,100}` columns. -For every TEST_NAME that appears in Step 1, describes the unit distribution of the records that already have both a value and a unit (`MEASUREMENT_VALUE_MERGED IS NOT NULL AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL`), grouped by `(TEST_NAME, TEST_ID)`. Note that this covers all TEST_IDs for those TEST_NAMEs, not just the ones above the threshold in Step 1. +- `COUNT`: no-unit record count +- `N_WITH_UNIT`: total reference records with any unit +- `top_prevalence`: prevalence (%) of the dominant unit; 0 if no reference records exist -Columns: `TEST_NAME`, `TEST_ID`, `COUNT`, `UNIT`, `PREVALENCE_DICT` +### Classification (`CATEGORY`) -- `COUNT`: number of reference records for this pair -- `UNIT`: the most frequent unit for this pair -- `PREVALENCE_DICT`: JSON-like string with the top-3 units and their percentage share, e.g. `{mmol/l:98.5,umol/l:1.5}` +| Category | Condition | +|---|---| +| `NO_DATA` | `N_WITH_UNIT < --min-target-n` OR `top_prevalence == 0` | +| `UNAMBIGUOUS` | `top_prevalence >= --prevalence-threshold` | +| `AMBIGUOUS` | `0 < top_prevalence < --prevalence-threshold` | -These records are the basis for deciding which unit to inject. +The injection engine only runs tests classified as UNAMBIGUOUS or AMBIGUOUS. NO_DATA tests are written directly to `no_data_results.tsv`. --- -## Step 3 — Plotting tables and scatter plots +## Step 4 — Injection engine (`--inject`) -Two intermediate tables are built in Python by merging Steps 1 and 2, then a two-panel scatter plot is saved. Before any computation, Step 2 data is restricted to the `(TEST_NAME, TEST_ID)` pairs present in Step 1, so the plots only reflect injection-target pairs. +With `--inject`, three passes are run and a coverage check validates that every TEST_NAME in `plot_name_level.tsv` appears in exactly one output file. -### `plot_name_id_level.tsv` +### Unambiguous pass → `unambiguous_results.tsv` -One row per `(TEST_NAME, TEST_ID)` from Step 1. Joined with the top unit prevalence from the reference population (Step 2) where available. +TEST_NAMEs with `CATEGORY == UNAMBIGUOUS`. The candidate distribution (no-unit records) is compared against the reference distribution for the dominant unit. -- `COUNT`: number of injection-target records -- `top_prevalence`: prevalence (%) of the dominant unit in the reference population for this pair; 0 if no reference records exist -- `has_unit_data`: whether any reference records exist for this pair +One row per TEST_NAME. Columns: `TEST_NAME`, `UNIT`, `PREVALENCE_DICT`, `N_CANDIDATE`, `N_TARGET`, `CAND_DECILES`, `TARG_DECILES`, `KS_STAT`, `KS_MLOGP`, `KS_PASS`, `T_STAT`, `T_MLOGP`, `T_PASS`, `MAD_DIST`, `MAD_THRESHOLD`, `MAD_PASS`, `OUTCOME`, `NOTES`. -### `plot_name_level.tsv` +### Ambiguous pass → `ambiguous_results.tsv` + +TEST_NAMEs with `CATEGORY == AMBIGUOUS`. Only units with prevalence > 1% and at least `--min-target-n` reference records are considered. + +Pipeline per TEST_NAME: + +1. **Pre-check**: run the full (unsplit) candidate distribution against each qualifying unit. If any unit passes, record those results and skip bimodality entirely. +2. **Bimodality check** (only if pre-check fails): test the candidate distribution for bimodality (see below). If bimodal, split into low/high sub-distributions and re-run the engine on each sub-distribution × unit. + +One row per `(TEST_NAME, SUB_DIST)` — the best unit only. Best unit selection: PASS > FAIL > SKIP, then highest `UNIT_PREVALENCE` as tiebreaker — we prefer the dominant clinical unit when two units both pass. + +Columns: `TEST_NAME`, `BIMODAL_STATUS`, `BIMODAL_SEP`, `BIMODAL_BC`, `BIMODAL_DIP_P`, `SUB_DIST`, `UNIT`, `UNIT_PREVALENCE`, `PREVALENCE_DICT`, `BEST_UNIT`, `N_CANDIDATE`, `N_TARGET`, `CAND_DECILES`, `TARG_DECILES`, `KS_STAT`, `KS_MLOGP`, `KS_PASS`, `T_STAT`, `T_MLOGP`, `T_PASS`, `MAD_DIST`, `MAD_THRESHOLD`, `MAD_PASS`, `OUTCOME`, `NOTES`. + +### No-data pass → `no_data_results.tsv` + +TEST_NAMEs with `CATEGORY == NO_DATA`. No engine is run; unit is left blank. + +Columns: `TEST_NAME`, `UNIT` + +### Unified output → `injection_results.tsv` + +Merge of the unambiguous and ambiguous results with a `TYPE` column (`unambiguous` / `ambiguous`). Does not include no_data rows. + +### Coverage check + +After all three passes, a checksum validates that the union of the three output files equals the full set of TEST_NAMEs in `plot_name_level.tsv`, with no overlaps and no missing entries. + +--- + +## Injection engine pipeline + +Each comparison runs three tests in order. All three always run; the first to decide the outcome wins. + +1. **KS test** — two-sample Kolmogorov–Smirnov. PASS = stat < 0.3 AND p < 0.05. Uses a fast binned approximation (100k bins, Hodges-corrected asymptotic p) above 500k samples; exact scipy otherwise. +2. **Welch t-test** — fallback if KS fails. PASS = p ≥ 0.05 (means not significantly different). +3. **MAD test** — last resort. PASS = |median(candidate) − median(target)| ≤ 3 × MAD(target). + +Decision rule: KS PASS → PASS. KS FAIL, T PASS → PASS. Both fail → MAD decides. `NOTES` records the deciding test and how many of the three passed, e.g. `PASS_at_T_(2/3)`. + +P-values are stored as −log10(p) throughout (`KS_MLOGP`, `T_MLOGP`). + +Each comparison produces a 3-panel diagnostic plot saved to `--dump-dir`: +- **Panel 1**: ECDFs + KS distance marked in red + KS annotation +- **Panel 2**: KDE (linear scale) + dotted mean lines + t-test annotation +- **Panel 3**: KDE (log scale) + MAD band (green = PASS, salmon = FAIL) + median lines + distance arrow + +KDE/ECDF rendering downsamples to 50k points. All statistics use the full arrays. + +--- -One row per `TEST_NAME`, aggregated from `plot_name_id_level.tsv`. +## Bimodal check -- `total_count`: sum of injection-target counts across all TEST_IDs -- `top_prevalence`: COUNT-weighted mean of `top_prevalence` across TEST_IDs that have reference records (TEST_IDs with no reference records are excluded from the average) +Before the ambiguous sub-distribution pass, the candidate distribution is tested for bimodality using two statistics: -### `test_names_exploration_scatter.png` +**Hartigan's dip test** (primary gate): p-value < `--dip-threshold` (default 0.05) declares non-unimodal. -Two scatter plots (log x-axis): +**Bimodality coefficient** (BC): `(skew² + 1) / (excess_kurtosis + 3(n−1)²/((n−2)(n−3)))`. Values above ~0.555 suggest bimodality. -- **Left**: one dot per `(TEST_NAME, TEST_ID)` — x = injection-target count, y = top unit prevalence in reference population -- **Right**: one dot per `TEST_NAME` — x = total injection-target count, y = weighted top unit prevalence +Both are computed in the space (linear or log) where a 2-component GMM achieves lower BIC. The GMM separator is used to split the candidate distribution. -Points in the top-right are high-volume tests with a consistent unit in the reference population — the best candidates for automated unit injection. +| dip p | BC | Status | +|---|---|---| +| ≥ threshold | — | `unimodal` | +| < threshold | ≥ 0.555 | `bimodal` — split into low/high | +| < threshold | < 0.555 | `bimodal_cautious` — split, modes overlap | -![Scatter plot](data/test_names_exploration_scatter.png) +A diagnostic plot (`bimodal_{tag}.png`) is saved to `--dump-dir`. diff --git a/scripts/injection/data/plot_name_id_level.tsv b/scripts/injection/data/plot_name_id_level.tsv deleted file mode 100644 index 8e8ba99..0000000 --- a/scripts/injection/data/plot_name_id_level.tsv +++ /dev/null @@ -1,2763 +0,0 @@ -TEST_NAME TEST_ID COUNT top_prevalence has_unit_data -b-eryt 1341 2046474 100.0 True -b-leuk 2218 2031768 100.0 True -b-trom 2791 1835388 100.0 True -b-hkr 1358 1108179 52.67 True -p-tt-inr 4520 827663 92.6 True -b-neut 3238 560729 99.5 True -p-inr 4520 465614 100.0 True -ab-ph 1527 375883 98.69 True -b-hkr 3001358 364840 84.79 True -b-leuk 3002218 348425 100.0 True -b-eryt 3001341 339178 100.0 True -e-mch 3001558 338725 100.0 True -e-mcv 3001357 338615 100.0 True -b-trom 3002791 338540 100.0 True -b-hb 3001552 322284 100.0 True -b-eos 1330 320814 99.8 True -b-monos 3230 310738 99.57 True -b-hb 1552 306395 100.0 True -b-baso 3157 301099 99.84 True -b-ly 3223 298815 99.33 True -u-ph 1530 291005 98.78 True -b-erblast 8518 290470 100.0 True -s-ph 8523 283517 0.0 False -p-k 1999 269981 100.0 True -e-mcv 1357 247360 100.0 True -e-mch 1558 243479 99.77 True -p-inr 3004520 234554 0.0 False -p-k 3001999 229082 100.0 True -p-na 3003622 222257 100.0 True -p-na 3622 192896 100.0 True -b-hb 1001552 187110 100.0 True -b-hkr 1001358 186638 100.0 True -b-leuk 1002218 186134 100.0 True -b-eryt 1001341 185621 100.0 True -e-mcv 1001357 185288 100.0 True -b-trom 1002791 185060 100.0 True -e-mch 1001558 184982 100.0 True -e-mchc 3001557 176587 100.0 True -u-suhti 2715 174960 92.52 True -p-inr 6004520 171649 0.0 False -pt-gfreepi 645140 163298 0.0 False -p-alat 1024 161208 100.0 True -vb-ph 1531 159518 100.0 True -e-rdw 619260 158705 100.0 True -b-hba1c 6128 147505 100.0 True -fp-gluk 1468 147429 99.97 True -p-krea 1002143 145767 100.0 True -u-ph 21701 143491 0.0 False -u-leuk 2221 139384 99.76 True -u-eryt 1344 137185 99.44 True -u-lier 19006 136425 100.0 True -p-tt-inr 3004520 133612 100.0 True -u-levyep 20524 133277 100.0 True -u-pienep 20525 133093 100.0 True -pt-gfreepi 5589849 129232 100.0 True -p-krea 605262 121923 100.0 True -p-na 1003622 120981 100.0 True -p-k 1001999 120976 100.0 True -p-tsh 4831 119706 97.99 True -ph 595 118639 0.0 False -p-crp 4594 116644 100.0 True -p-krea 4600 114156 100.0 True -p-alat 1001026 111476 100.0 True -b-erybla 19978 109544 100.0 True -fp-gluk 3001468 109118 100.0 True -pt-gfreepi 13470 108305 96.59 True -pt-gfre 6354 108215 100.0 True -pt-gfreepi 6002 106731 0.0 False -e-rdw 19976 103098 100.0 True -cb-ph 1528 99671 100.0 True -p-inr 604913 90412 0.0 False -p-alat 3001024 86716 100.0 True -pt-gfreepi 6354 82046 100.0 True -fp-kol-ldl 4599 81995 100.0 True -fp-gluk 1001469 77927 100.0 True -p-tsh 1002832 76678 100.0 True -b-hkr 6001358 75405 100.0 True -b-hb 6001552 75081 100.0 True -b-eryt 6001341 75069 100.0 True -fb-leuk 6002218 75037 100.0 True -e-mch 6001558 75032 100.0 True -e-mcv 6001357 75026 100.0 True -p-alat 605242 75005 100.0 True -e-mchc 6001557 74961 100.0 True -b-tromb 6002791 74939 100.0 True -p-kol-ldl 6433 73834 100.0 True -p-t4-v 4832 71144 100.0 True -fp-kol 4515 65814 100.0 True -fp-kol-ldl 1002099 65634 100.0 True -e-rdw 20408 65406 100.0 True -fp-kol 1002095 64459 100.0 True -p-crp 1001216 63280 100.0 True -fp-trigly 1002770 61758 100.0 True -p-kol 6429 61539 100.0 True -b-hba1c 620426 60186 100.0 True -fp-kol-hdl 2002097 60152 100.0 True -hdl/kol 1000505 59638 100.0 True -p-kol-hdl 6431 59251 100.0 True -pt-gfre 645275 58891 100.0 True -p-crp 3005293 58707 100.0 True -p-trigly 4530 58273 100.0 True -u-ph 6001530 57665 0.0 False -non-hdl 10168 56603 0.0 False -fp-kol-ldl 3005319 55612 100.0 True -p-krea 2142 55491 100.0 True -p-crp 605241 55433 100.0 True -fp-kol 3004515 55271 100.0 True -fp-kol-hdl 3004516 55080 100.0 True -u-suhti 6002715 54926 0.0 False -fp-trigly 3004568 54792 100.0 True -fp-trigly 4568 54491 100.0 True -p-afos 4587 52626 100.0 True -p-krea 1604748 51450 100.0 True -b-erybla 649167 51200 100.0 True -e-rdw 649166 50665 100.0 True -p-tsh 606115 49589 100.0 True -b-la 2203 49373 100.0 True -fp-kol-hdl 4516 49231 100.0 True -p-tt-inr 601976 48880 0.0 False -s-ph 11554 48701 0.0 False -p-k 6001999 48059 100.0 True -p-na 6003622 48019 100.0 True -b-hba1c 607918 47333 100.0 True -b-neut 3003238 46036 100.0 True -fp-kol-ldl 605259 45772 100.0 True -b-la 3002203 45470 100.0 True -kol/hdlsuh 10067 44001 0.0 False -p-t4-v 606116 43479 100.0 True -b-la 1002203 42660 100.0 True -p-inr 1607047 41919 0.0 False -p-t4-v 1002836 41305 100.0 True -pt-gfreepi 21218 40596 100.0 True --h-ind 20536 39809 0.0 False -p-afos 1001046 39414 100.0 True -u-ph-o 3667 39137 0.0 False -p-tromboplastiiniaika,inr-tulostus 4520 38382 100.0 True -p-krea 3002142 37240 100.0 True -e-mchc 1557 36967 100.0 True -p-gt 4597 36019 100.0 True -s-ph 50100 34663 0.0 False -p-alat 1605001 34228 100.0 True -p-tsh 649821 32953 100.0 True -p-ferrit 4826 30887 100.0 True -u-suhti-o 0715 30337 0.0 False -p-afos 605244 30073 100.0 True -b-eos 3001330 29841 100.0 True -pt-gfreepi 11326 29761 100.0 True -u-krea 2145 29249 98.94 True -u-keto-o 3001122 29010 100.0 True -p-afos 3005282 28039 100.0 True -u-gluk-o 3001479 27975 100.0 True -kolesteroli/hdl-suhde 10067 27781 0.0 False -hdl/kol 505 27161 100.0 True -u-alb-o 3001030 26863 100.0 True -u-ph 13039 26642 0.0 False -fp-kol 605256 26455 100.0 True -fp-kol-hdl 605257 26256 100.0 True -p-gt 1001489 26228 100.0 True -fp-trigly 605258 26182 100.0 True -ab-be 10083 25881 100.0 True -u-nitr-o 3003094 25800 100.0 True -p-psa 4869 25083 100.0 True -u-ph. 21701 23871 0.0 False -u-suhti. 21702 23384 0.0 False -fp-gluk 6001468 23324 100.0 True -u-eryt-o 3001345 23075 100.0 True -b-trom 2629414 23064 100.0 True -b-ly 3003223 23009 100.0 True -b-monos 3003230 23009 100.0 True -b-baso 3003157 23009 100.0 True -l-eos(a) 3001332 23006 100.0 True -l-lymf(a) 3009235 23006 100.0 True -l-mono(a) 3000399 23006 100.0 True -l-neut(a) 3000398 23006 100.0 True -l-baso(a) 3001168 23006 100.0 True -kol/hdlsuh 10037 22867 0.0 False -fp-kol-ldl 1605024 22609 100.0 True -b-retik 2581 22598 100.0 True -b-hba1c 650105 22516 100.0 True -p-happamuusaste(ionis.ca) 595 22410 0.0 False -fp-kol 1605022 22188 100.0 True -p-alb 4586 22154 100.0 True -fs-ph 50100 22040 0.0 False -ph 1000595 21958 0.0 False -u-nitr-o 3094 21869 100.0 True -fs-folaat 1416 21758 100.0 True -u-albkre 4511 21642 100.0 True -u-ph 3667 21609 0.0 False -s-b12-tc2 1142 21574 100.0 True -pt-gfre 656400 21550 0.0 False -u-krea 3002145 21319 93.49 True -u-gluk-o 1479 21143 100.0 True -u-ph 3001530 21058 0.0 False -fp-kol-hdl 1605023 20836 100.0 True -pt-gfreepi 0232 20834 100.0 True -p-tsh 1605042 20670 100.0 True -vb-be 9074 20573 100.0 True -fp-trigly 1605041 20454 100.0 True -p-gluk 1471 20310 100.0 True -u-leuk-o 3002223 20119 100.0 True -b-leuk 1629408 19981 0.0 False -b-eryt 1629409 19962 0.0 False -e-rdw 1631804 19908 0.0 False -b-trom 1629414 19870 0.0 False -u-keto-o 1122 19716 95.16 True -ca-ion 1000597 19146 0.0 False -ca++/7.40 1000596 19140 0.0 False -p-crp 1605013 19124 100.0 True -p-t4v 1605037 18942 100.0 True -p-psa 2003642 18865 100.0 True -p-t4-v 649822 18774 100.0 True -b-neut 1003238 18307 100.0 True -u-leuk-o 2223 18164 100.0 True -ph 9018 17842 0.0 False -s-k/l-s-v 20113 17806 100.0 True -b-leuk 3629408 17552 100.0 True -u-suhteellinentiheys 2715 17548 100.0 True -b-eryt 3629409 17499 100.0 True -p-inr 607047 17490 0.0 False -p-gt 3005292 17319 100.0 True -p-krea 645274 17118 100.0 True -u-eryt-o 1345 17072 100.0 True -s-apob/apoa1-suhde 0623 16804 0.0 False -p-probnp 4760 16554 100.0 True -u-krea 10458 16442 100.0 True -p-krea 605305 15848 100.0 True -u-alb 3001029 15705 100.0 True -ab-be 50030 15686 99.94 True -u-suhti 21702 15672 0.0 False -e-rdw 3635986 15504 0.0 False -u-krea 1010458 15417 0.0 False -p-inr 600493 15107 0.0 False --l-ind 20537 15069 0.0 False -s-tsh 3002832 14964 100.0 True -p-k 101999 14906 100.0 True -b-eryt 2629409 14818 100.0 True -p-na 103622 14701 100.0 True -p-tfr 4720 14678 100.0 True -p-inr-hy 7355261 14671 0.0 False -u-alb-o 1030 14540 100.0 True -p-gt 605248 14228 100.0 True -p-bil 4592 13960 100.0 True -s-ph 3008523 13864 0.0 False -e-mch 2629412 13628 100.0 True -e-mchc 2629413 13626 100.0 True -p-krea 604429 13625 100.0 True -e-mcv 2629411 13624 100.0 True -p-psa 606117 13586 100.0 True -b-be 105 13570 100.0 True -b-ghb-a1c 1001560 13570 100.0 True -e-rdw 606834 13559 0.0 False -p-krea 2605305 13533 100.0 True -u-suhtih 0352 13353 0.0 False -u-alb 1029 13089 100.0 True -b-ghb-a1c 3001560 12943 100.0 True -b-hba1c 620261 12911 100.0 True -b-neut 6003238 12889 100.0 True -p-d-25 1001220 12837 0.0 False -u-suhti-o 600748 12537 0.0 False -u-ph 600817 12513 0.0 False -s-b12-vit 3001137 12395 100.0 True -cb-be 151 12224 100.0 True -fe-folaat 1001414 12140 100.0 True -p-inr 2607047 11963 0.0 False -p-ferrit 606675 11905 0.0 False -b-la 6002203 11845 100.0 True -p-probnp 611261 11741 0.0 False -u-suhti 0730 11634 0.0 False -s-b12-tc2 616408 11610 0.0 False -hdl/kol. 14578 11548 100.0 True -p-alb 605243 11507 100.0 True -oma-gluk 256 11472 0.0 False -b-lymfos 3223 11425 95.72 True -ntkmom 20758 11282 0.0 False -pappakmom 20757 11279 0.0 False -l-lymfos 191 11276 100.0 True -l-lymf(a) 9235 11241 100.0 True -b-eos 1001330 11218 100.0 True -hcgbvkmom 20756 11204 0.0 False -p-k 2101999 11202 100.0 True -l-eosin 598 11163 100.0 True -l-monos 197 11118 100.0 True -baso 1000599 11034 100.0 True -baso 1003157 11033 100.0 True -b-eosin 1330 11027 100.0 True -eos 1000598 11022 100.0 True -b-basof 3157 11017 100.0 True -lymf 1003223 11005 100.0 True -lymf 1000191 11002 100.0 True -mono 1000197 10995 100.0 True -mono 1003230 10979 100.0 True -b-neutr 3238 10973 97.48 True -neut 1000612 10966 100.0 True -p-bil 1001185 10881 100.0 True -p-uraat 4533 10864 98.62 True -b-erblast 602870 10860 100.0 True -b-hb-a1c 1605248 10849 100.0 True -l-basof 599 10834 100.0 True -l-neutr 612 10825 100.0 True -vb-ph 8270 10807 0.0 False -b-hba1c 7037277 10779 100.0 True -b-erytrosyytit,tilavuusosuus 1358 10629 77.48 True -fs-trfesat 10100 10586 100.0 True -p-ca 605254 10486 100.0 True -p-psa-v 4900 10483 100.0 True -l-mono(a) 399 10383 100.0 True -p-inr 104520 10380 0.0 False -p-psa 615989 10243 100.0 True -p-ca-albk 613776 10182 100.0 True -u-ph-huu 8869 10033 0.0 False -l-eos(a) 1332 10031 100.0 True -u-ominp-h 20567 10003 0.0 False -s-ca(akt) 3005097 9965 100.0 True -s-ca(7.4) 3005099 9951 100.0 True -p-afos 1605000 9948 100.0 True -p-antifxa 3828 9909 55.18 True -s-d-25 1220 9900 100.0 True -s-ph(akt) 3005098 9886 100.0 True --i-ind 20538 9849 0.0 False -p-ferrit 1001395 9800 100.0 True -p-ca 4598 9683 100.0 True -u-albkre 2010455 9660 100.0 True -p-na 2103622 9653 100.0 True -u-alb 1010457 9615 0.0 False -pt-gfreepi 2917425 9579 0.0 False -l-neut(a) 398 9540 100.0 True -cp-gluk-hy 0589 9537 100.0 True -p-gluk 3001471 9483 100.0 True -p-tromboplastiiniaika,inr,tt 4520 9455 0.0 False -oma-crp 462 9415 100.0 True -p-inr 601850 9385 0.0 False -non-hdl 10138 9376 0.0 False -u-alb 10457 9359 100.0 True -p-bil 3005299 9162 100.0 True -u-prot-o 2529 9022 0.0 False -b-hba1c 7036281 8950 100.0 True -u-ph 0375 8890 0.0 False -l-baso(a) 1168 8791 100.0 True -p-alat 604418 8789 100.0 True -pt-gfreepi 1662604 8649 0.0 False -u-suhtih 0373 8539 0.0 False -p-tfr 1001949 8538 100.0 True -l-lymf 46 8470 100.0 True -cb-be 10191 8455 100.0 True -l-eos 690 8445 100.0 True -b-neutr 1003238 8441 0.0 False -b-basof 1003157 8427 0.0 False -b-neut 689 8421 100.0 True -b-eosin 1001330 8409 0.0 False -b-lymfos 1003223 8392 0.0 False -b-monos 1003230 8357 0.0 False -p-tnt 4532 8290 99.98 True -l-basof 1000599 8256 0.0 False -b-hkr 0639 8250 0.0 False -l-eosin 1000598 8245 0.0 False -l-lymfos 1000191 8204 0.0 False -l-monos 1000197 8170 0.0 False -l-neutr 1000612 8132 0.0 False -p-tromboplastiiniaika,inr-tulos 4520 8123 100.0 True -fp-gluk 2101468 8115 100.0 True -p-tsh 604895 8112 100.0 True -b-lymf 43 8077 100.0 True -p-psa-v 1004254 8055 100.0 True -s-t4-v 3002836 8052 100.0 True -fp-kol-ldl 604453 8045 100.0 True -ca++/7.40 596 8031 100.0 True -p-asat 4591 7931 100.0 True -p-amyl 4589 7910 100.0 True -fs-ph 0683 7870 0.0 False -oma-crp 5567927 7821 0.0 False -fp-transf 4567 7798 100.0 True -s-b12-vit 1137 7786 100.0 True -b-monos 42 7780 100.0 True -psa-v/psa 1010792 7743 0.0 False -b-eos 39 7740 100.0 True -fp-kol 604452 7719 100.0 True -l-monos 693 7709 100.0 True -l-baso 692 7698 100.0 True -fp-trigly 604454 7693 100.0 True -fp-kol-hdl 604451 7692 100.0 True -u-albkre 605850 7676 0.0 False -fp-kol-ldl 2605269 7672 100.0 True -ca-ion 597 7662 100.0 True -b-pvk+t 2474 7644 0.0 False -p-tnt 607465 7620 100.0 True -b-baso 40 7617 100.0 True -fs-ca++/7.40 596 7616 0.0 False -fs-ca-ion 597 7610 100.0 True -l-neut 688 7435 100.0 True -inr-vieri 603043 7407 0.0 False -p-psa-v 631060 7364 100.0 True -s-tsh 2832 7316 71.35 True -p-inr 606000 7295 0.0 False -b-neut 1103238 7241 100.0 True -crp 0113 7205 0.0 False -s-iglck-v 4966 7204 100.0 True -p-d-25 6401 7190 100.0 True -b-neut 2103238 7172 0.0 False -pt-gfreepi 4605 7034 0.0 False -b-trom 3629414 7028 100.0 True -s-ttgaba 1885 7011 91.32 True -s-iglcl-v 4950 7000 100.0 True -crp,tk 602087 6993 0.0 False -raskauksienmäärä,g Ras001 6870 0.0 False -b-erytroblastit 50610 6765 100.0 True -l-neut(a) 3629125 6740 0.0 False -l-lymf(a) 3629126 6737 0.0 False -l-mono(a) 3629127 6736 0.0 False -p-ferrit 617876 6735 100.0 True -l-eos(a) 3629128 6734 0.0 False -l-baso(a) 3629129 6728 0.0 False -p-uraat 1002884 6716 100.0 True -b-monos 2103230 6701 0.0 False -b-baso 2103157 6667 0.0 False -s-b12-tc2 617336 6642 100.0 True -p-alb 3005318 6638 100.0 True -cb-be 5400 6637 100.0 True -l-neut(a) 2629125 6627 0.0 False -p-gluk,tk 602079 6621 0.0 False -l-lymf(a) 2629126 6620 0.0 False -p-tnt 615402 6615 0.0 False -l-mono(a) 2629127 6615 0.0 False -l-eos(a) 2629128 6606 0.0 False -l-baso(a) 2629129 6602 0.0 False -b-monos 1103230 6564 0.0 False -fp-gluk 101468 6555 100.0 True -p-tt-inr 3576 6546 0.0 False -b-baso 1103157 6522 0.0 False -p-afos 1605265 6512 0.0 False -vb-be 5386 6466 100.0 True -p-alb 1001028 6456 100.0 True -pt-gfreepi 3653122 6405 0.0 False -p-d-25 1220 6393 100.0 True -s-k/l-s-v 9319 6363 100.0 True -s-ca-ion 9010 6361 100.0 True -p-bil 605249 6352 100.0 True -p-amyl 1001078 6319 100.0 True -snabb-inr 0743 6267 0.0 False -p-crp 604422 6213 100.0 True -p-mg 4601 6178 100.0 True -u-ph 100325 6168 0.0 False -b-hba1c 606590 6161 100.0 True -b-hb-a1c 604449 6157 100.0 True -fp-kol-ldl 605269 6150 0.0 False -s-ca(7.4) 5099 6137 100.0 True -fe-folaat 4001414 6129 100.0 True -cb-pco2 1622 6119 100.0 True -p-psa 1605032 6073 100.0 True -p-afos 2605265 6055 0.0 False -p-amyl 3005208 6052 100.0 True -non-hdl(paasto) 10138 6004 0.0 False -kolesteroli/hdl-suhde 10037 6002 0.0 False -s-ph(akt) 5098 5988 100.0 True -s-ca-ion 597 5881 0.0 False -p-tsh 1663381 5873 0.0 False -synnytystenmäärä,p Ras002 5868 0.0 False -s-ca++/7.40 596 5861 0.0 False -p-inr 4004520 5803 0.0 False -u-suhtih 100323 5732 0.0 False -fp-fe 4529 5720 100.0 True -p-d-25 632020 5675 100.0 True -pt-gfreepi 622040 5635 0.0 False -oma-p-crp 7037327 5623 100.0 True -b-leukosyytit 2218 5619 100.0 True -cb-tt-inrp 602165 5576 0.0 False -p-inr-hy 50285 5557 0.0 False -b-ly 1605097 5514 100.0 True -p-inr-vt 10757 5501 100.0 True -p-tsh 3657914 5475 0.0 False -fe-folaat 3014140 5457 100.0 True -p-uraat 605270 5451 100.0 True -p-inr 602670 5440 0.0 False -u-ph-o 13039 5438 0.0 False -b-ghb-a1c 1560 5330 100.0 True -s-ph 45093 5321 0.0 False -u-happamuusaste 1530 5304 0.0 False -p-tfr 605894 5294 0.0 False -fp-kol-hdl 2605268 5285 100.0 True -fp-kol-hdl 605268 5275 0.0 False -fp-trigly 2605285 5259 100.0 True -vb-be 50032 5232 100.0 True -14272 14272 5212 0.0 False -fp-trigly 605285 5194 0.0 False -b-erblast 3629130 5193 0.0 False -u-osmoest 606697 5188 87.05 True -nu-albkrea 618158 5154 100.0 True -p-uraat 3004533 5133 100.0 True -b-erblast 2629130 5130 0.0 False -p-tfr 617378 5088 100.0 True -p-tt-inr 1605218 5071 0.0 False -s-ttgaba 3001885 5066 100.0 True -vp-ph 1531 5059 0.0 False -p-asat 605247 5051 100.0 True -s-ca-iona 8524 5048 100.0 True -b-hba1c,tk 606670 5039 0.0 False -cb-hco3-st 154 5012 100.0 True -p-fidd 4113 5011 100.0 True -p-crp 605304 5001 100.0 True -s-fsh 1422 4996 51.01 True --trfesat 4606 4851 100.0 True -p-tsh 622558 4847 0.0 False -p-psa-suh 4868 4811 99.68 True -s-ca-iona 3008524 4794 100.0 True -s-ca-ion 4009010 4788 100.0 True -s-ca-ion 2019 4747 100.0 True -e-retik 2582 4736 100.0 True -u-osmole 626820 4685 100.0 True -b-hba1c,t 606670 4683 0.0 False -u-ph 0067 4678 0.0 False -b-ghb-a1c 600221 4645 0.0 False -u-lier 2630671 4632 0.0 False -fp-pi 1431 4623 100.0 True -psa-v/psa 10792 4619 100.0 True -u-eryt 1101344 4619 0.0 False -u-leuk 1102221 4598 100.0 True -p-urea 4534 4590 100.0 True -mononukleaariset Mon1223 4588 0.0 False -neutrofiilit Neu1222 4535 0.0 False -s-cdt 4101 4511 100.0 True -b-erybla 644813 4508 100.0 True -pt-gfreepi 621337 4507 100.0 True -p-t4-v 604894 4480 100.0 True -p-gt 604424 4455 100.0 True -b-hba1c 3636046 4443 0.0 False -e-rdw 644812 4417 100.0 True -p-crp-o 7035803 4405 100.0 True -zb-ph 1532 4383 0.0 False -p-b12-vit 1001137 4382 100.0 True -p-psa-suh 606119 4330 100.0 True -p-psa-v 606118 4329 100.0 True -u-ominaispaino 18811 4321 0.0 False -b-hba1c 607475 4297 100.0 True -p-tt 3001731 4288 100.0 True -p-ph 50099 4275 0.0 False -s-ccpab 4744 4273 82.87 True -cb-inrc-c 0113 4271 0.0 False -b-eos 6001330 4262 100.0 True -u-ph 0325 4255 0.0 False -pappakmom 620902 4251 0.0 False -ntkmom 620900 4251 0.0 False -hcgbvkmom 620904 4251 0.0 False -u-suhtih 0323 4246 0.0 False -p-pi 4595 4227 100.0 True -ab-be 9224 4217 100.0 True -p-t4-v 1663382 4194 0.0 False -vb-be 9220 4185 100.0 True -pt-gfre 643362 4171 100.0 True -fp-ca 1002013 4162 100.0 True -inr-pika 868 4158 0.0 False -b-ghb-a1c,tk 600221 4155 0.0 False -f-calpro 4803 4155 100.0 True -u-gluk-0 1479 4154 0.0 False -pituus(cm) Pit484 4130 0.0 False -p-psa-suh 1605034 4125 100.0 True -cb-tt-inrpika 602165 4095 0.0 False -b-monos 1605103 4068 100.0 True -b-baso 1605100 4068 100.0 True -pt-gfreepi 3960575 4060 0.0 False -s-k/l-s-v 11927 4016 0.0 False -p-asat 3005281 4016 100.0 True -pt-gfreepi 622237 4011 0.0 False -pt-gfreepi 635156 3935 0.0 False -b-ghba1cp 0591 3927 100.0 True -b-erybla 7716 3907 0.0 False -p-ca-albk 8293 3905 100.0 True -cd4/cd8 10825 3896 0.0 False -p-ck 4517 3884 100.0 True -p-bil 1605005 3880 100.0 True -p-rf 8849 3828 100.0 True -fp-pth 4560 3819 79.63 True -e-retik 3002582 3806 100.0 True -p-iga 5577788 3796 0.0 False -ph 1530 3794 0.0 False -fs-kol 2095 3794 100.0 True -fs-kol-ldl 2099 3772 100.0 True -u-ph 0105 3763 0.0 False -u-leuk 3002221 3757 100.0 True -cp-glukoosi,ihopistosn,vieritestihoitoyksikössä 0589 3716 0.0 False -p-probnp 603605 3695 0.0 False -u-osmest 3000292 3639 100.0 True -p-ck 1002134 3634 100.0 True -b-neut 14272 3631 100.0 True -b-hba1c 1632264 3626 0.0 False -b-erytroblastit 19978 3614 100.0 True -eosinofiil. 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-sy-leuk 3080 3253 99.73 True -p-tnt 1605039 3186 100.0 True -fp-krea 603104 3173 0.0 False -u-epit 615359 3164 100.0 True -u-lier 615358 3161 100.0 True -p-gt 1605018 3159 100.0 True -p-t4-v 622559 3156 0.0 False -b-neut 103238 3150 99.97 True -p-iga 4827 3149 100.0 True -u-leuk 615357 3136 100.0 True -oma-gluk 4601160 3124 0.0 False -u-eryt 615356 3120 100.0 True -u-ph-o 103667 3097 0.0 False -u-lier 3630671 3096 0.0 False -u-eryt 2101344 3083 0.0 False -p-ck 1605010 3082 100.0 True -cb-ph 1001528 3067 0.0 False -p-tnt 603603 3065 0.0 False -u-leuk 2102221 3059 0.0 False -p-ck-mbm 1004236 3054 100.0 True -li-leuk 2219 3052 100.0 True -b-ly 1103223 3048 100.0 True -li-eryt 1342 3048 100.0 True -u-kemseul,omin.p 103268_2 3045 0.0 False -p-ph 8522 3036 0.0 False -fs-trigly 2770 3024 100.0 True -p-amylp 605246 3021 100.0 True -vb-be 10085 3014 100.0 True -b-neut 5597073 3007 0.0 False -fs-kol-hdl 2097 3005 100.0 True -fp-pth 1002457 2996 100.0 True -p-psa-suh 631061 2982 100.0 True -fb-leuk 2218 2978 100.0 True -s-k/l-s-v 50207 2977 0.0 False -u-epit 607576 2974 0.0 False -p-t4-v 630118 2973 0.0 False -u-eryt 607597 2964 0.0 False -b-ph 1531 2963 0.0 False -p-alb 1605002 2961 100.0 True -s-testo 2735 2947 99.97 True -p-inr-pika 606328 2945 0.0 False -b-hba1c 623599 2943 0.0 False -u-lier 607577 2943 0.0 False -u-eryt 11344 2934 100.0 True -crp(päiv.hoitaja) akiea0002 2927 100.0 True -p-uraat 1605043 2924 100.0 True -pt-gfre 10055629 2920 100.0 True -fs-ca-ion 1000597 2886 0.0 False -fs-ca++/7.40 1000596 2879 0.0 False -p-crp-vt 10759 2870 100.0 True -b-hkr 4001358 2868 100.0 True -u-suhtih 2715 2861 0.0 False -cb-pco2 1001622 2859 100.0 True -u-epit 980 2847 100.0 True -cb-be 1000151 2836 100.0 True -p-inr-pi 606328 2836 0.0 False -s-li 3002260 2834 100.0 True -e-retik 1002582 2828 100.0 True -b-eryt 4001341 2825 100.0 True -e-mcv 4001357 2825 100.0 True -b-hb 4001552 2825 100.0 True -b-leuk 4002218 2825 100.0 True -e-rdw 615255 2825 100.0 True -e-mch 4001558 2825 100.0 True -e-mchc 4001557 2824 100.0 True -b-trom 4002791 2821 100.0 True -u-lier 981 2816 100.0 True -cb-hco3-st 1000154 2814 100.0 True -cb-crp 101217 2782 0.0 False -s-tshrab 4965 2775 84.77 True -f-calpro 613422 2753 0.0 False -p-mg 605264 2747 100.0 True -fs-folaat 1001416 2731 100.0 True -u-suhti-o 715 2722 0.0 False -b-hba1c 606591 2696 100.0 True -fp-gluk 603107 2696 100.0 True -p-ck-mbm 1605011 2673 100.0 True -erytroblastit 8518 2654 100.0 True -p-krea 1605262 2652 100.0 True -pt-kt/v1 15024 2648 0.0 False -fp-krea 2142 2634 100.0 True -s-ph 1606713 2634 0.0 False -p-t3-v 1002775 2622 0.0 False -p-ck 605261 2609 100.0 True -s-apob/a1 02249 2604 0.0 False -u-albkre 604448 2599 100.0 True -b-baso 103157 2598 100.0 True -p-uraat 1605306 2597 0.0 False -p-cmvnh 4777 2592 82.64 True -pt-gfre 10066523 2588 100.0 True -fp-kol-ind 633151 2587 0.0 False -s-klotsa 609927 2569 100.0 True -s-ph 2606713 2552 0.0 False -b-monos 103230 2542 100.0 True -s-norklot 609913 2537 100.0 True -l-neut(a) 1629125 2534 0.0 False -l-lymf(a) 1629126 2531 0.0 False -l-eos(a) 1629128 2529 0.0 False -l-mono(a) 1629127 2529 0.0 False -l-baso(a) 1629129 2527 0.0 False -u-veri-o 2947 2498 0.0 False -u-krea 2606670 2492 0.0 False -lieriöt 40527 2485 100.0 True -fp-kol-ind 6518 2479 0.0 False -pt-gfre 2928608 2478 0.0 False -s-ph 7368425 2475 0.0 False -ab-emäsylimäärä 10083 2472 100.0 True -b-la 102203 2468 100.0 True -p-k 4001999 2440 100.0 True -u-ph-hy 0368 2439 0.0 False -seeruminhappamuusaste 8523 2429 0.0 False -fp-ca 4514 2426 100.0 True -p-gluk 6001471 2422 100.0 True -p-bnp 4709 2420 99.98 True -b-la 2102203 2414 100.0 True -fp-pi 1001432 2410 100.0 True -b-crp-vt 6592 2408 100.0 True -vb-pco2 1623 2408 100.0 True -li-igg-ind 3450 2406 100.0 True -p-afos 604419 2405 100.0 True -vb-po2 1537 2405 100.0 True -p-d-25 607216 2394 0.0 False -p-na 4003622 2385 100.0 True -l-eos 1332 2379 100.0 True -s-igg4 4228 2367 100.0 True -b-hba1c 604640 2366 100.0 True -ly-cd4/cd8 9270 2357 0.0 False -zb-be 11453 2350 0.0 False -b-inr-pik 8120 2340 100.0 True -u-albkrea 4511 2339 100.0 True -s-psa 3642 2336 100.0 True -pt-gfre 626572 2320 100.0 True -p-ca-iona 3000335 2305 100.0 True -s-k/l-s-v 10747 2302 0.0 False -p-pi 605252 2296 100.0 True -p-ca 7368221 2282 100.0 True -b-eos 632777 2278 0.0 False -b-baso 632778 2278 0.0 False -b-ly 632780 2278 0.0 False -l-baso 632773 2278 0.0 False -b-neut 632776 2278 0.0 False -l-neut 632771 2278 0.0 False -l-eos 632772 2278 0.0 False -b-mono 632779 2278 0.0 False -l-ly 632775 2278 0.0 False -l-mono 632774 2278 0.0 False -p-ca-ion. 3013900 2258 100.0 True -s-valpr 3003681 2253 100.0 True -p-t4-v 3657915 2253 0.0 False -s-prl 3002507 2247 100.0 True -ab-pco2 3001621 2242 100.0 True -ab-be 3009224 2242 100.0 True -ab-hco3-st 3009314 2242 100.0 True -p-b12-vit 608792 2241 100.0 True -ab-po2 3001535 2237 100.0 True -p-igg 4828 2235 100.0 True -p-alat 1605242 2229 100.0 True -f-calpro 606035 2216 0.0 False -s-mkomp-1 9982 2215 100.0 True -e-rdw 2644100 2199 100.0 True -fp-kol-ldl 2629664 2194 0.0 False -vp-happamuusaste 1531 2193 0.0 False -crp-pika 9011 2188 100.0 True -vb-ph 3001531 2182 0.0 False -oma-inr 617344 2181 0.0 False -u-osmole 2900806 2178 100.0 True -fp-kol-hdl 1002097 2171 100.0 True -hdl/kol 602250 2171 100.0 True -pt-gfre 3663121 2170 0.0 False -p-tsh 2917625 2158 100.0 True -p-probnp 609847 2150 100.0 True -b-hba1cvt 11246 2149 82.01 True -p-alat 101024 2137 100.0 True -p-krea 628929 2137 100.0 True -pt-gfre 628930 2130 100.0 True -f-calpro 616027 2127 100.0 True -p-gluk 1001473 2123 0.0 False -u-lieriö 9244 2104 100.0 True -p-tsh 613256 2093 100.0 True -pt-gfreepi 626168 2078 100.0 True -u-lieriöt 40527 2067 100.0 True -p-tnt 602562 2054 100.0 True -pf-leuk 2220 2053 99.08 True -u-osmest 292 2048 100.0 True -p-inr-vt 621377 2039 0.0 False -p-ca-iona 335 2036 100.0 True -fp-gluk 4001468 2033 100.0 True -p-fidd 621300 2032 100.0 True -s-mypnabm 4151 2032 0.0 False -b-erblast 1629130 2028 0.0 False -pf-eryt 1343 2022 99.97 True -u-alb 6001029 2008 100.0 True -p-kysc 4507 1998 100.0 True -s-ca(akt) 5097 1998 100.0 True -p-psa 604836 1997 100.0 True -s-cdt 3004101 1997 100.0 True -vb-happamuusaste 1531 1984 0.0 False -s-trigly 6427 1983 100.0 True -p-tsh 2664021 1983 0.0 False -u-epit 3630670 1982 0.0 False -s-kol-hdl 6430 1972 100.0 True -p-tsh 603956 1972 100.0 True -p-crp-o 613895 1963 100.0 True -s-k 2001 1963 100.0 True -s-hcgbv/d 620903 1962 100.0 True -s-pappa 620901 1961 100.0 True -l-mono 0905 1954 100.0 True -pika-inr 607101 1953 0.0 False -u-ph akiosa0004 1943 0.0 False -l-eos 0902 1930 100.0 True -p-ca-ion. 13900 1918 100.0 True -u-alb 0129 1917 100.0 True -s-d-25 649206 1915 0.0 False -p-t3-v 6362 1914 100.0 True -pt-gfreepi 645275 1913 0.0 False -p-t4-v 613257 1907 100.0 True -s-igg1 4225 1897 100.0 True -s-prot 2516 1897 100.0 True -s-igg2 4226 1893 100.0 True -p-crp 7010044 1892 100.0 True -crp,tk 70001 1890 0.0 False -p-alat 7010034 1888 100.0 True -p-inr 603120 1885 0.0 False -s-dnanab. 12610 1881 100.0 True -b-tacro 4360 1877 100.0 True -s-cdt 617036 1876 100.0 True -vb-emäsylimäärä 50032 1871 100.0 True -s-b12-tc2 1101142 1870 100.0 True -u-epit 10096 1855 100.0 True -s-igg3 4227 1853 100.0 True -s-iga 3001666 1832 100.0 True -e-rdw 3631804 1829 0.0 False -u-ph-huu 606264 1823 0.0 False -s-testo 3002735 1823 100.0 True -fp-kol-ldl 1605259 1823 100.0 True -l-neutr 0901 1798 100.0 True -s-pr3ab 4160 1796 76.4 True -s-kol-ldl 6432 1796 100.0 True -nu-albkrea 23572 1796 100.0 True -pappakmom 5568787 1793 0.0 False -ntkmom 5568790 1792 0.0 False -p-tt-inr 3575 1792 0.0 False -hcgbvkmom 5568788 1792 0.0 False -u-osmol 2444 1792 100.0 True -l-lymf 0907 1790 100.0 True -s-testo 1002735 1790 100.0 True -b-hba1c 603372 1782 100.0 True -u-ominp-h 618136 1775 0.0 False -s-rf 3003550 1770 100.0 True -p-t4-v 603957 1753 100.0 True -p-ld 1002194 1741 100.0 True -cp-gluk-po 8716 1736 0.0 False --nt 617897 1730 100.0 True -s-crp-o 1217 1730 100.0 True -fp-fe 3005323 1727 100.0 True -p-t4-v 2664022 1726 0.0 False -p-cea 6363 1719 100.0 True -cp-gluk 0350 1718 100.0 True -sao2 600605 1715 0.0 False -p-inr-pik 603692 1713 0.0 False -e-erytrosyytit,kokojakauma 11086 1709 100.0 True -vb-ph 0531 1708 0.0 False -u-ph-0 3367 1707 0.0 False -pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava 13470 1706 100.0 True -p-uraat 2605306 1704 0.0 False -l-baso 1168 1702 99.99 True -p-fidd 1004113 1700 100.0 True -cb-phpika 14234 1696 0.0 False -fp-laktaat 3002184 1693 100.0 True -p-d-25 2101220 1682 0.0 False -crp-pika 602611 1680 0.0 False -s-immunoglobuliini,kevyetketjut,vapaat,kappa-lambda-suhde 11927 1672 0.0 False -fp-transf 3004567 1666 100.0 True -l-lymf 9235 1666 100.0 True -u-tutk-1-oma,ph 1605222_4 1647 0.0 False -b-inr-pik 1630673 1646 0.0 False -pt-ekg-12 6001270 1646 0.0 False -fp-kol 7010048 1643 100.0 True -u-osmole 20479 1642 100.0 True -b-be 0105 1641 100.0 True -u-tutk-1-,ph 1605222_4 1640 0.0 False -p-amylp 4590 1639 100.0 True -fp-kol-ldl 7010050 1638 100.0 True -u-suhtih 0715 1630 100.0 True -s-enaab 3022 1628 100.0 True -p-inr 601708 1624 0.0 False -fp-kol 1605256 1618 100.0 True -p-crp-o 1217 1613 100.0 True -pt-gfreepi 2663222 1612 0.0 False -l-eos 604160 1608 100.0 True -b-monos 604163 1608 100.0 True -l-ly 607191 1608 100.0 True -b-baso 604164 1608 100.0 True -b-neut 607193 1608 100.0 True -l-monos 607192 1608 100.0 True -b-ly 604162 1608 100.0 True -b-eos 607194 1608 100.0 True -l-baso 604161 1607 100.0 True -l-neut 607190 1607 100.0 True -s-ca-ion 622231 1606 100.0 True -cb-be 4923 1595 100.0 True -fp-fe 1002566 1595 100.0 True -s-digoks 1256 1584 96.73 True -p-psa 2628984 1582 100.0 True -fe-folaat 1414 1571 100.0 True -b-retik 3025810 1562 100.0 True -p-glukpoc 9439 1562 100.0 True -p-psa 1628984 1561 0.0 False -s-pappa 4549 1550 100.0 True -p-ld 3004526 1550 100.0 True -s-mypnabg 4150 1535 99.91 True -p-luakptt 4426 1534 100.0 True -u-albkre 603497 1526 100.0 True -p-psa 3628984 1516 100.0 True -b-hba1c 616356 1512 100.0 True -u-kemseul,u-ph 101881_5 1507 0.0 False -b-inrpika 94520 1503 100.0 True -p-crp 1605304 1496 100.0 True -fp-ca 3004514 1494 100.0 True -s-cdt 1004101 1489 0.0 False -b-crp-o 9343 1485 0.0 False -s-hcgbv/d 20754 1479 100.0 True -pt-gfreepi 41320 1474 0.0 False -p-ferrit 2630464 1473 100.0 True -fp-transf 1002756 1471 100.0 True -l-mon 399 1466 100.0 True -u-epipien 50203 1465 100.0 True -paastoseeruminph 50100 1457 0.0 False -u-suhti 617971 1456 0.0 False -b-hba1c,tk 70003 1453 0.0 False --nt 20248 1448 100.0 True -s-tsh 102832 1446 96.13 True -b-hba1c 10017548 1444 100.0 True -u-leuk-bv 637391 1442 100.0 True -hba1c-pika 870 1437 0.0 False -s-prot 1002516 1436 100.0 True -p-fidd 3004113 1425 100.0 True -s-prealb 1002494 1420 100.0 True -fp-trigly 1605258 1418 100.0 True -s-igg-sum 9115 1410 100.0 True -fp-kol-hdl 1605257 1402 100.0 True -p-ca-albk 7368224 1400 100.0 True -p-mg 3005285 1400 100.0 True -p-psa-v 1635178 1396 0.0 False -s-van 3277 1396 100.0 True -s-tfr 6001949 1394 100.0 True -happamuusaste,virtsasta 13039 1393 0.0 False -tffesat 4606 1386 100.0 True -e-rdw 630871 1382 100.0 True -u-tutk-1-oma,sg 1605222_3 1372 0.0 False -u-kemseul,u-suhti 101881_3 1362 0.0 False -gt-cdt-ind 50526 1349 0.0 False -cb-ph 0528 1349 0.0 False -s-chpnabm 4204 1348 88.46 True -p-korsol 1002129 1346 100.0 True -pt-gfre 633141 1345 0.0 False -hemolyysi-indeksi 20536 1344 0.0 False -oma-p-gluk 4601160 1343 0.0 False -fp-kol-hdl 7010049 1342 100.0 True -fp-glukoosi 1468 1341 99.93 True -fp-trigly 7010320 1339 100.0 True -s-ccpab 603704 1339 0.0 False -s-cea 3002034 1339 100.0 True -tffesat 2010359 1334 0.0 False -oma-u-tutk,u-ph 4601161_1 1333 0.0 False -u-tutk-1-,sg 1605222_3 1332 0.0 False -b-leuk 2629408 1325 100.0 True -u-osmole 0574 1324 0.0 False -fp-urea 1002888 1322 100.0 True -p-bil-kj 4593 1319 100.0 True -ab-be 5382 1317 100.0 True -p-mg 1002303 1315 100.0 True -e-rdw 7370521 1313 100.0 True -b-hba1c 615779 1313 100.0 True -b-crp 0801 1312 0.0 False -p-ld 4526 1311 100.0 True -b-b-cd19 8374 1310 100.0 True -s-b12-tc2 2101142 1310 0.0 False -tromboplastiiniaika,inr-tulostus,plasmasta 4520 1310 100.0 True -b-ly/abs 9060 1306 100.0 True -s-korsol 3002129 1306 100.0 True -b-ba/abs 9062 1306 100.0 True -u-krea 1002145 1303 100.0 True -pt-gfre 3969737 1302 0.0 False -u-epilevy 50200 1298 100.0 True -p-tsh 7010179 1297 100.0 True -eos 598 1295 100.0 True -emäsylimäärä,laskimoveri 5386 1291 0.0 False -p-asat 604421 1290 100.0 True -u-leuk 102221 1286 100.0 True -u-krea 606670 1286 0.0 False -b-hba1c 2897005 1285 100.0 True -u-a1miglo 15132 1280 0.0 False -u-eryt 101344 1277 100.0 True -cb-be 10084 1275 100.0 True -l-neut 620537 1264 0.0 False -b-crp-o 1217 1252 100.0 True -e-rdw 643282 1251 100.0 True -b-hba1c 2897006 1245 100.0 True -p-tsh 10015837 1245 100.0 True -i-stathct akiea0019 1240 0.0 False -b-hkr 1333 1237 0.0 False -p-igm 4829 1233 100.0 True -pappakmom 12973 1232 0.0 False -u-ph 325 1232 0.0 False -ntkmom 12976 1231 0.0 False -hcgbvkmom 12974 1231 0.0 False -i-statna akiea0021 1231 100.0 True -i-statk akiea0020 1230 0.0 False -i-statcrea akiea0017 1228 0.0 False -oma-hba1c 5592308 1226 0.0 False -s-prot 3002516 1225 100.0 True -b-leuk 625424 1225 100.0 True -ph,seerumista,osatutk 11554 1224 0.0 False -s-rf 3550 1222 72.46 True -cb-po2 1536 1218 100.0 True -p-crp-hy 7035741 1217 100.0 True -p-gfreepi 11326 1212 100.0 True -p-amyl 605245 1202 100.0 True -p-tsh 10015842 1202 100.0 True -b-tbifng 54254 1200 100.0 True -u-lier 1630671 1194 0.0 False -s-ttgaba 6001885 1191 100.0 True -p-t4-v 10015838 1185 100.0 True -p-ferrit 1605017 1182 100.0 True -b-hkr 602706 1179 100.0 True -p-psa-v 3636304 1178 0.0 False -p-iga 616267 1177 100.0 True -oma-crp-pi 610504 1174 0.0 False -p-tsh 603267 1173 100.0 True -b-hba1c 3636047 1169 0.0 False -b-la 603144 1168 0.0 False -b-lymf 3000043 1167 0.0 False -b-neut 650867 1167 0.0 False -p-gfrtest 15326 1165 0.0 False -l-baso 3000692 1164 0.0 False -l-eos 3000690 1163 0.0 False -l-lymf 3000046 1161 0.0 False -p-kreatiniini 2142 1159 100.0 True -u-sg 0103 1159 0.0 False -u-kemseul,ph 1881_PH 1152 0.0 False -u-suhtih 323 1148 0.0 False -l-monos 3000693 1145 0.0 False -p-psa-v 609298 1142 0.0 False -p-t3-v 607656 1141 0.0 False -b-ghb-a1c,tk 9728 1140 0.0 False -b-hba1c 604132 1139 100.0 True -pt-gfre 648817 1138 0.0 False -e-rdw 2631804 1133 0.0 False -l-neut 650866 1131 0.0 False -p-asat 1001128 1130 100.0 True -fp-pth 3004560 1128 100.0 True -inr/hoito 9910757 1127 0.0 False -u-epitel 0918 1120 0.0 False -p-tt 1731 1115 100.0 True -b-baso 3000040 1109 0.0 False -p-crp-hy 50303 1109 100.0 True -b-eos 3000039 1109 0.0 False -b-monos 3000042 1108 0.0 False -ph 602205 1108 0.0 False -p-t4-v 7010293 1104 100.0 True -cb-be 9218 1098 100.0 True -s-fsh 3001422 1093 81.21 True --cyp4f2 23164 1093 0.0 False -pt-gfre 4083609 1087 0.0 False -p-tni 650660 1087 100.0 True -p-ferrit 1630464 1083 0.0 False -iga/prealb 9407 1082 0.0 False -p-t4-v 10015843 1081 100.0 True -fp-trfesat 3009906 1077 100.0 True -u-ominaispaino 616 1077 0.0 False -p-t4-v 603268 1077 100.0 True -pt-gfreepi 107310 1077 0.0 False -b-retind 3009200 1075 100.0 True -pt-gfreepi 637332 1072 100.0 True -fp-pi 3001431 1071 100.0 True -p-kol-ldl 633118 1067 0.0 False -u-suhti 0352 1067 0.0 False -u-albkre 7033173 1061 100.0 True -u-krea 100274 1058 100.0 True -oma-crp-pika 610504 1056 0.0 False -u-ph 9102 1056 0.0 False -b-pvk+tkd,leuk 102475_1 1051 100.0 True -nu-albkrea 2630765 1048 0.0 False -u-tutk-1,ph 103268_5 1048 0.0 False -s-tpoab 4028 1047 56.22 True -oma-crp 613992 1045 0.0 False -s-mpoabg 4149 1044 98.78 True -b-crp-pik 4052989 1042 0.0 False -cb-be 0769 1042 100.0 True -p-krea 1605305 1038 100.0 True -s-ca-ion 1604774 1036 100.0 True -eos 1000602 1035 0.0 False -bla 1000342 1034 0.0 False -baso 1000603 1034 0.0 False -oma-crp 604324 1033 0.0 False -lymf 1000600 1031 0.0 False -p-prl 1002507 1029 100.0 True -metam 1000345 1025 0.0 False -mono 1000601 1025 0.0 False -nlt 1000347 1025 0.0 False -myel 1000344 1025 0.0 False -nst 1000346 1024 0.0 False -p-cea 1002034 1022 100.0 True -b-inr-pik 3630673 1022 0.0 False -s-b12-tc2 606275 1018 0.0 False -prom 1000343 1016 0.0 False -pt-fib-4 14742 1010 0.0 False -s-pappa 3628524 1009 0.0 False -p-krea 643361 1009 100.0 True -p-b12-vit 4824 1008 100.0 True -ly-tcd4/8. 13896 1005 0.0 False -p-ferrit 3630464 1004 100.0 True -gluk-pika 9029 1002 100.0 True -s-hcg-b-v 605905 997 100.0 True -s-pappa 605906 997 100.0 True -vb-be 0102 994 100.0 True -p-fidd 6004113 992 100.0 True -s-infli 6381 991 100.0 True -emäsylimäärä,kapillaariveri 5400 991 0.0 False -lymf 3223 990 86.15 True -lipemia-indeksi 20537 987 0.0 False -b-hba1c 10017549 984 100.0 True -s-tsh 2102832 979 100.0 True -pikainr 605449 973 0.0 False -s-ccpab 1604746 968 100.0 True -fp-fe 605267 963 100.0 True -s-prealb 2494 962 52.69 True -b-hba1c 604418 960 100.0 True -p-fibr 1399 959 100.0 True -b-hba1c 1632265 954 0.0 False -p-bil-kj 3005310 952 100.0 True -s-digoks 1001256 951 100.0 True -s-k/l-s-v 616407 950 0.0 False -p-k-vt 11376 950 100.0 True -s-valpr 3681 949 100.0 True -kol/hdl-su 0020 945 0.0 False -p-aptt 2783 943 100.0 True -cp-crp-hy 0181 942 100.0 True -u-tutk-1,ph 103268_4 942 0.0 False -p-t4v 2917626 942 100.0 True -s-d-25 3001220 940 100.0 True -b-hb-a1c 604419 937 100.0 True -vb-emäsylimäärä 10085 936 100.0 True -p-psagen 13984 935 100.0 True -b-retik 611321 933 100.0 True -vb-hco3-st 3009075 931 100.0 True -vb-pco2 3001623 931 100.0 True -vb-be 3009074 931 100.0 True --nt 2628525 930 0.0 False -vb-po2 3001537 928 100.0 True -oma-inr-pi 1601502 928 0.0 False -l-baso 1000603 926 0.0 False -fp-pth 606684 923 100.0 True -p-krea 10066521 923 100.0 True -p-tni 4531 921 89.44 True -s-d-25 6001220 920 100.0 True -l-bla 1000342 919 0.0 False -b-hba1c 3897006 918 100.0 True -p-ca 605328 915 0.0 False -l-eos 1000602 914 0.0 False -l-lymf 1000600 911 0.0 False -b-ghb-a1c 101560 907 100.0 True -ab-emäsylimäärä 50030 907 100.0 True -oma-inr 614032 906 0.0 False -s-igg 3001676 903 100.0 True --ph 8591 903 0.0 False -s-ca-iona 7368424 903 100.0 True --nt 3628525 903 0.0 False -l-metam 1000345 901 0.0 False -l-mono 1000601 898 0.0 False -p-prealb 601658 897 100.0 True -inr-vieri 603108 897 0.0 False -b-hba1c 607474 895 0.0 False -fs-folaat 3001416 893 100.0 True -p-psa,sädehoidettupotilas 13983 893 0.0 False -l-myel 1000344 891 0.0 False -p-t3-v 649823 889 100.0 True -pt-gfreepi 624403 888 0.0 False -p-ca-albk 1630650 886 0.0 False -b-peth 14303 886 100.0 True -p-na 1103622 884 100.0 True -s-li 2260 883 100.0 True -s-cdt 2104101 881 0.0 False -l-nlt 1000347 878 0.0 False -p-omagluk 604603 877 0.0 False -oma-u-tutk,u-ph 4601161_3 877 0.0 False -u-prot 1002519 877 100.0 True -oma-hb 601760 875 0.0 False -p-pct 619806 873 0.0 False -p-krea 604950 872 100.0 True -p-ck-mbm 4525 871 100.0 True -e-punasolujenkokojakauma 19976 870 100.0 True -oma-crp 601063 869 100.0 True -l-nst 1000346 868 0.0 False -pt-gfreepi 3738240 868 0.0 False -p-psa 1003642 867 100.0 True -u-pienep 1665082 865 0.0 False -u-levyep 1665081 864 0.0 False -l-prom 1000343 862 0.0 False -oma-ghb-a1 601860 851 0.0 False -s-cea 2034 848 100.0 True -s-dmklots 3004208 844 99.21 True -p-ld 605263 844 100.0 True -l-neut 398 844 100.0 True --s.yht. 8593 844 0.0 False -s-b12-tc2 101142 843 100.0 True -s-immunoglobuliini,kevyetketjut,vapaat,kappa-lambda-suhde 50207 840 0.0 False -p-psa-suh 604838 835 100.0 True -p-psa-v 604837 834 100.0 True -pikau-stix,u-ph 39002_U-PH 832 0.0 False -b-hba1c 7010710 829 100.0 True -p-tt-inr 600629 825 100.0 True -u-tutk-1-oma,ph 210_PH 819 0.0 False -p-b12-vit 632851 819 100.0 True -oma-crp 13632 818 0.0 False -fp-transf 605268 816 100.0 True -hb(päiv.hoitaja) akiea0007 816 0.0 False -s-b12-tc2 6001142 811 100.0 True -pt-gfreepi 625832 810 100.0 True -u-albkrea 3630745 808 0.0 False -p-tsh 636807 806 100.0 True -mono 3230 806 86.56 True -s-k/l-s-v 8648 805 0.0 False -u-suhti 2102715 803 100.0 True -fs-pi 1432 803 100.0 True -lymf 191 802 100.0 True -b-crp-vt 1217 800 100.0 True -u-krea 606902 798 0.0 False -p-kol 633117 798 0.0 False -crp(vo:nyhteydessäotettu),tth 8000 797 100.0 True -ab-ph(t) 0061 795 0.0 False -p-k 1101999 794 100.0 True -s-digoks 3001256 793 100.0 True -s-apob/a1-suhde 02249 793 0.0 False -b-trom 9028 793 0.0 False -p-fsh 1001422 790 0.0 False -b-hb-vt 6590 789 100.0 True -p-probnp 620997 788 0.0 False -b-neut 7010326 786 100.0 True -p-probnp 604432 785 100.0 True -p-igg 5577789 783 0.0 False -fp-trfesat 606124 783 100.0 True -p-krea 10066522 783 100.0 True -s-mkomp-4 610184 782 100.0 True -s-alfa-2 610177 782 100.0 True -s-alfa-1 610176 782 100.0 True -s-mkomp-2 610182 782 100.0 True -s-beta-1 610178 782 100.0 True -s-beta-2 610179 782 100.0 True -s-mkomp-3 612058 782 100.0 True -b-pvk+tkd 2475 782 0.0 False -s-gamma 610180 782 100.0 True -s-album 612055 782 100.0 True -s-mkomp-1 610181 782 100.0 True -s-ph 606713 780 0.0 False -s-alb 3001028 779 100.0 True -u-prot 2519 776 55.29 True -as-leuk 2216 773 100.0 True -cu-tilav 3000207 770 100.0 True -as-eryt 1340 767 100.0 True -cu-kesto 3000211 767 100.0 True -vb-o2sat 616664 767 100.0 True -s-pappa 2628524 765 0.0 False -p-krea 626552 763 100.0 True -p-tsh 3959915 762 100.0 True -nu-albkre 23572 761 100.0 True -pika-inr 601848 760 0.0 False -b-hba1cvt 2897647 759 0.0 False -b-eos 10753 753 100.0 True -s-haptog 1545 752 100.0 True -p-tsh 4077049 749 100.0 True -b-crp-vt 10351 748 100.0 True -cb-tt-inrpika 2789 746 0.0 False -fp-fe 2566 746 100.0 True -erblast 8518 744 0.0 False -b-crp 12773 744 100.0 True -e-rdw 11086 744 100.0 True -pf-ph 20032 743 0.0 False -p-kol-hdl 633119 741 0.0 False -u-ph 247 738 0.0 False -u-sakka,eryt 1600029_1 738 0.0 False -u-ph 2600334 738 0.0 False -p-psa 603958 736 100.0 True -s-album 14346 736 100.0 True -s-alfa-1 14347 733 100.0 True -s-beta-1 14349 733 100.0 True -s-alfa-2 14348 732 100.0 True -l-lymf 600 731 100.0 True -p-crp 1605241 731 100.0 True --slco1b1 23168 729 0.0 False -s-beta-2 14350 729 100.0 True -p-ca-albk 2630650 727 0.0 False -s-gamma 14351 726 100.0 True -ab-po2 1535 725 99.99 True -s-cmvavi 1831 722 0.0 False --glutamyylitransferaasi-desialotransferriini-indeksi 12376 720 0.0 False -ab-pco2 1621 711 99.99 True -mono 197 711 100.0 True -gt-cdt-ind 12376 709 0.0 False -fp-gluk,t 602080 708 0.0 False -cu-alb 3035570 708 100.0 True -p-trigly 633120 707 0.0 False -cu-vm 606230 706 100.0 True -s-igf1sds 5379 704 100.0 True -s-etoh 4305 701 94.19 True -p-b12-vit 7037268 700 100.0 True -u-kemseul 1881 699 0.0 False -l-metam 345 698 100.0 True -cu-alb 7033174 697 100.0 True -p-bil 604890 696 100.0 True -p-tt-inr 208 696 0.0 False -p-gt 1489 695 100.0 True -cb-ph 0695 690 0.0 False -u-osmole 609254 690 0.0 False -fs-c-pept 3002503 689 100.0 True -p-igm 5577790 689 0.0 False -f-elast1 3001718 688 100.0 True -p-ck 604428 688 100.0 True -l-nlt 347 686 100.0 True -u-tutk-1-oma,sg 210_SG 686 0.0 False -s-mkomp-1 14352 684 100.0 True -b-ghb-a1c 4001560 683 100.0 True -b-crp 1217 681 100.0 True -ab-ph 10730 681 0.0 False -l-myel 344 681 100.0 True -s-prl 2507 676 94.07 True -l-eos 602 676 100.0 True -b-crp-pika 4052989 675 0.0 False -l-ly 10465 674 100.0 True -p-uraat 605306 673 0.0 False -l-lymf 45080 672 0.0 False -l-baso 603 672 100.0 True -s-t3-v 3002775 669 100.0 True --cd4-solujensuhdecd8-soluihin 10825 665 0.0 False -b-neut 10754 665 100.0 True -l-monos 10466 662 100.0 True -s-prealb 3002494 661 100.0 True -l-mono 601 657 100.0 True -l-bla 342 657 100.0 True -cu-alb-mi 3004084 656 100.0 True -l-neut 10459 652 100.0 True -s-cdt 1104101 651 0.0 False -p-kol 649647 651 0.0 False -u-osmole 4055509 651 0.0 False -pt-gfreepi 647682 650 0.0 False -pt-gfreepinosatutkimus 15326 649 0.0 False -crp-pika 90 648 0.0 False -u-osmole 3636281 647 0.0 False -u-ph-pika 4053012 647 0.0 False -l-nst 346 646 100.0 True -p-kol-ldl 649649 644 0.0 False -s-pappa 619548 643 100.0 True -s-hcgbv 619549 643 100.0 True -u-seulonta,ph 606400_3 643 0.0 False -crp-pika 3009011 642 100.0 True -l-lymf 0301 641 100.0 True -s-gadab 4400 641 98.63 True -u-krea 609416 640 0.0 False -p-kol-hdl 649648 640 0.0 False -b-neut 600321 640 100.0 True -oma-u-tutk,u-gluk-o 4601161_5 640 0.0 False -p-trigly 649650 639 0.0 False -p-ca-albk 3630650 636 0.0 False -cb-bepika 14237 634 0.0 False -nu-albkrea 1630765 633 0.0 False -l-prom 343 632 100.0 True -p-rf 1003550 631 0.0 False -nt- 5568789 631 0.0 False -ph 609994 631 0.0 False -s-hbsab 1608 630 69.71 True -pt-gfre-cg 627011 630 0.0 False -vb-be-vt 11584 629 100.0 True -s-mypnabg 3004150 626 0.0 False -pt-gfre-md 6000 626 100.0 True -baso 599 626 100.0 True -s-mkomp-1 8956 625 100.0 True -s-d-25 2101220 625 0.0 False -s-rnpab 3317 625 100.0 True -b-retind 9200 624 100.0 True -pd-leuk 4329 622 100.0 True -oma-u-tutk,u-keto-o 4601161_6 622 0.0 False -b-eos 600324 620 100.0 True -mono 600317 619 100.0 True -lymf 600322 619 100.0 True -baso 600325 619 100.0 True -baso 600319 619 100.0 True -neut 600315 619 100.0 True -eos 600318 619 100.0 True -mono 600323 619 100.0 True -fp-kol-ldl 1605269 619 100.0 True -lymf 600316 619 100.0 True -p-fsh 6368 618 100.0 True -s-ige 3001673 617 100.0 True -s-ca-i7.4 631497 616 0.0 False -s-ca-iona 631498 614 0.0 False -u-osmest 633075 613 0.0 False -b-crp 5568387 613 0.0 False -oma-u-tutk,u-nitr-o 4601161_2 612 0.0 False -mb-ph 9242 612 0.0 False -glukoosi(päiv.hoitaja) akiea0005 611 0.0 False -p-inr-vt 9103 610 0.0 False -s-ph 631499 609 0.0 False -p-bkvnh 6001 607 63.26 True -s-ferrit 1395 606 100.0 True -u-alb 1101029 605 100.0 True -s-dnaab 8092 605 100.0 True -p-urea 605271 603 100.0 True -p-psa-v 2900846 602 100.0 True -s-valpr 1003681 602 100.0 True -s-sappih 3379 599 100.0 True -l-eos 9214 598 100.0 True -p-prealb 4618 598 99.21 True -cb-crp 1217 598 0.0 False -u-ph 647864 597 0.0 False -pt-gfreepi 7310 594 0.0 False -s-lzm 2289 593 100.0 True -s-crp 1216 592 100.0 True -ntkmom 2897206 591 0.0 False -u-ph-huu 2606671 590 0.0 False -s-klotsa 3964 590 76.33 True -p-uraat 604444 589 100.0 True -pappakmom 2897207 587 0.0 False -hcgbvkmom 2897209 587 0.0 False -s-van 1003277 585 100.0 True -s-hcg-b-v 7032504 584 100.0 True -u-ominp-h 3630844 582 0.0 False -u-sakka,leuk 1600029_2 581 0.0 False -s-li 1002260 575 100.0 True -fe-folaat 7033483 575 100.0 True -oma-u-tutk,u-leuk-o 4601161_1 574 0.0 False -i-statcl akiea0044 574 0.0 False -i-statglu akiea0047 573 0.0 False -p-psa 606898 572 100.0 True -s-pappa 7032503 571 100.0 True -crpvieri 9041 571 100.0 True -s-album 5597572 571 0.0 False -s-alfa-1 5597573 570 0.0 False -u-albkre 10015133 570 100.0 True -p-gluk,tk 70007 569 0.0 False -fs-sappih 3003379 569 100.0 True -s-kysc 1887 569 100.0 True -s-alfa-2 5597574 567 0.0 False -s-igm 3001688 566 100.0 True -u-albkre 603627 565 100.0 True -u-suhteellinentiheysstix 0103 564 0.0 False -p-korsol 2128 564 100.0 True -b-laktevt 11591 563 100.0 True -fp-kolesteroli 4515 562 100.0 True -s-beta-1 5597575 562 0.0 False -pt-gfrekys 23315 561 100.0 True -u-alb 100273 561 100.0 True -vb-emäsylimäärä 9074 560 100.0 True -s-beta-2 5597576 560 0.0 False -b-pco2 3000104 559 100.0 True -b-be 3000105 559 100.0 True -s-shbg 2737 559 100.0 True -b-ph 3000103 558 100.0 True -p-hco3 3000106 558 100.0 True -b-po2 3000107 558 100.0 True -p-amyl 604420 558 100.0 True -s-gamma 5597577 556 0.0 False -s-hepyabg 3954 556 98.43 True -p-psa-suh 1635177 555 0.0 False -fp-gluk 1101468 555 100.0 True -mittaustulos(mmol/l) Trom318 552 0.0 False -p-aptt 3002783 552 100.0 True -p-alaniiniaminotransferaasi 1024 550 100.0 True -p-t3-v 7037276 549 100.0 True -p-antifxa 604282 547 98.55 True -p-tt-inr 103576 545 100.0 True -s-ca-i7.4 10299 544 100.0 True -p-t4v 4832 543 100.0 True -p-fidd-o 7035802 543 100.0 True -vb-ph-vt 11570 542 0.0 False -oma-inr 601064 542 0.0 False -p-prl 4830 542 100.0 True -p-pct 1773 542 80.51 True -p-tpoab 607657 541 0.0 False -oma-u-tutk,u-alb-o 4601161_4 539 0.0 False -u-krea 604314 539 100.0 True -b-leuc-v 0127 538 0.0 False -s-tsh 4002832 538 100.0 True -nu-alb 1606685 538 0.0 False -u-muulier 606695 537 100.0 True -u-levyep 606692 537 100.0 True -u-hyalier 606694 537 100.0 True -u-pienep 606693 537 100.0 True -oma-u-tutk,u-eryt-o 4601161_7 537 0.0 False -vb-be 152 535 100.0 True -oma-gluk 7371081 535 0.0 False -s-gamma 8955 535 100.0 True -p-t4-v 636763 531 100.0 True -u-eryt 606690 529 100.0 True -s-ca-ion 621417 528 0.0 False -b-hb,tk 602081 528 0.0 False -u-osmole 3945815 527 100.0 True -p-inr-o 50220 525 0.0 False -pika-crp 601455 525 0.0 False -s-tfr 1949 524 100.0 True -s-d-25 101220 522 100.0 True -u-bakt 0919 522 0.0 False -i-staturea akiea0051 522 0.0 False -b-glukoosi,hoitoyksikönvieritesti,kokoveri 23229 521 0.0 False -p-afos 7010033 521 100.0 True -s-e2 1366 521 100.0 True -p-d-25 101220 520 100.0 True -b-peth 12510 520 100.0 True -l-ly 3223 519 70.59 True -u-phstix 0105 518 0.0 False -li-igg/alb 3290 517 100.0 True -p-kysc 3004507 517 100.0 True -pt-gfre 2673263 516 0.0 False -l-monos 3230 516 98.19 True -s-cdt 6004101 516 100.0 True -p-tfr 603042 514 0.0 False -s-mkomp-2 8957 514 100.0 True -u-alb 606901 514 0.0 False -p-asat 2605264 513 100.0 True -b-hb 0121 513 0.0 False -p-ck-mbm 607466 511 100.0 True -s-mkomp-3 8958 510 100.0 True -u-leuk 606691 510 100.0 True -s-k/l-s-v 616263 510 0.0 False -b-la 4002203 508 100.0 True -p-psa 613258 506 100.0 True -fp-trigly 1605285 505 100.0 True -l-lymf 0366 505 100.0 True -s-mkomp-4 8959 504 100.0 True -du-ca 1002011 502 100.0 True -s-ana 1002819 501 0.0 False -s-ca-iona 11564 501 100.0 True -b-hba1c/pi 1632285 501 0.0 False -p-haptog 1001545 500 100.0 True -fs-folaat 101416 498 100.0 True -u-suhtih 647862 498 0.0 False -pikau-stix,u-ph 602556_4 498 0.0 False -p-crp-o 8818 496 100.0 True -s-epo 1339 495 68.57 True -b-hkr 101358 495 61.52 True -p-shbg 1002737 495 100.0 True -oma-ghb-a1c 473 494 0.0 False -fp-kol-hdl 1605268 494 100.0 True -nu-alb 4836 494 100.0 True -p-tnt 621002 493 0.0 False -p-iga 650027 492 0.0 False -b-hba1c 614731 492 100.0 True -s-ana 2819 492 100.0 True -s-adali 6382 491 100.0 True -fp-pi 1605029 491 100.0 True -pt-gfreep 2663222 489 0.0 False -b-6-me-mp 21214 488 0.0 False -p-apcres. 13893 488 0.0 False -b-hba1c 3897005 487 100.0 True -s-iga 1666 486 100.0 True -u-albkre 600248 485 100.0 True -du-ca 2011 485 98.22 True -p-ca 645506 485 100.0 True -vb-pco2-vt 11573 485 0.0 False -fp-laktaat 2184 484 100.0 True -b-co 6164 483 100.0 True -u-ph 602090 482 0.0 False -b-6-tgn 21013 482 0.0 False -p-inr(pikamittari) akivo0007 479 100.0 True -vieri-crp 999 477 0.0 False -b-crp-ospkl 604629 477 0.0 False -p-haptog 20476 477 100.0 True -p-fe 1605016 476 100.0 True -pf-ph 5345 473 0.0 False -crp(vo:nyhteydessäotettu),tth 515000 470 100.0 True -crppika 1217 470 100.0 True -u-albkre 613055 468 100.0 True -p-psa-v 2650740 467 0.0 False -s-bil 1185 466 100.0 True -ab-be 150 465 100.0 True -fp-transf 2603428 465 100.0 True -p-tsh 2738611 464 0.0 False -s-lh 3002265 463 79.14 True -cb-inrpika 11451 463 0.0 False -b-crp-os 604629 462 0.0 False -u-alb 101029 461 100.0 True -b-erblast 50610 461 100.0 True -ab-be 0063 460 100.0 True -s-hcgbv/d 3945257 459 0.0 False -neut 612 458 100.0 True -p-lh 1002265 458 0.0 False -fibrosis-4-indeksi 21799 458 0.0 False -mb-be 5429 458 100.0 True -p-psa-suh 3636303 458 0.0 False -s-beta-2 8954 457 100.0 True -s-t4-v 2836 456 100.0 True -p-osmol 4857 456 100.0 True -b-cr 13010 456 100.0 True --trfesat 651773 455 0.0 False -u-suht-hy 0367 453 0.0 False -s-osmol 2443 450 100.0 True -s-shbg 3002737 449 100.0 True -s-album 8950 446 100.0 True -nu-albkrea 606082 445 0.0 False -f-elast1 1718 444 100.0 True -b-hba1c 2644700 442 0.0 False -eosin 11584 441 100.0 True -u-krea 0581 440 100.0 True -p-tnt 610556 440 100.0 True -u-phstix PAIKALLINEN5569008 439 0.0 False -s-k/l-s-v 0996 439 0.0 False -vb-be 4933 439 100.0 True -p-alb 1605324 439 100.0 True -f-elast1 1001718 438 100.0 True -p-tfr 1603042 438 100.0 True -p-psa 10015844 437 100.0 True -i-stathb akiea0018 437 0.0 False -s-hcg 3002122 436 62.34 True -s-beta-1 8953 435 100.0 True -p-asat 1605004 435 100.0 True -pt-gfreepio1 90062 434 100.0 True -s-mkomp-1 5597578 434 0.0 False -s-alfa-1 8951 432 100.0 True -du-prot 2513 431 72.86 True -u-hb-o 6001556 431 0.0 False -pt-gfreepi 2738770 429 0.0 False -p-bnp 650661 429 100.0 True -s-alfa-2 8952 428 100.0 True -li-igg 1675 427 99.03 True -u-krea 4002145 426 100.0 True -u-seulont,ph 606400_3 423 0.0 False -s-pölyer 7154 423 0.0 False -u-gluk-o 6001479 422 0.0 False -b-krea 13053 421 0.0 False -p-hcg-tot 21251 421 0.0 False -b-k 12447 420 0.0 False -ab-be 0766 420 100.0 True -vb-caionvt 11588 420 100.0 True -pikahb 601215 419 0.0 False -b-na 12448 418 0.0 False -u-keto-o 6001122 418 0.0 False -p-psa 7010628 418 100.0 True -b-eos 4001330 417 100.0 True -u-nitr-o 6003094 416 0.0 False -b-neut 4003238 416 100.0 True -li-igg-ind 224 415 0.0 False -b-eos 1332 413 99.58 True -s-tpoab 1004028 413 0.0 False -p-psa-suh 609297 413 0.0 False -b-inr-pik 2630673 412 0.0 False -p-uraat 1605270 412 100.0 True -b-hb-a1c 7010327 411 100.0 True -fp-b6-vit 6080 411 100.0 True -p-fidd 104113 411 100.0 True -kolesterolinjahdl-kolesterolinsuhde VI0020 411 0.0 False -p-psa 1615989 410 100.0 True -nu-albkrea 3630765 410 0.0 False -oma-crp 10011274 410 0.0 False -p-afos 1605244 410 100.0 True -pt-audio/i 2279505 410 0.0 False -b-mono 9231 409 99.98 True -p-tfr 604443 408 100.0 True -p-igg 616268 408 100.0 True -p-c3 4545 408 100.0 True -l-lymf(a) 4009235 407 100.0 True -cp-gluk 1605207 407 100.0 True -b-ly 4003223 407 100.0 True -b-monos 4003230 407 100.0 True -l-baso(a) 4001168 407 100.0 True -l-mono(a) 4000399 407 100.0 True -pappakmom 3945256 407 0.0 False -b-hb 101552 407 100.0 True -l-eos(a) 4001332 407 100.0 True -ntkmom 3945255 407 0.0 False -b-baso 4003157 407 100.0 True -l-neut(a) 4000398 407 100.0 True -hcgbvkmom 3945258 406 0.0 False -p-korsol 7037273 406 100.0 True -p-bil 1605325 405 100.0 True -s-dmklots 4208 405 60.81 True -u-leuk-o 6002223 405 0.0 False -pt-ekg-12 1270 405 0.0 False -punasolujenerittelylaskenta 20408 404 0.0 False -l-mono 9213 403 100.0 True -fs-folaat 2101416 401 100.0 True -u-prot-o 6001030 400 0.0 False -u-kemseul,omin.p 1881_OMIN.P 399 0.0 False -s-psa-v/t 622478 398 0.0 False -s-k/l-s-v 0339 396 100.0 True -b-konedif,lymf 603012_2 395 0.0 False -b-konedif,eos 603012_4 395 0.0 False -b-konedif,neutro 603012_1 395 0.0 False -b-konedif,baso 603012_5 395 0.0 False -u-alb 4001029 395 100.0 True -p-pct 6462 395 100.0 True -b-konedif,monos 603012_3 395 0.0 False -b-hba1c/pika 1632285 393 0.0 False -p-kol-ldl 1674162 392 0.0 False -b-qr-crp 5017728 392 100.0 True -p-fsh 7037272 390 100.0 True -s-c1inh 1209 390 100.0 True -mittaustulos(mg/l) Mit403 390 0.0 False -p-c-reaktiivinenproteiinipikahoitoyksiköt 8518 389 100.0 True -s-ttgaba 1020053 387 100.0 True -s-tpoab 6004028 387 100.0 True -b-leuk 102218 386 100.0 True -vb-ahco3vt 11581 386 100.0 True -s-valpr 6003681 386 100.0 True -p-gt 1605248 386 100.0 True -s-psa 103642 384 100.0 True -b-tbifng 6173 382 93.97 True -u-suhti 102715 382 100.0 True -ab-be 4913 381 100.0 True -fp-krea 1002143 380 100.0 True -p-glukhoi 8512 380 100.0 True -ab-be 45136 378 100.0 True -f-calpro 7354384 377 100.0 True -happamuusaste 1530 377 0.0 False -u-gluk-o 0479 377 0.0 False -p-ferrit 608791 376 100.0 True -u-keto-o 0022 376 0.0 False -s-borrabm 3004096 374 0.0 False -s-mg 2303 373 100.0 True -p-glukoosipikahoitoyksiköt 8512 373 100.0 True -5400 5400 373 0.0 False -u-ph-o 0303 373 0.0 False -oma-pt-ekg 7029004 372 0.0 False -cu-alb-mi 1004084 371 100.0 True -s-ph 10492 370 0.0 False -cp-inr-vt 8162 369 0.0 False -pf-ph 10193 369 0.0 False -p-c4 4546 369 100.0 True -p-gt 101489 368 100.0 True -b-leuk/pi 3636214 367 0.0 False -s-t3-v 2775 365 100.0 True -e-rdw 632931 365 100.0 True -p-psa 603269 364 100.0 True -p-d-25 2901445 364 100.0 True -p-krea 21422 363 100.0 True -p-kalium 1999 363 100.0 True -b-eryt 101341 362 100.0 True -s-igg 1676 362 100.0 True -e-mch 101558 361 100.0 True -pf-ph 50056 361 0.0 False -p-tyreotropiini 4831 361 98.98 True -p-psa-v 622555 360 100.0 True -pikau-sti,u-leuk-o 602556_7 359 0.0 False -pikau-sti,u-prot-o 602556_5 359 0.0 False -pikau-sti,u-keto-o 602556_2 359 0.0 False -pikau-sti,u-eryt-o 602556_3 359 0.0 False -s-t4-v 102836 359 100.0 True -pikau-sti,u-nitr-o 602556_6 359 0.0 False -b-keto/pik 20 358 0.0 False -pikau-sti,u-gluk-o 602556_1 358 0.0 False -u-tutk-1 3268 358 0.0 False -pikau-sti,u-ph 602556_4 358 0.0 False -u-omin.p- 4053014 358 0.0 False -p-tt-inr 600607 358 100.0 True -p-hcg-tot 633200 358 0.0 False -b-neut N689 358 0.0 False -p-psa 10015839 357 100.0 True -s-ace 1001092 356 0.0 False -ps-crp 602398 356 0.0 False -b-baso 1168 355 100.0 True -leuk-pika 604532 353 100.0 True -du-prot 1002513 352 100.0 True -s-puumabm 3528 352 0.0 False -s-klotsa 7003964 352 100.0 True -p-kol-ldl 3663264 351 0.0 False -s-d-1,25 3003163 351 0.0 False -cb-be 0101 350 100.0 True -b-hba1c/pika 3657981 349 0.0 False -b-hkr 610021 349 100.0 True -s-dmklots 6004208 349 100.0 True -u-nitr-o 0094 348 0.0 False -u-albkrea 614987 347 100.0 True -s-sappih 3003379 347 100.0 True -cb-be 313 346 100.0 True -fs-sappih 3379 346 100.0 True -emäsylimäärä,valtimoveri 5382 346 100.0 True -hb-pika 604533 345 100.0 True -p-probnp 1632369 345 0.0 False -b-trom 102791 344 100.0 True -u-suhti-o 2715 344 0.0 False -b-fosfatidyylietanoli 14303 344 0.0 False -ca++/ph7.4 9551 343 100.0 True -b-crp-o 9700 342 0.0 False -vb-ph 0341 341 0.0 False -p-rf 2629868 340 0.0 False -p-ca 1605328 340 100.0 True -du-tilav 3000208 338 100.0 True -s-mypnabg 1004150 337 0.0 False -s-smab 3324 337 100.0 True -s-psa-suh 4637 337 99.22 True -s-hepyabg 1003954 337 87.5 True -cb-be 45139 336 100.0 True -u-pienep 3967099 335 0.0 False -s-koivue 7015 334 0.0 False -p-psa-v 4059090 334 0.0 False -u-albkre 10015113 334 100.0 True -u-prot-o 0030 333 0.0 False -b-hb-a1c 1560 333 93.78 True -u-levyep 3967098 333 0.0 False -s-toxoabg 2749 333 100.0 True -p-urea 1605077 331 100.0 True -p-tromboplastiiniaika-pika,inrpika-tulos 50489 331 0.0 False -p-tnt 1629464 331 0.0 False -s-t4-v 4002836 329 100.0 True -nu-alb 2606685 329 0.0 False -u-epit 1630670 329 0.0 False -l-mono 0915 328 100.0 True -du-prot 3002513 328 95.76 True -u-osmole 1635090 328 0.0 False -l-lymf 9212 327 100.0 True -l-lymf 0903 327 100.0 True -p-preurea 11500 326 100.0 True -p-non-hdl 7908 326 0.0 False -inr-vieri 96 326 0.0 False -p-amylp 1634830 326 0.0 False -li-gluk 1470 326 100.0 True -u-osmole 617905 326 100.0 True -b-leuk-vt 6589 326 100.0 True -s-afp 1001040 326 100.0 True -p-igm 616269 325 100.0 True -ab-ph(t) 0007 325 0.0 False -l-eos 0912 324 100.0 True -s-ige 6001673 324 100.0 True -p-t4-v 3959916 324 100.0 True -vb-bepika 14233 324 100.0 True -p-d-25 609559 324 0.0 False -psa-v/psa 610015 323 100.0 True -p-psa-v 610014 323 100.0 True -u-albkre 604312 323 100.0 True -b-hba1c 3632264 323 0.0 False -p-pc 3003435 322 100.0 True -s-timotee 7009 321 100.0 True -s-ca19-9 3003412 321 100.0 True -p-prl 1605031 320 100.0 True -u-phstix 9004 318 0.0 False -b-ly 7010064 318 100.0 True -u-ph 101530 318 0.0 False -ab-be 0204 317 100.0 True -u-levyep 3658861 316 0.0 False -u-albkre 603121 316 100.0 True -s-dgpabg 618505 316 0.0 False -oma-fp-glu 602182 316 0.0 False -u-sakka,leuk 102600_2 316 0.0 False -s-prot 6002516 316 100.0 True -u-pienep 3658862 315 0.0 False -u-huum-7,ph 606595_8 315 0.0 False -pappakmom 3897207 313 0.0 False -cu-alb-mi 4084 313 100.0 True -ntkmom 3897206 313 0.0 False -hcgbvkmom 3897209 313 0.0 False -u-sakka,epit 102600_3 311 0.0 False -s-tpoab 3004028 311 67.55 True -p-inr 3576 311 0.0 False -p-reninm 6339 311 100.0 True -p-haptog 617396 309 100.0 True -p-inr-vt 653 308 0.0 False -u-krea 1102145 306 100.0 True -u-ph 10099 305 0.0 False -u-sakka,makrof 102600_4 305 0.0 False -b-lymf 9230 305 100.0 True -sao2 9743 305 0.0 False -p-kol 1674160 304 0.0 False -u-ph 375 304 0.0 False -p-psa-suh 603960 304 100.0 True -p-psa-v 603959 304 100.0 True -p-hcg 7034641 304 100.0 True -b-hba1c 603188 303 100.0 True -u-sakka,eryt 102600_1 303 0.0 False -p-antifxa 1003828 303 100.0 True -psa-v/psa 602225 303 100.0 True -fp-nh4-ion 3001071 302 100.0 True -u-sakka,lier 102600_5 302 0.0 False -fb-gluk 1467 302 100.0 True -p-asat 605264 302 100.0 True -u-ph-o PAIKALLINEN103667 301 0.0 False -s-olants 3001900 301 100.0 True -ps-inr 602401 300 0.0 False -u-ominaisp akiosa0009 300 0.0 False -e-retik 6002582 300 100.0 True -plasmaninr(k) 3576 299 0.0 False -p-lh 6367 299 100.0 True -fp-urea 3004573 298 100.0 True -fs-sappih 1003379 298 100.0 True -s-kalsium,ionisoitunut 597 297 100.0 True -p-tt-inr 615121 296 0.0 False -b-gluk 0111 295 0.0 False -b-ti 6166 295 100.0 True -l-blastit 674 295 100.0 True -b-erytrosyytit,tilavuusosuus 0639 295 0.0 False -p-probnp 3636089 293 0.0 False -fs-rf 3003550 293 100.0 True -u-leuk. 14057 292 100.0 True -l-metamye 677 292 100.0 True -u-eryt. 14056 292 100.0 True -s-ca12-5 3003414 291 100.0 True -u-ph 600334 291 0.0 False -u-albkrea 606080 291 0.0 False -p-t4-v 2738612 291 0.0 False -epit.solut 14058 291 0.0 False -p-tni 621001 289 0.0 False -u-osmol 3002444 289 100.0 True -s-borrabm 4096 289 100.0 True -sy-leuk 1003080 289 100.0 True -fs-pth 1603680 289 0.0 False -s-dnanab 1261 288 58.48 True -b-retik 7354422 288 100.0 True -b-baso 7010065 288 100.0 True -b-monos 7010066 288 100.0 True -pt-fvspido 618833 288 0.0 False -pt-fvspiro 1002680 287 0.0 False -l-myelos 676 286 100.0 True -s-klotsa 602622 285 100.0 True -fp-trfesat 8855 285 100.0 True -u-leuk-o 0222 284 0.0 False -cb-inr-oma 21392 284 0.0 False -s-vlseabm 618440 284 0.0 False -p-omagluk 600554 284 0.0 False -p-t4-v 4077050 283 100.0 True -b-inr-vt 6597 283 0.0 False -s-hepyabg 3003954 282 100.0 True -s-li 6002260 282 100.0 True -p-bnp 620999 282 0.0 False -p-myogl 615783 282 0.0 False -emäsylimäärä,koneveri 5429 281 0.0 False -pt-gfreep 21218 281 0.0 False -b-la 1102203 281 100.0 True -u-kemseul,ph 103268_5 279 0.0 False -s-k/l-s-v 9055 279 0.0 False -p-amyl 1605266 279 100.0 True -kol/hdl 5008 278 0.0 False -p-crp 2605304 278 100.0 True -fp-c-pept 616725 278 0.0 False -baso 3157 277 100.0 True -u-phv 1364 275 0.0 False -b-hba1c/pi 3657981 275 0.0 False -fs-transferiininrautakyllästeisyys 10100 275 0.0 False -p-tt 615925 275 0.0 False -s-hcgbv/d 608216 274 0.0 False -p-kol-hdl 1674161 274 0.0 False -s-papp-a 2628524 274 0.0 False -fe-folaat 604293 274 100.0 True -emäsylimäärä,laskimoverestä,pikatesti 14233 273 0.0 False -lieriöt 14059 273 100.0 True -u-suhtih 373 272 0.0 False -s-k/l-s-v 0626 272 0.0 False -ab-ph 9452 272 0.0 False -l-promyel 675 272 100.0 True -sy-solut 3002658 272 0.0 False -p-rf 1605251 271 100.0 True --transf 20426 269 100.0 True -du-iglck 98320 269 0.0 False -p-probnp 2897325 269 0.0 False -p-tt-inr 104520 268 100.0 True -kolesterolinjahdl-kolest.suhde 0020 268 0.0 False 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new file mode 100644 index 0000000..4c30f25 --- /dev/null +++ b/scripts/injection/data/summary_table.md @@ -0,0 +1,9 @@ +*Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements* + +| Threshold | UNAMBIGUOUS test names | UNAMBIGUOUS measurements | AMBIGUOUS test names | AMBIGUOUS measurements | NO_DATA test names | NO_DATA measurements | +| --- | ---: | ---: | ---: | ---: | ---: | ---: | +| 95% | 434 (60.7%) | 26,508,342 (82.9%) | 79 (11.0%) | 4,345,264 (13.6%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 98% \* | 413 (57.8%) | 24,979,594 (78.2%) | 100 (14.0%) | 5,874,012 (18.4%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 99% | 392 (54.8%) | 22,954,996 (71.8%) | 121 (16.9%) | 7,898,610 (24.7%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 100% | 275 (38.5%) | 12,745,902 (39.9%) | 238 (33.3%) | 18,107,704 (56.7%) | 202 (28.3%) | 1,108,898 (3.5%) | +| **TOTAL** | **715** | | | || | diff --git a/scripts/injection/data/test_names_exploration_scatter.png 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g7fSyx4%JFgnlsV!c!}=WX>#Ev2aXzL?05O)KOrlrI{*Lx diff --git a/scripts/injection/explore_test_name.py b/scripts/injection/explore_test_name.py new file mode 100644 index 0000000..cfb40ee --- /dev/null +++ b/scripts/injection/explore_test_name.py @@ -0,0 +1,813 @@ +#!/usr/bin/env python3 +""" +explore_test_name.py + +Identifies lab measurements that have a numeric value but no unit, characterises +the unit distribution of matching records that do have a unit, and optionally +runs the injection engine to validate each candidate TEST_NAME. + +Usage +----- + python3 explore_test_name.py PARQUET MIN_COUNT [options] +""" + +import argparse +import os +import re +import subprocess +import sys +from pathlib import Path + +import numpy as np +import pandas as pd + +import injection_engine +from plot_exploration import make_scatter_plot + + +# --------------------------------------------------------------------------- +# ClickHouse +# --------------------------------------------------------------------------- + +def clickhouse(query, **params): + cmd = ["clickhouse", "-q", query] + for k, v in params.items(): + cmd.append(f"--param_{k}={v}") + proc = subprocess.run(cmd, capture_output=True, text=True) + if proc.returncode != 0: + print(proc.stderr, file=sys.stderr) + raise RuntimeError("ClickHouse query failed") + return proc.stdout + + +# --------------------------------------------------------------------------- +# Queries +# --------------------------------------------------------------------------- + +_COUNTS_MIN = 50 # fixed baseline for the cached query; --min-count filters post-load + + +def query_counts(parquet, out="test_name_counts.tsv"): + if Path(out).exists(): + print(f"{out} already exists, skipping.") + return pd.read_csv(out, sep="\t") + + result = clickhouse(f""" + SELECT TEST_NAME, count() AS COUNT + FROM file('{parquet}') + WHERE (MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_SOURCE IS NOT NULL) + AND MEASUREMENT_UNIT_PRE_FIX IS NULL + GROUP BY TEST_NAME + HAVING COUNT > {_COUNTS_MIN} + ORDER BY COUNT DESC + FORMAT TSVWithNames + """) + Path(out).write_text(result) + df = pd.read_csv(out, sep="\t") + print(f"Wrote {out} ({len(df)} rows)") + return df + + +def query_details(parquet, counts_file="test_name_counts.tsv", out="test_name_details.tsv"): + if Path(out).exists(): + print(f"{out} already exists, skipping.") + return pd.read_csv(out, sep="\t") + + counts_abs = str(Path(counts_file).resolve()) + result = clickhouse(f""" + WITH + global_names AS ( + SELECT DISTINCT TEST_NAME + FROM file('{counts_abs}', TSVWithNames) + ), + top3_units AS ( + SELECT + TEST_NAME, + argMax(MEASUREMENT_UNIT_PRE_FIX, unit_cnt) AS UNIT, + concat('{{', arrayStringConcat(groupArray(unit_json), ','), '}}') AS PREVALENCE_DICT + FROM ( + SELECT TEST_NAME, MEASUREMENT_UNIT_PRE_FIX, unit_cnt, unit_json + FROM ( + SELECT + TEST_NAME, MEASUREMENT_UNIT_PRE_FIX, unit_cnt, + ROW_NUMBER() OVER (PARTITION BY TEST_NAME ORDER BY unit_cnt DESC) AS rn, + concat( + MEASUREMENT_UNIT_PRE_FIX, ':', + toString(round(100.0 * unit_cnt / SUM(unit_cnt) OVER (PARTITION BY TEST_NAME), 2)) + ) AS unit_json + FROM ( + SELECT TEST_NAME, MEASUREMENT_UNIT_PRE_FIX, count() AS unit_cnt + FROM file('{parquet}') + WHERE MEASUREMENT_VALUE_SOURCE IS NOT NULL + AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL + GROUP BY TEST_NAME, MEASUREMENT_UNIT_PRE_FIX + ) AS sub + ) AS ranked + WHERE rn <= 3 + ) AS top3 + GROUP BY TEST_NAME + ), + total_counts AS ( + SELECT TEST_NAME, count() AS COUNT + FROM file('{parquet}') + WHERE MEASUREMENT_VALUE_SOURCE IS NOT NULL + AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL + GROUP BY TEST_NAME + ) + SELECT + t.TEST_NAME AS TEST_NAME, + t.COUNT AS COUNT, + u.UNIT AS UNIT, + u.PREVALENCE_DICT AS PREVALENCE_DICT + FROM total_counts t + LEFT JOIN top3_units u USING (TEST_NAME) + INNER JOIN global_names g USING (TEST_NAME) + ORDER BY t.COUNT DESC + FORMAT TSVWithNames + """) + Path(out).write_text(result) + df = pd.read_csv(out, sep="\t") + print(f"Wrote {out} ({len(df)} rows)") + return df + + +# --------------------------------------------------------------------------- +# Plot table +# --------------------------------------------------------------------------- + +def build_plot_table(counts, details): + def parse_top_prevalence(d): + if pd.isna(d): + return None + pcts = re.findall(r':(\d+\.?\d*)[,}]', str(d)) + return max(float(p) for p in pcts) if pcts else None + + details = details.copy() + details["top_prevalence"] = details["PREVALENCE_DICT"].apply(parse_top_prevalence) + + plot_name = counts.merge( + details[["TEST_NAME", "top_prevalence", "COUNT"]].rename(columns={"COUNT": "N_WITH_UNIT"}), + on="TEST_NAME", how="left", + ) + plot_name["top_prevalence"] = plot_name["top_prevalence"].fillna(0) + plot_name["N_WITH_UNIT"] = plot_name["N_WITH_UNIT"].fillna(0).astype(int) + return plot_name + + +# --------------------------------------------------------------------------- +# Summary table +# --------------------------------------------------------------------------- + +_SUMMARY_THRESHOLDS = [95, 98, 99, 100] + + +def _cat_at(df, t, min_target_n): + return np.select( + [ + df["N_WITH_UNIT"] < min_target_n, + df["top_prevalence"] >= t, + df["top_prevalence"] > 0, + ], + ["NO_DATA", "UNAMBIGUOUS", "AMBIGUOUS"], + default="NO_DATA", + ) + + +def _add_category(plot_name, threshold, min_target_n): + """Add CATEGORY (operational) and CATEGORY_{t} (exploratory) columns.""" + df = plot_name.copy() + df["CATEGORY"] = _cat_at(df, threshold, min_target_n) + for t in _SUMMARY_THRESHOLDS: + df[f"CATEGORY_{t}"] = _cat_at(df, t, min_target_n) + return df + + +def print_summary(plot_name, threshold): + total = len(plot_name) + total_n = int(plot_name["COUNT"].sum()) + + tw = 13 # test_names cell width + mw = 18 # measurements cell width + + cats = ["UNAMBIGUOUS", "AMBIGUOUS", "NO_DATA"] + + # Header + print() + h1 = f"{'':>12}" + h2 = f"{'Threshold':>10} " + sep = f"{'':>12}" + for cat in cats: + h1 += f" {cat:^{tw+mw+2}}" + h2 += f" {'TEST_NAMES':>{tw}} {'MEASUREMENTS':>{mw}}" + sep += f" {'-'*tw} {'-'*mw}" + print(h1) + print(h2) + print(sep) + + for t in _SUMMARY_THRESHOLDS: + marker = " *" if t == threshold else " " + row = f"{t:>9}%{marker}" + for cat in cats: + sub = plot_name[plot_name[f"CATEGORY_{t}"] == cat] + n = len(sub) + m = int(sub["COUNT"].sum()) + row += f" {f'{n:,} ({100*n/total:.1f}%)':>{tw}} {f'{m:,} ({100*m/total_n:.1f}%)':>{mw}}" + print(row) + + print(sep) + print(f"{'TOTAL':>12} {total:>{tw},}{'':>{mw+4}}" + f" {'':>{tw}} {total_n:>{mw},}") + print(f"\n * = active threshold ({threshold}%)\n") + + +def dump_summary_md(plot_name, threshold, min_count, out="summary_table.md"): + total = len(plot_name) + total_n = int(plot_name["COUNT"].sum()) + cats = ["UNAMBIGUOUS", "AMBIGUOUS", "NO_DATA"] + + lines = [] + lines.append(f"*Active threshold: {threshold}% — min count: {min_count:,} — " + f"{total:,} TEST_NAMEs, {total_n:,} measurements*\n") + + header = "| Threshold | " + " | ".join( + f"{c} test names | {c} measurements" for c in cats + ) + " |" + sep = "| --- | " + " | ".join(["---: | ---:" for _ in cats]) + " |" + lines.append(header) + lines.append(sep) + + for t in _SUMMARY_THRESHOLDS: + marker = " \\*" if t == threshold else "" + row = f"| {t}%{marker} |" + for cat in cats: + sub = plot_name[plot_name[f"CATEGORY_{t}"] == cat] + n = len(sub) + m = int(sub["COUNT"].sum()) + row += f" {n:,} ({100*n/total:.1f}%) | {m:,} ({100*m/total_n:.1f}%) |" + lines.append(row) + + lines.append(f"| **TOTAL** | **{total:,}** | | " + "| |" * (len(cats) - 1)) + + Path(out).write_text("\n".join(lines) + "\n") + print(f"Wrote {out}") + + +# --------------------------------------------------------------------------- +# Injection engine +# --------------------------------------------------------------------------- + +def _query_test_values(parquet, name, mode, unit=None): + if mode == "candidate": + q = f""" + SELECT coalesce(MEASUREMENT_VALUE_EXTRACTED, MEASUREMENT_VALUE_SOURCE) AS value + FROM file('{parquet}') + WHERE TEST_NAME = {{name:String}} + AND MEASUREMENT_UNIT_PRE_FIX IS NULL + AND isNotNull(coalesce(MEASUREMENT_VALUE_EXTRACTED, MEASUREMENT_VALUE_SOURCE)) + FORMAT TSV + """ + out = clickhouse(q, name=name) + else: + q = f""" + SELECT MEASUREMENT_VALUE_SOURCE AS value + FROM file('{parquet}') + WHERE TEST_NAME = {{name:String}} + AND MEASUREMENT_UNIT_PRE_FIX = {{unit:String}} + AND MEASUREMENT_VALUE_SOURCE IS NOT NULL + FORMAT TSV + """ + out = clickhouse(q, name=name, unit=unit) + if not out.strip(): + return np.array([]) + vals = [] + for line in out.strip().split("\n"): + try: + vals.append(float(line.strip())) + except ValueError: + pass + return np.sort(np.array(vals, dtype=float)) + + +def _sample_deciles(df): + """Return one row per COUNT decile (by rank), up to 10 rows.""" + df = df.reset_index(drop=True) + n = len(df) + indices = sorted({int(round((i / 9) * (n - 1))) for i in range(10)}) + return df.iloc[indices] + + +_PCTS = [10, 20, 30, 40, 50, 60, 70, 80, 90] + + +def _fmt_deciles(arr): + vals = np.percentile(arr, _PCTS) + return "[" + ",".join(f"{v:.4g}" for v in vals) + "]" + + +def _run_engine(c_vals, t_vals, name, dump_dir, prevalence=None, tag_override=None): + """Run KS / T / MAD pipeline, save diagnostic plot, return (updates, ks, t, mad).""" + ks_step = injection_engine._ks(c_vals, t_vals, ks_threshold=0.3, sig_level=0.05) + t_step = injection_engine._t(c_vals, t_vals, sig_level=0.05) + mad_step = injection_engine._mad(c_vals, t_vals, n_mad=3.0) + + ks_mlogp = -np.log10(np.clip(ks_step.details["pval"], 1e-300, 1.0)) + t_mlogp = -np.log10(np.clip(t_step.details["pval"], 1e-300, 1.0)) + + if ks_step.passed: + decided_by, outcome = "KS", "PASS" + elif t_step.passed: + decided_by, outcome = "T", "PASS" + else: + decided_by = "MAD" + outcome = "PASS" if mad_step.passed else "FAIL" + + result = injection_engine.PipelineResult(outcome, decided_by, + [ks_step, t_step, mad_step]) + injection_engine.plot_result(c_vals, t_vals, result, name, dump_dir, + prevalence=prevalence, tag_override=tag_override) + + n_passed = sum(s.passed for s in [ks_step, t_step, mad_step]) + updates = dict( + KS_STAT=ks_step.details["stat"], KS_MLOGP=ks_mlogp, + KS_PASS="PASS" if ks_step.passed else "FAIL", + T_STAT=t_step.details["stat"], T_MLOGP=t_mlogp, + T_PASS="PASS" if t_step.passed else "FAIL", + MAD_DIST=mad_step.details["distance"], + MAD_THRESHOLD=mad_step.details["threshold"], + MAD_PASS="PASS" if mad_step.passed else "FAIL", + OUTCOME=outcome, + NOTES=f"{outcome}_at_{decided_by}_({n_passed}/3)", + CAND_DECILES=_fmt_deciles(c_vals), + TARG_DECILES=_fmt_deciles(t_vals), + ) + return updates, ks_step, t_step, mad_step + + +def run_unambiguous(parquet, plot_name, details, dump_dir, test_mode=False): + os.makedirs(dump_dir, exist_ok=True) + + unambig = plot_name[plot_name["CATEGORY"] == "UNAMBIGUOUS"].sort_values("COUNT", ascending=False) + if test_mode: + unambig = _sample_deciles(unambig) + test_names = unambig["TEST_NAME"].tolist() + print(f"Unambiguous TEST_NAMEs: {len(test_names)}") + + dom_unit = dict(zip(details["TEST_NAME"], details["UNIT"])) + prev_dict = dict(zip(details["TEST_NAME"], details["PREVALENCE_DICT"])) + + rows = [] + n_pass = n_fail = n_skip = 0 + + for i, name in enumerate(test_names, 1): + print(f" [{i:>4}/{len(test_names)}] {name:<40}", end=" ", flush=True) + + tag = name.replace("/", "_").replace(" ", "_") + cand_npy = os.path.join(dump_dir, f"cand_{tag}.npy") + targ_npy = os.path.join(dump_dir, f"targ_{tag}.npy") + + unit = dom_unit.get(name, "NA") + prev = prev_dict.get(name, "NA") + + if os.path.exists(cand_npy): + c_vals = np.load(cand_npy) + print("cand=cache", end=" ", flush=True) + else: + print("cand=query", end=" ", flush=True) + c_vals = _query_test_values(parquet, name, "candidate") + np.save(cand_npy, c_vals) + + if os.path.exists(targ_npy): + t_vals = np.load(targ_npy) + print(f"targ=cache({unit})", end=" ", flush=True) + else: + print(f"targ=query({unit})", end=" ", flush=True) + t_vals = _query_test_values(parquet, name, "target", unit=unit) + np.save(targ_npy, t_vals) + + print(f"N={len(c_vals):,}/{len(t_vals):,}", end=" ", flush=True) + + row = dict(TEST_NAME=name, UNIT=unit, PREVALENCE_DICT=prev, + N_CANDIDATE=len(c_vals), N_TARGET=len(t_vals), + KS_STAT=np.nan, KS_MLOGP=np.nan, KS_PASS="NA", + T_STAT=np.nan, T_MLOGP=np.nan, T_PASS="NA", + MAD_DIST=np.nan, MAD_THRESHOLD=np.nan, MAD_PASS="NA", + OUTCOME="SKIP", NOTES="SKIP(NO_DATA)") + + if len(c_vals) >= 2 and len(t_vals) >= 2: + print("engine...", end=" ", flush=True) + updates, ks, t, mad = _run_engine(c_vals, t_vals, name, dump_dir, + prevalence=prev) + row.update(updates) + print( + f"KS={'P' if ks.passed else 'F'}" + f"(stat={ks.details['stat']:.3g},mlogp={updates['KS_MLOGP']:.1f},{ks.details['method']})" + f" T={'P' if t.passed else 'F'}(mlogp={updates['T_MLOGP']:.1f})" + f" MAD={'P' if mad.passed else 'F'}" + f"(dist={mad.details['distance']:.3f},thr={mad.details['threshold']:.3f})", + end=" ", flush=True, + ) + + if row["OUTCOME"] == "PASS": n_pass += 1 + elif row["OUTCOME"] == "FAIL": n_fail += 1 + else: n_skip += 1 + + rows.append(row) + print(f"{row['OUTCOME']} ({row['NOTES']}) " + f"[running: {n_pass}P/{n_fail}F/{n_skip}S] {prev}") + + cols = ["TEST_NAME", "UNIT", "PREVALENCE_DICT", "N_CANDIDATE", "N_TARGET", + "CAND_DECILES", "TARG_DECILES", + "KS_STAT", "KS_MLOGP", "KS_PASS", + "T_STAT", "T_MLOGP", "T_PASS", + "MAD_DIST", "MAD_THRESHOLD", "MAD_PASS", + "OUTCOME", "NOTES"] + results = pd.DataFrame(rows, columns=cols) + for col in ("TEST_NAME", "UNIT", "OUTCOME", "NOTES"): + results[col] = results[col].str.replace(" ", "_", regex=False) + results.to_csv("unambiguous_results.tsv", sep="\t", index=False, + float_format="%.4g", na_rep="NA") + print(f"\nWrote unambiguous_results.tsv ({len(results)} rows)") + return results + + +# --------------------------------------------------------------------------- +# Ambiguous injection +# --------------------------------------------------------------------------- + +def parse_top_units(prevalence_dict, n=3): + """Parse '{unit1:pct1,unit2:pct2,...}' → list of (unit, pct) sorted by pct desc.""" + if pd.isna(prevalence_dict) or str(prevalence_dict) in ("", "NA", "nan"): + return [] + matches = re.findall(r'([^:{},\s][^:{},]*):(\d+\.?\d*)', str(prevalence_dict)) + pairs = [(u.strip(), float(p)) for u, p in matches if u.strip()] + pairs.sort(key=lambda x: x[1], reverse=True) + return pairs[:n] + + +def _unit_tag(unit): + return unit.replace("/", "_").replace(" ", "_").replace("%", "pct") + + +def run_ambiguous(parquet, plot_name, details, dump_dir, + dip_threshold=0.05, min_target_n=30, test_mode=False): + os.makedirs(dump_dir, exist_ok=True) + + ambig = plot_name[plot_name["CATEGORY"] == "AMBIGUOUS"].sort_values("COUNT", ascending=False) + if test_mode: + ambig = ambig.head(10) + n_names = len(ambig) + print(f"\nAmbiguous TEST_NAMEs: {n_names}") + + prev_dict = dict(zip(details["TEST_NAME"], details["PREVALENCE_DICT"])) + + rows = [] + + for i, name in enumerate(ambig["TEST_NAME"].tolist(), 1): + tag = name.replace("/", "_").replace(" ", "_") + cand_npy = os.path.join(dump_dir, f"cand_{tag}.npy") + + print(f"\n[{i:>4}/{n_names}] {name}") + + # Candidate values (reuse cache from unambiguous run if present) + if os.path.exists(cand_npy): + c_vals = np.load(cand_npy) + print(f" cand=cache N={len(c_vals):,}") + else: + c_vals = _query_test_values(parquet, name, "candidate") + np.save(cand_npy, c_vals) + print(f" cand=query N={len(c_vals):,}") + + if len(c_vals) < 2: + print(" SKIP: too few candidate values") + continue + + # Filter to units with prevalence > 1% (top 3) + top_units = [(u, p) for u, p in parse_top_units(prev_dict.get(name, ""), n=3) if p > 1.0] + if not top_units: + print(" SKIP: no units with prevalence > 1%") + continue + + # Load & cache target arrays once (applies min_target_n guard) + unit_data = {} # unit -> t_vals + for unit, upct in top_units: + utag = _unit_tag(unit) + targ_npy = os.path.join(dump_dir, f"targ_{tag}_{utag}.npy") + if os.path.exists(targ_npy): + t_vals_u = np.load(targ_npy) + else: + t_vals_u = _query_test_values(parquet, name, "target", unit=unit) + np.save(targ_npy, t_vals_u) + if len(t_vals_u) < min_target_n: + print(f" SKIP unit {unit}({upct:.1f}%): N_TARGET={len(t_vals_u)}<{min_target_n}") + else: + unit_data[unit] = t_vals_u + + if not unit_data: + print(" SKIP: no units with sufficient reference data") + continue + + # Pre-check: run engine on full candidate vs each qualifying unit. + # If any unit already passes, record those results and skip bimodality. + print(f" pre-check (full candidate) units={list(unit_data)}") + precheck = [] # (unit, upct, t_vals, updates, ks_step, t_step, mad_step) + for unit, upct in [(u, p) for u, p in top_units if u in unit_data]: + t_vals_u = unit_data[unit] + upd, ks, t, mad = _run_engine( + c_vals, t_vals_u, + f"{name} [all] [{unit}]", dump_dir, + prevalence=f"{upct:.1f}%", + tag_override=f"{tag}_all_{_unit_tag(unit)}", + ) + precheck.append((unit, upct, t_vals_u, upd, ks, t, mad)) + print(f" [all][{unit}({upct:.1f}%)]" + f" N={len(c_vals):,}/{len(t_vals_u):,}" + f" KS={'P' if ks.passed else 'F'}(stat={ks.details['stat']:.3g})" + f" T={'P' if t.passed else 'F'}" + f" MAD={'P' if mad.passed else 'F'}" + f" → {upd['OUTCOME']}") + + any_precheck_pass = any(upd["OUTCOME"] == "PASS" for _, _, _, upd, *_ in precheck) + + if any_precheck_pass: + print(f" pre-check passed → skipping bimodality split") + for unit, upct, t_vals_u, upd, ks, t, mad in precheck: + rows.append(dict( + TEST_NAME=name, + BIMODAL_STATUS="skipped", + BIMODAL_SEP=np.nan, BIMODAL_BC=np.nan, BIMODAL_DIP_P=np.nan, + SUB_DIST="all", + UNIT=unit, UNIT_PREVALENCE=upct, + PREVALENCE_DICT=prev_dict.get(name, "NA"), + N_CANDIDATE=len(c_vals), N_TARGET=len(t_vals_u), + **upd, + )) + continue + + # No unit passes on the full distribution → bimodal check + bim = injection_engine.bimodal_check(c_vals, dip_threshold=dip_threshold) + injection_engine.plot_bimodal_check(bim, name, dump_dir) + print(f" bimodal={bim.status} sep={bim.separator:.4g}" + f" BC={bim.bc:.3f} dip_p={bim.dip_p:.3g}") + + if bim.status == "unimodal": + # Already ran "all" in pre-check — reuse those results + sub_label = "unimodal" + for unit, upct, t_vals_u, upd, ks, t, mad in precheck: + rows.append(dict( + TEST_NAME=name, + BIMODAL_STATUS=bim.status, + BIMODAL_SEP=bim.separator, BIMODAL_BC=bim.bc, BIMODAL_DIP_P=bim.dip_p, + SUB_DIST="all", + UNIT=unit, UNIT_PREVALENCE=upct, + PREVALENCE_DICT=prev_dict.get(name, "NA"), + N_CANDIDATE=len(c_vals), N_TARGET=len(t_vals_u), + **upd, + )) + else: + sep = bim.separator + low = c_vals[c_vals <= sep] + high = c_vals[c_vals > sep] + sub_dists = [] + if len(low) >= 2: sub_dists.append(("low", low)) + if len(high) >= 2: sub_dists.append(("high", high)) + if not sub_dists: + sub_dists = [("all", c_vals)] + + print(f" sub_dists={[s for s, _ in sub_dists]}") + for sub_name, c_sub in sub_dists: + for unit, upct in [(u, p) for u, p in top_units if u in unit_data]: + t_vals_u = unit_data[unit] + upd, ks, t, mad = _run_engine( + c_sub, t_vals_u, + f"{name} [{sub_name}] [{unit}]", dump_dir, + prevalence=f"{upct:.1f}%", + tag_override=f"{tag}_{sub_name}_{_unit_tag(unit)}", + ) + rows.append(dict( + TEST_NAME=name, + BIMODAL_STATUS=bim.status, + BIMODAL_SEP=bim.separator, BIMODAL_BC=bim.bc, BIMODAL_DIP_P=bim.dip_p, + SUB_DIST=sub_name, + UNIT=unit, UNIT_PREVALENCE=upct, + PREVALENCE_DICT=prev_dict.get(name, "NA"), + N_CANDIDATE=len(c_sub), N_TARGET=len(t_vals_u), + **upd, + )) + print(f" [{sub_name}][{unit}({upct:.1f}%)]" + f" N={len(c_sub):,}/{len(t_vals_u):,}" + f" KS={'P' if ks.passed else 'F'}(stat={ks.details['stat']:.3g})" + f" T={'P' if t.passed else 'F'}" + f" MAD={'P' if mad.passed else 'F'}" + f" → {upd['OUTCOME']}") + + if not rows: + print("No ambiguous results to write.") + return None + + results = pd.DataFrame(rows) + + # Best unit per (TEST_NAME, SUB_DIST): PASS > FAIL > SKIP, then highest prevalence + def _outcome_rank(o): + return {"PASS": 0, "FAIL": 1, "SKIP": 2}.get(o, 2) + + results["_rank"] = results["OUTCOME"].map(_outcome_rank) + best = (results + .sort_values(["_rank", "UNIT_PREVALENCE"], ascending=[True, False]) + .groupby(["TEST_NAME", "SUB_DIST"])["UNIT"] + .first() + .reset_index() + .rename(columns={"UNIT": "BEST_UNIT"})) + results = results.merge(best, on=["TEST_NAME", "SUB_DIST"], how="left") + results = results[results["UNIT"] == results["BEST_UNIT"]].drop(columns=["_rank"]) + + col_order = [ + "TEST_NAME", "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", "SUB_DIST", + "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "BEST_UNIT", + "N_CANDIDATE", "N_TARGET", + "CAND_DECILES", "TARG_DECILES", + "KS_STAT", "KS_MLOGP", "KS_PASS", + "T_STAT", "T_MLOGP", "T_PASS", + "MAD_DIST", "MAD_THRESHOLD", "MAD_PASS", + "OUTCOME", "NOTES", + ] + results = results[col_order] + results.to_csv("ambiguous_results.tsv", sep="\t", index=False, + float_format="%.4g", na_rep="NA") + + _print_ambig_summary(results) + return results + + +def _print_ambig_summary(results): + n_tot = results["TEST_NAME"].nunique() + tested = results[results["OUTCOME"] != "SKIP"] + + best_rows = tested.copy() + + n_pass = (best_rows["OUTCOME"] == "PASS").sum() + n_fail = (best_rows["OUTCOME"] == "FAIL").sum() + n_skip = n_tot - best_rows["TEST_NAME"].nunique() + + print(f"\n{'=' * 72}") + print("AMBIGUOUS INJECTION SUMMARY") + print(f"{'=' * 72}") + print(f" TEST_NAMEs: {n_tot} " + f"PASS={n_pass} FAIL={n_fail} SKIP={n_skip}") + print() + + w = 40 + print(f" {'TEST_NAME':<{w}} {'BIMODAL':<18} {'SUB':<5} {'BEST_UNIT':<14} OUTCOME") + print(f" {'-'*w} {'-'*18} {'-'*5} {'-'*14} -------") + for _, r in best_rows.iterrows(): + print(f" {r['TEST_NAME']:<{w}} {r['BIMODAL_STATUS']:<18} {r['SUB_DIST']:<5}" + f" {r['BEST_UNIT']:<14} {r['OUTCOME']}") + + print(f"\nWrote ambiguous_results.tsv ({len(results)} rows, {n_tot} TEST_NAMEs)") + + +# --------------------------------------------------------------------------- +# Unified output +# --------------------------------------------------------------------------- + +_UNIFIED_COLS = [ + "TYPE", + "TEST_NAME", "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", + "SUB_DIST", "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "BEST_UNIT", + "N_CANDIDATE", "N_TARGET", + "CAND_DECILES", "TARG_DECILES", + "KS_STAT", "KS_MLOGP", "KS_PASS", + "T_STAT", "T_MLOGP", "T_PASS", + "MAD_DIST", "MAD_THRESHOLD", "MAD_PASS", + "OUTCOME", "NOTES", +] + + +def _write_unified(udf, adf): + parts = [] + + if udf is not None and len(udf): + u = udf.copy() + u["TYPE"] = "unambiguous" + u["SUB_DIST"] = "all" + u["BEST_UNIT"] = u["UNIT"] + # Derive UNIT_PREVALENCE from the dominant unit in PREVALENCE_DICT + def _top_pct(row): + pairs = parse_top_units(row["PREVALENCE_DICT"], n=10) + for unit, pct in pairs: + if unit == row["UNIT"]: + return pct + return np.nan + u["UNIT_PREVALENCE"] = u.apply(_top_pct, axis=1) + parts.append(u) + + if adf is not None and len(adf): + a = adf.copy() + a["TYPE"] = "ambiguous" + parts.append(a) + + if not parts: + return + + combined = (pd.concat(parts, ignore_index=True) + .reindex(columns=_UNIFIED_COLS)) + combined.to_csv("injection_results.tsv", sep="\t", index=False, + float_format="%.4g", na_rep="NA") + print(f"\nWrote injection_results.tsv ({len(combined)} rows)") + + +# --------------------------------------------------------------------------- +# Coverage check +# --------------------------------------------------------------------------- + +def _check_coverage(plot_name, udf, adf, no_data): + expected = set(plot_name["TEST_NAME"]) + + covered = set() + for label, df in [("unambiguous", udf), ("ambiguous", adf), ("no_data", no_data)]: + if df is not None and len(df): + names = set(df["TEST_NAME"]) + overlap = covered & names + if overlap: + print(f" COVERAGE ERROR: {len(overlap)} TEST_NAME(s) appear in multiple files: " + f"{sorted(overlap)[:5]}{'...' if len(overlap) > 5 else ''}") + covered |= names + + missing = expected - covered + extra = covered - expected + + print(f"\nCoverage check: {len(expected)} expected " + f"{len(covered)} covered " + f"{len(missing)} missing " + f"{len(extra)} extra") + + if missing: + print(f" MISSING: {sorted(missing)[:10]}{'...' if len(missing) > 10 else ''}") + if extra: + print(f" EXTRA: {sorted(extra)[:10]}{'...' if len(extra) > 10 else ''}") + if not missing and not extra: + print(" OK: all TEST_NAMEs accounted for across 3 output files") + + +# --------------------------------------------------------------------------- +# CLI +# --------------------------------------------------------------------------- + +def build_parser(): + p = argparse.ArgumentParser( + description="Explore unit injection targets in Kanta lab data.", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + p.add_argument("parquet", help="Input parquet file (INJECT.parquet)") + p.add_argument("--min-count", type=int, default=1000, metavar="INT", + help="Minimum no-unit records per TEST_NAME to include") + p.add_argument("--prevalence-threshold", type=float, default=98, metavar="FLOAT", + help="Min top-unit prevalence (%%) for a TEST_NAME to be unambiguous") + p.add_argument("--dump-dir", default="/mnt/disks/data/kanta/inject/tmp/", metavar="PATH", + help="Cache directory for per-test .npy arrays") + p.add_argument("--inject", action="store_true", + help="Run the injection engine on all tests (unambiguous + ambiguous)") + p.add_argument("--dip-threshold", type=float, default=0.05, metavar="FLOAT", + help="Hartigan dip test p-value threshold for bimodality detection") + p.add_argument("--min-target-n", type=int, default=30, metavar="INT", + help="Minimum reference records a unit must have to be tested (ambiguous pass)") + p.add_argument("--test", action="store_true", + help="Limit to a small sample: one per COUNT decile (unambiguous) " + "and top 10 by volume (ambiguous)") + return p + + +def main(): + args = build_parser().parse_args() + + counts = query_counts(args.parquet) + counts = counts[counts["COUNT"] > args.min_count].reset_index(drop=True) + details = query_details(args.parquet) + + plot_name = build_plot_table(counts, details) + plot_name = _add_category(plot_name, args.prevalence_threshold, args.min_target_n) + plot_name.to_csv("plot_name_level.tsv", sep="\t", index=False) + print(f"Built plot_name_level.tsv ({len(plot_name)} rows, " + f"min_count={args.min_count}, threshold={args.prevalence_threshold}%)") + + make_scatter_plot(plot_name) + print_summary(plot_name, args.prevalence_threshold) + dump_summary_md(plot_name, args.prevalence_threshold, args.min_count) + + if args.inject: + udf = run_unambiguous(args.parquet, plot_name, details, args.dump_dir, + test_mode=args.test) + adf = run_ambiguous(args.parquet, plot_name, details, args.dump_dir, + dip_threshold=args.dip_threshold, + min_target_n=args.min_target_n, test_mode=args.test) + _write_unified(udf, adf) + + no_data = plot_name[plot_name["CATEGORY"] == "NO_DATA"][["TEST_NAME"]].copy() + no_data["UNIT"] = "" + no_data.to_csv("no_data_results.tsv", sep="\t", index=False) + print(f"Wrote no_data_results.tsv ({len(no_data)} rows)") + + _check_coverage(plot_name, udf, adf, no_data) + + +if __name__ == "__main__": + main() diff --git a/scripts/injection/explore_test_name.sh b/scripts/injection/explore_test_name.sh deleted file mode 100644 index 02ffc9f..0000000 --- a/scripts/injection/explore_test_name.sh +++ /dev/null @@ -1,163 +0,0 @@ -#!/bin/bash - -F="$1" -MIN_COUNT="$2" - -OUT_COUNTS="test_name_id_counts.tsv" -OUT_DETAILS="test_name_id_details.tsv" -PLOT="test_names_exploration_scatter.png" - -# --- Query 1: TEST_NAME, TEST_ID, COUNT for all pairs with count > threshold --- -if [[ ! -f "$OUT_COUNTS" ]]; then - clickhouse -q " - SELECT - TEST_NAME, - TEST_ID, - count() AS COUNT - FROM file('$F') - WHERE (MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_HARMONIZED IS NOT NULL) - AND MEASUREMENT_UNIT_PRE_FIX IS NULL - GROUP BY TEST_NAME, TEST_ID - HAVING COUNT > $MIN_COUNT - ORDER BY COUNT DESC - FORMAT TSVWithNames - " > "$OUT_COUNTS" - echo "Wrote $OUT_COUNTS" -else - echo "$OUT_COUNTS already exists, skipping." -fi - -# --- Query 2: TEST_NAME, TEST_ID, COUNT, UNIT, PREVALENCE_DICT --- -# Include all TEST_NAMEs present in Query 1 output -if [[ ! -f "$OUT_DETAILS" ]]; then - OUT_COUNTS_ABS="$(realpath "$OUT_COUNTS")" - clickhouse -q " - WITH - global_names AS ( - SELECT DISTINCT TEST_NAME - FROM file('$OUT_COUNTS_ABS', TSVWithNames) - ), - top3_units AS ( - SELECT - TEST_NAME, TEST_ID, - argMax(MEASUREMENT_UNIT_PRE_FIX, unit_cnt) AS UNIT, - concat('{', arrayStringConcat(groupArray(unit_json), ','), '}') AS PREVALENCE_DICT - FROM ( - SELECT TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX, unit_cnt, unit_json - FROM ( - SELECT - TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX, unit_cnt, - ROW_NUMBER() OVER (PARTITION BY TEST_NAME, TEST_ID ORDER BY unit_cnt DESC) AS rn, - concat( - MEASUREMENT_UNIT_PRE_FIX, ':', - toString(round(100.0 * unit_cnt / SUM(unit_cnt) OVER (PARTITION BY TEST_NAME, TEST_ID), 2)) - ) AS unit_json - FROM ( - SELECT TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX, count() AS unit_cnt - FROM file('$F') - WHERE MEASUREMENT_VALUE_MERGED IS NOT NULL - AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL - GROUP BY TEST_NAME, TEST_ID, MEASUREMENT_UNIT_PRE_FIX - ) AS sub - ) AS ranked - WHERE rn <= 3 - ) AS top3 - GROUP BY TEST_NAME, TEST_ID - ), - total_counts AS ( - SELECT TEST_NAME, TEST_ID, count() AS COUNT - FROM file('$F') - WHERE MEASUREMENT_VALUE_MERGED IS NOT NULL - AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL - GROUP BY TEST_NAME, TEST_ID - ) - SELECT - t.TEST_NAME AS TEST_NAME, - t.TEST_ID AS TEST_ID, - t.COUNT AS COUNT, - u.UNIT AS UNIT, - u.PREVALENCE_DICT AS PREVALENCE_DICT - FROM total_counts t - LEFT JOIN top3_units u USING (TEST_NAME, TEST_ID) - INNER JOIN global_names g ON t.TEST_NAME = g.TEST_NAME - ORDER BY t.COUNT DESC - FORMAT TSVWithNames - " > "$OUT_DETAILS" - echo "Wrote $OUT_DETAILS" -else - echo "$OUT_DETAILS already exists, skipping." -fi - -# --- Python: build plotting tables and scatter plots --- -if [[ -f "$PLOT" ]]; then - echo "Plot '$PLOT' already exists, skipping." - exit 0 -fi - -python3 - <<'EOF' -import re -import pandas as pd -import matplotlib.pyplot as plt - -def parse_top_prevalence(d): - if pd.isna(d): - return None - pcts = re.findall(r':(\d+\.?\d*)[,}]', str(d)) - if not pcts: - return None - return max(float(p) for p in pcts) - -counts = pd.read_csv("test_name_id_counts.tsv", sep="\t") -details = pd.read_csv("test_name_id_details.tsv", sep="\t") - -# restrict details to (TEST_NAME, TEST_ID) pairs present in Query 1 -details = details.merge(counts[["TEST_NAME", "TEST_ID"]], on=["TEST_NAME", "TEST_ID"], how="inner") - -# ---- TEST_NAME + TEST_ID level ---- -details["top_prevalence"] = details["PREVALENCE_DICT"].apply(parse_top_prevalence) - -plot_name_id = counts.merge( - details[["TEST_NAME", "TEST_ID", "top_prevalence"]], - on=["TEST_NAME", "TEST_ID"], how="left" -) -plot_name_id["has_unit_data"] = plot_name_id["top_prevalence"].notna() -plot_name_id["top_prevalence"] = plot_name_id["top_prevalence"].fillna(0) -plot_name_id.to_csv("plot_name_id_level.tsv", sep="\t", index=False) -print(f"Built plot_name_id_level.tsv ({len(plot_name_id)} rows)") - -# ---- TEST_NAME level (COUNT-weighted mean over rows WITH unit data only) ---- -def weighted_prevalence(d): - valid = d[d["has_unit_data"]] - if valid.empty: - return 0.0 - return (valid["top_prevalence"] * valid["COUNT"]).sum() / valid["COUNT"].sum() - -g = plot_name_id.groupby("TEST_NAME") -plot_name = pd.DataFrame({ - "total_count": g["COUNT"].sum(), - "top_prevalence": g.apply(weighted_prevalence), -}).reset_index() -plot_name.to_csv("plot_name_level.tsv", sep="\t", index=False) -print(f"Built plot_name_level.tsv ({len(plot_name)} rows)") - -# ---- Scatter plots ---- -fig, axes = plt.subplots(1, 2, figsize=(18, 7)) - -ax1 = axes[0] -ax1.scatter(plot_name_id["COUNT"], plot_name_id["top_prevalence"], alpha=0.5, s=20) -ax1.set_xlabel("Count (value, no unit)") -ax1.set_ylabel("Top unit prevalence (%)") -ax1.set_title("TEST_NAME + TEST_ID level") -ax1.set_xscale("log") - -ax2 = axes[1] -ax2.scatter(plot_name["total_count"], plot_name["top_prevalence"], alpha=0.5, s=20) -ax2.set_xlabel("Total count (value, no unit)") -ax2.set_ylabel("Weighted top unit prevalence (%)") -ax2.set_title("TEST_NAME level") -ax2.set_xscale("log") - -plt.tight_layout() -plt.savefig("test_names_exploration_scatter.png", dpi=150) -print("Saved test_names_exploration_scatter.png") -EOF diff --git a/scripts/injection/injection_engine.py b/scripts/injection/injection_engine.py new file mode 100644 index 0000000..215311f --- /dev/null +++ b/scripts/injection/injection_engine.py @@ -0,0 +1,661 @@ +#!/usr/bin/env python3 +""" +injection_engine.py + +Tests whether a candidate value distribution is compatible with a target +(reference) distribution for unit injection. + +Pipeline +-------- +1. KS test : stat < ks_threshold AND p < sig_level → PASS + (small effect size + sufficient data to trust the assessment) +2. Welch t : runs when KS fails; p ≥ sig_level (not significantly different) → PASS +3. MAD : last resort — |median(candidate) − median(target)| ≤ n_mad × MAD(target) → PASS + → FAIL + +All three tests always run (for reporting); decision order is KS → T → MAD. + +Usage +----- + injection_engine.py CANDIDATE TARGET [options] + injection_engine.py --test-mode [options] +""" + +import argparse +import os +import sys +from dataclasses import dataclass, field + +import matplotlib +matplotlib.use("Agg") +import matplotlib.pyplot as plt +import numpy as np +from scipy import stats +from scipy.special import kolmogorov as _kolmogorov + +try: + from sklearn.mixture import GaussianMixture as _GaussianMixture + _GMM_AVAILABLE = True +except ImportError: + _GMM_AVAILABLE = False + + +# --------------------------------------------------------------------------- +# Result types +# --------------------------------------------------------------------------- + +def _fmt(v): + if not isinstance(v, float): + return str(v) + if v == 0.0 or abs(v) < 1e-3 or abs(v) >= 1e5: + return f"{v:.4e}" + return f"{v:.4f}" + + +@dataclass +class StepResult: + name: str + passed: bool + details: dict = field(default_factory=dict) # raw values (floats/ints) + + def __str__(self): + kv = " ".join(f"{k}={_fmt(v)}" for k, v in self.details.items()) + return f"[{self.name:<4}] {'PASS' if self.passed else 'FAIL'} {kv}" + + +@dataclass +class PipelineResult: + outcome: str # "PASS" or "FAIL" + decided_by: str # "KS", "T", or "MAD" + steps: list = field(default_factory=list) + + def __str__(self): + lines = [f"Outcome : {self.outcome} (decided by {self.decided_by})"] + for s in self.steps: + lines.append(f" {s}") + return "\n".join(lines) + + +# --------------------------------------------------------------------------- +# Individual tests +# --------------------------------------------------------------------------- + +_BINNED_KS_N = 500_000 # switch to binned approximation above this size + + +def _binned_ks(data1, data2, bins=100_000): + """ + Fast approximate two-sample KS test via histograms. + + Stat approximation error ≤ 1/bins ≈ 1e-5 (negligible vs threshold 0.3). + P-value uses the Hodges-corrected asymptotic Kolmogorov distribution, + identical to scipy ks_2samp(method='asymp'). + """ + n1, n2 = len(data1), len(data2) + lo = min(data1.min(), data2.min()) + hi = max(data1.max(), data2.max()) + + if lo == hi: # all values identical — distributions are the same + return 0.0, 1.0 + + hist1, _ = np.histogram(data1, bins=bins, range=(lo, hi)) + hist2, _ = np.histogram(data2, bins=bins, range=(lo, hi)) + + ecdf1 = np.cumsum(hist1) / n1 + ecdf2 = np.cumsum(hist2) / n2 + + stat = float(np.max(np.abs(ecdf1 - ecdf2))) + + # Hodges (1958) correction — matches scipy's asymptotic formula exactly + en = np.sqrt(n1 * n2 / (n1 + n2)) + pval = float(np.clip(_kolmogorov((en + 0.12 + 0.11 / en) * stat), 0.0, 1.0)) + + return stat, pval + + +def _ks(candidate, target, ks_threshold, sig_level): + if max(len(candidate), len(target)) > _BINNED_KS_N: + stat, pval = _binned_ks(candidate, target) + method = "binned" + else: + stat, pval = stats.ks_2samp(candidate, target) + method = "exact" + passed = (stat < ks_threshold) and (pval < sig_level) + return StepResult("KS", passed, { + "stat": float(stat), + "ks_threshold": ks_threshold, + "pval": float(pval), + "sig_level": sig_level, + "method": method, + }) + + +def _t(candidate, target, sig_level): + stat, pval = stats.ttest_ind(candidate, target, equal_var=False) + passed = pval >= sig_level # PASS = means NOT significantly different → proceed to MAD + return StepResult("T", passed, { + "stat": float(stat), + "pval": float(pval), + "sig_level": sig_level, + }) + + +def _mad(candidate, target, n_mad): + t_median = np.median(target) + t_mad = float(stats.median_abs_deviation(target)) + c_median = np.median(candidate) + distance = abs(float(c_median) - float(t_median)) + threshold = n_mad * t_mad + return StepResult("MAD", distance <= threshold, { + "cand_median": float(c_median), + "target_median": float(t_median), + "MAD": t_mad, + "distance": distance, + "threshold": threshold, + "n_mad": n_mad, + }) + + +# --------------------------------------------------------------------------- +# Bimodal check +# --------------------------------------------------------------------------- + +@dataclass +class BimodalResult: + status: str # "unimodal" | "bimodal" | "bimodal_cautious" + separator: float # split point in original space (nan if unimodal) + bc: float + dip_p: float + lognormal: bool # which space had lower BIC + fit: dict # raw GMM output (empty dict if unavailable) + + def __str__(self): + return (f"[BIMODAL] {self.status} sep={self.separator:.4g}" + f" BC={self.bc:.3f} dip_p={self.dip_p:.3g}" + f" space={'log' if self.lognormal else 'linear'}") + + +def _bimodality_coefficient(arr): + n = len(arr) + g = float(stats.skew(arr)) + k = float(stats.kurtosis(arr, fisher=True)) + if n > 3: + return (g**2 + 1) / (k + 3.0 * (n - 1)**2 / ((n - 2) * (n - 3))) + return np.nan + + +def _gmm_fit(arr, lognormal): + if not _GMM_AVAILABLE: + return None + if lognormal: + pos = arr[arr > 0] + if len(pos) < 10: + return None + x = np.log(pos) + else: + x = arr + pos = arr + try: + gmm = _GaussianMixture(n_components=2, random_state=0, max_iter=300) + gmm.fit(x.reshape(-1, 1)) + except Exception: + return None + means = gmm.means_.flatten() + sigmas = np.sqrt(gmm.covariances_).flatten() + weights = gmm.weights_ + + # Separator: grid search between the two means + linear interpolation. + # fsolve is avoided because it can diverge badly with a poor starting point. + lo_m, hi_m = float(np.min(means)), float(np.max(means)) + span = max(hi_m - lo_m, 1e-10) + grid = np.linspace(lo_m - 0.1 * span, hi_m + 0.1 * span, 2000) + diff = (weights[0] * stats.norm.pdf(grid, means[0], sigmas[0]) + - weights[1] * stats.norm.pdf(grid, means[1], sigmas[1])) + inner = (grid >= lo_m) & (grid <= hi_m) + g_in, d_in = grid[inner], diff[inner] + cx = np.where(np.diff(np.sign(d_in)))[0] + if len(cx) > 0: + i = cx[0] + x0, x1, d0, d1 = g_in[i], g_in[i + 1], d_in[i], d_in[i + 1] + sep_native = float(x0 - d0 * (x1 - x0) / (d1 - d0)) + else: + sep_native = float(np.mean(means)) + return dict( + separator=float(np.exp(sep_native)) if lognormal else float(sep_native), + sep_native=sep_native, + means_native=means, sigmas_native=sigmas, weights=weights, + bic=float(gmm.bic(x.reshape(-1, 1))), + bc=float(_bimodality_coefficient(x)), + lognormal=lognormal, + x_fit=x, x_orig=pos, + ) + + +_BIMODAL_MAX_N = 50_000 # dip test is unreliable above 72k; GMM also faster + + +def bimodal_check(arr, dip_threshold=0.05, bc_threshold=0.555): + """ + Classify a distribution as unimodal / bimodal / bimodal_cautious. + + Decision logic: + - dip p >= dip_threshold → unimodal + - dip p < dip_threshold, BC >= bc_threshold → bimodal + - dip p < dip_threshold, BC < bc_threshold → bimodal_cautious (overlap) + - dip unavailable: fall back to BC alone + """ + arr = np.asarray(arr, dtype=float) + arr = arr[np.isfinite(arr)] + + if len(arr) > _BIMODAL_MAX_N: + rng = np.random.default_rng(42) + arr = arr[rng.choice(len(arr), size=_BIMODAL_MAX_N, replace=False)] + + fit_norm = _gmm_fit(arr, lognormal=False) + fit_log = _gmm_fit(arr, lognormal=True) + fits = [f for f in (fit_norm, fit_log) if f is not None] + + if not fits: + return BimodalResult("unimodal", np.nan, np.nan, np.nan, False, {}) + + best = min(fits, key=lambda f: f["bic"]) + + # Dip test in the same space as the best GMM fit (log or linear) + dip_p = np.nan + try: + from diptest import diptest + _, dip_p = diptest(best["x_fit"]) + dip_p = float(dip_p) + except ImportError: + pass + bc = best["bc"] + sep = best["separator"] + + if not np.isnan(dip_p): + if dip_p >= dip_threshold: + status = "unimodal" + else: + status = "bimodal" if bc >= bc_threshold else "bimodal_cautious" + else: + status = "bimodal" if bc >= bc_threshold else "unimodal" + + return BimodalResult(status, sep, bc, dip_p, best["lognormal"], best) + + +def plot_bimodal_check(result, name, dump_dir): + """ + Save bimodal diagnostic to dump_dir/bimodal_{tag}.png. + Uses the subsampled arrays stored in result.fit; no-op only if GMM failed. + """ + if not result.fit: + return + tag = name.replace("/", "_").replace(" ", "_") + out_path = os.path.join(dump_dir, f"bimodal_{tag}.png") + if os.path.exists(out_path): + return + + fit = result.fit + means_n, sigmas_n, weights_n = fit["means_native"], fit["sigmas_native"], fit["weights"] + x_orig = fit["x_orig"] # positive values in original space + x_fit = fit["x_fit"] # values in fitted space (log or linear) + + fig, axes = plt.subplots(1, 2, figsize=(12, 4)) + fig.suptitle( + f"{name} — {result.status} sep={result.separator:.4g}" + f" BC={result.bc:.3f} dip_p={result.dip_p:.3g}" + f" space={'log' if result.lognormal else 'linear'}", + fontsize=10, fontweight="bold", + ) + + # Panel 1: original space + ax = axes[0] + lo, hi = np.percentile(x_orig, [0.5, 99.5]) + ax.hist(x_orig, bins=60, density=True, alpha=0.45, color="steelblue", range=(lo, hi)) + xlin = np.linspace(lo, hi, 400) + for m, s, w in zip(means_n, sigmas_n, weights_n): + if fit["lognormal"]: + safe = np.clip(xlin, 1e-10, None) + ax.plot(xlin, w * stats.norm.pdf(np.log(safe), m, s) / safe, alpha=0.8) + else: + ax.plot(xlin, w * stats.norm.pdf(xlin, m, s), alpha=0.8) + if not np.isnan(result.separator): + ax.axvline(result.separator, color="red", ls="--", + label=f"sep={result.separator:.3g}") + ax.set_xlabel("value"); ax.set_title("Original space"); ax.legend(fontsize=8) + + # Panel 2: fitted space (log or linear) + ax = axes[1] + lo_f, hi_f = np.percentile(x_fit, [0.5, 99.5]) + ax.hist(x_fit, bins=60, density=True, alpha=0.45, color="steelblue", range=(lo_f, hi_f)) + xf = np.linspace(lo_f, hi_f, 400) + for m, s, w in zip(means_n, sigmas_n, weights_n): + ax.plot(xf, w * stats.norm.pdf(xf, m, s), alpha=0.8) + if not np.isnan(fit["sep_native"]): + ax.axvline(fit["sep_native"], color="red", ls="--", + label=f"sep={fit['sep_native']:.3g}") + space_label = "log(value)" if fit["lognormal"] else "value" + ax.set_xlabel(space_label) + ax.set_title(f"Fitted space ({'log' if fit['lognormal'] else 'linear'})") + ax.legend(fontsize=8) + + plt.tight_layout() + plt.savefig(out_path, dpi=120, bbox_inches="tight") + plt.close(fig) + + +# --------------------------------------------------------------------------- +# Pipeline +# --------------------------------------------------------------------------- + +def run_pipeline(candidate, target, ks_threshold=0.3, sig_level=0.05, n_mad=3.0): + """ + Run the injection compatibility pipeline. + Returns a PipelineResult with outcome ("PASS"/"FAIL") and per-step details. + details dicts contain raw floats, suitable for direct programmatic access. + """ + ks = _ks(candidate, target, ks_threshold, sig_level) + t = _t(candidate, target, sig_level) + mad = _mad(candidate, target, n_mad) + steps = [ks, t, mad] + + if ks.passed: + decided_by, outcome = "KS", "PASS" + elif t.passed: + decided_by, outcome = "T", "PASS" + else: + decided_by = "MAD" + outcome = "PASS" if mad.passed else "FAIL" + + return PipelineResult(outcome, decided_by, steps) + + +# --------------------------------------------------------------------------- +# Test generation +# --------------------------------------------------------------------------- + +def _generate_test_cases(n=1000, seed=42): + """ + Synthetic cases designed to exercise each outcome in the pipeline. + + Expected results with default thresholds (ks=0.3, sig=0.05, n_mad=3): + + pass_ks → PASS via KS : N(0.3,1) vs N(0,1) — small stat (~0.12), p << 0.05 + fail_all → FAIL via MAD : N(5,1) vs N(0,1) — different means, median also far + pass_T → PASS via T : N(0,0.1) vs N(0,1) — different shape, same mean (T gates before MAD) + pass_T2 → PASS via T : lognormal(0,σ=2) shifted to mean=0 vs N(0,1) + mean=0 by construction so T passes; MAD would fail (median≈−6.4) + """ + rng = np.random.default_rng(seed) + target = rng.normal(0.0, 1.0, n) + + c_pass_ks = rng.normal(0.3, 1.0, n) + c_fail_t = rng.normal(5.0, 1.0, n) + c_pass_mad = rng.normal(0.0, 0.1, n) + + # lognormal(μ=0, σ=2): E[X] = e^2 ≈ 7.39, median = 1 + # subtract mean → mean=0, median = 1 − e^2 ≈ −6.39 + c_fail_mad = rng.lognormal(mean=0.0, sigma=2.0, size=n) - np.exp(2.0) + + return [ + ("pass_ks [expect: PASS via KS ]", c_pass_ks, target), + ("fail_all [expect: FAIL via MAD]", c_fail_t, target), + ("pass_T [expect: PASS via T ]", c_pass_mad, target), + ("pass_T2 [expect: PASS via T ]", c_fail_mad, target), + ] + + +# --------------------------------------------------------------------------- +# I/O +# --------------------------------------------------------------------------- + +def _load_values(path): + """Load a 1-D float array from a .npy file or a text/TSV file.""" + if path.endswith(".npy"): + return np.load(path) + values = [] + with open(path) as f: + for line in f: + line = line.strip() + if line: + values.append(float(line.split("\t")[0])) + return np.array(values) + + +# --------------------------------------------------------------------------- +# Diagnostics plot +# --------------------------------------------------------------------------- + +def _ecdf(arr): + x = np.sort(arr) + y = np.arange(1, len(x) + 1) / len(x) + return x, y + + +def _kde(ax, arr, label, color): + if len(arr) < 2 or np.std(arr) == 0: + return + kde = stats.gaussian_kde(arr) + xs = np.linspace(arr.min(), arr.max(), 400) + ys = kde(xs) + ax.plot(xs, ys, color=color, label=label, alpha=0.85) + ax.fill_between(xs, ys, color=color, alpha=0.15) + + +_PLOT_MAX_N = 50_000 # downsample to this many points for KDE/ECDF plots only + + +def _plot_sample(arr, rng): + if len(arr) > _PLOT_MAX_N: + return arr[np.sort(rng.choice(len(arr), size=_PLOT_MAX_N, replace=False))] + return arr + + +def plot_result(candidate, target, result, name, dump_dir, prevalence=None, + tag_override=None): + """ + Save a 3-panel diagnostic figure to dump_dir/plot_.png. + Skips if the file already exists. + + Panels + ------ + 1. Empirical CDFs with KS distance marked + 2. KDE in linear scale + t-test statistics + 3. KDE in log scale + MAD statistics + """ + if tag_override: + tag = tag_override + else: + tag = name.replace("/", "_").replace(" ", "_") + out_path = os.path.join(dump_dir, f"plot_{tag}.png") + if os.path.exists(out_path): + return + + rng = np.random.default_rng(42) + c_plot = _plot_sample(candidate, rng) + t_plot = _plot_sample(target, rng) + sampled = len(candidate) > _PLOT_MAX_N or len(target) > _PLOT_MAX_N + + ks_step = next((s for s in result.steps if s.name == "KS"), None) + t_step = next((s for s in result.steps if s.name == "T"), None) + mad_step = next((s for s in result.steps if s.name == "MAD"), None) + + fig, axes = plt.subplots(1, 3, figsize=(18, 5)) + sample_note = f" [plot: {_PLOT_MAX_N:,} sampled]" if sampled else "" + prev_note = f"\n{prevalence}" if prevalence and str(prevalence) not in ("NA", "nan") else "" + fig.suptitle(f"{name} — {result.outcome} at {result.decided_by}{sample_note}{prev_note}", + fontsize=11, fontweight="bold") + + _TXT = dict(transform=None, va="top", fontsize=9, + bbox=dict(boxstyle="round", facecolor="lightyellow", alpha=0.8)) + _TXT_GREY = dict(transform=None, va="top", fontsize=9, + bbox=dict(boxstyle="round", facecolor="lightgrey", alpha=0.6)) + + # ---- Panel 1: ECDFs + KS ---------------------------------------- + ax = axes[0] + cx, cy = _ecdf(c_plot) + tx, ty = _ecdf(t_plot) + ax.step(cx, cy, where="post", color="steelblue", label="candidate", alpha=0.85) + ax.step(tx, ty, where="post", color="darkorange", label="target", alpha=0.85) + + if ks_step: + d = ks_step.details + stat = d["stat"] + pval = d["pval"] + all_x = np.sort(np.unique(np.concatenate([cx, tx]))) + c_cdf = np.searchsorted(cx, all_x, side="right") / len(cx) + t_cdf = np.searchsorted(tx, all_x, side="right") / len(tx) + i_max = np.argmax(np.abs(c_cdf - t_cdf)) + x_ks = all_x[i_max] + y_lo, y_hi = sorted([c_cdf[i_max], t_cdf[i_max]]) + ax.plot([x_ks, x_ks], [y_lo, y_hi], color="red", lw=2.5, label=f"D = {stat:.4f}") + mlogp = -np.log10(np.clip(pval, 1e-300, 1.0)) + kw = {**_TXT, "transform": ax.transAxes} + ax.text(0.04, 0.96, + f"KS stat = {stat:.3g}\n-log10p = {mlogp:.1f}\n→ {'PASS' if ks_step.passed else 'FAIL'}", + **kw) + + ax.set_xlabel("value") + ax.set_ylabel("cumulative probability") + ax.set_title("Empirical CDFs") + ax.legend(fontsize=8) + + # ---- Panel 2: KDE linear + t-test ---------------------------------- + ax = axes[1] + _kde(ax, c_plot, "_nolegend_", "steelblue") + _kde(ax, t_plot, "_nolegend_", "darkorange") + c_mean = float(np.mean(c_plot)) + t_mean = float(np.mean(t_plot)) + ax.axvline(c_mean, color="steelblue", ls=":", lw=1.5, alpha=0.9, label=f"{c_mean:.3g}") + ax.axvline(t_mean, color="darkorange", ls=":", lw=1.5, alpha=0.9, label=f"{t_mean:.3g}") + + if t_step: + d = t_step.details + mlogp = -np.log10(np.clip(d["pval"], 1e-300, 1.0)) + kw = {**_TXT, "transform": ax.transAxes} + ax.text(0.04, 0.96, + f"t = {d['stat']:.3g}\n-log10p = {mlogp:.1f}\n→ {'PASS' if t_step.passed else 'FAIL'}", + **kw) + else: + kw = {**_TXT_GREY, "transform": ax.transAxes} + ax.text(0.04, 0.96, "t-test\nnot reached", **kw) + + ax.set_xlabel("value") + ax.set_ylabel("density") + ax.set_title("Distributions — linear scale") + ax.legend(fontsize=8) + + # ---- Panel 3: KDE log + MAD ---------------------------------------- + ax = axes[2] + c_pos = c_plot[c_plot > 0] + t_pos = t_plot[t_plot > 0] + + if mad_step: + d = mad_step.details + c_med = d["cand_median"] + t_med = d["target_median"] + thr = d["threshold"] + + lo = t_med - thr + hi = t_med + thr + all_pos = np.concatenate([c_pos, t_pos]) if len(c_pos) and len(t_pos) else np.array([1e-6]) + lo_log = np.log(lo) if lo > 0 else np.log(all_pos.min()) - 1 + hi_log = np.log(hi) if hi > 0 else np.log(all_pos.max()) + 1 + band_color = "limegreen" if mad_step.passed else "salmon" + ax.axvspan(lo_log, hi_log, alpha=0.18, color=band_color, + label=f"±{d['n_mad']:.0f}×MAD", zorder=0) + + if len(c_pos) > 1: + _kde(ax, np.log(c_pos), "_nolegend_", "steelblue") + if len(t_pos) > 1: + _kde(ax, np.log(t_pos), "_nolegend_", "darkorange") + + if mad_step: + lc = np.log(c_med) if c_med > 0 else None + lt = np.log(t_med) if t_med > 0 else None + if lc is not None: + ax.axvline(lc, color="steelblue", ls=":", lw=1.5, alpha=0.9, + label=f"{c_med:.3g}") + if lt is not None: + ax.axvline(lt, color="darkorange", ls=":", lw=1.5, alpha=0.9, + label=f"{t_med:.3g}") + if lc is not None and lt is not None: + ax.annotate("", xy=(lc, 0), xytext=(lt, 0), + arrowprops=dict(arrowstyle="<->", color="grey", lw=1.5), + annotation_clip=False) + ax.text((lc + lt) / 2, 0, f" {d['distance']:.3g}", + fontsize=7, va="bottom", color="grey") + kw = {**_TXT, "transform": ax.transAxes} + ax.text(0.04, 0.96, + f"MAD = {d['MAD']:.3g}\ndist = {d['distance']:.3g}\nthr = {d['threshold']:.3g}\n" + f"→ {'PASS' if mad_step.passed else 'FAIL'}", + **kw) + else: + kw = {**_TXT_GREY, "transform": ax.transAxes} + ax.text(0.04, 0.96, "MAD test\nnot reached", **kw) + + ax.set_xlabel("log(value)") + ax.set_ylabel("density") + ax.set_title("Distributions — log scale") + ax.legend(fontsize=8) + + plt.tight_layout() + plt.savefig(out_path, dpi=120, bbox_inches="tight") + plt.close(fig) + + +# --------------------------------------------------------------------------- +# CLI +# --------------------------------------------------------------------------- + +def _build_parser(): + p = argparse.ArgumentParser( + description="Test whether a candidate distribution is compatible with a target for unit injection.", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + p.add_argument("candidate", nargs="?", + help="File with candidate values (.npy, one float per line, or first TSV column)") + p.add_argument("target", nargs="?", + help="File with target (reference) values") + p.add_argument("--ks-threshold", type=float, default=0.3, metavar="FLOAT", + help="KS statistic must be below this for KS PASS") + p.add_argument("--sig-level", type=float, default=0.05, metavar="FLOAT", + help="Significance level for KS p-value and Welch t-test") + p.add_argument("--n-mad", type=float, default=3.0, metavar="FLOAT", + help="Candidate median must lie within this many MADs of the target median") + p.add_argument("--test-mode", action="store_true", + help="Run synthetic test cases designed to fail at each pipeline step") + p.add_argument("--quiet", action="store_true", + help="Print only the final PASS/FAIL outcome") + return p + + +def main(): + args = _build_parser().parse_args() + + if args.test_mode: + cases = _generate_test_cases() + for label, candidate, target in cases: + result = run_pipeline(candidate, target, args.ks_threshold, args.sig_level, args.n_mad) + print(f"\n{'─' * 64}") + print(f"Case : {label}") + print(result) + print() + return + + if not args.candidate or not args.target: + _build_parser().error("provide CANDIDATE and TARGET files, or use --test-mode") + + candidate = _load_values(args.candidate) + target = _load_values(args.target) + result = run_pipeline(candidate, target, args.ks_threshold, args.sig_level, args.n_mad) + + if args.quiet: + print(result.outcome) + else: + print(result) + + sys.exit(0 if result.outcome == "PASS" else 1) + + +if __name__ == "__main__": + main() diff --git a/scripts/injection/injection_extraction.sh b/scripts/injection/injection_extraction.sh deleted file mode 100644 index 5ff14da..0000000 --- a/scripts/injection/injection_extraction.sh +++ /dev/null @@ -1,87 +0,0 @@ -#!/bin/bash -set -e - -# === CONFIGURE PATHS === -BASE_DIR="/mnt/disks/data/kanta/test" -PARQUET_DATA="$BASE_DIR/kanta_v3_harmonized_2026_03_06_formatted.parquet" -PARQUET_TESTS="$BASE_DIR/finngen_R14_kanta_lab_1.0_extended_columns.parquet" - -OUT_CF_COUNTS="$BASE_DIR/omop_convfactor_counts.tsv" -OUT_AMBIGUOUS="$BASE_DIR/ambiguous_omop_cf_ids_sorted.txt" -OUT_TEST_COUNTS="$BASE_DIR/testname_omopid_count_sorted.tsv" -OUT_INJECTION="$BASE_DIR/injection_candidates.txt" - -echo "FETCH AMBIGUOUS IDS/CONVERSION FACTORS" -clickhouse -q " -SELECT - OMOP_CONCEPT_ID, - CONVERSION_FACTOR, - count() AS cnt -FROM file('$PARQUET_DATA', 'Parquet') -WHERE MEASUREMENT_UNIT_CLEANED IS NOT NULL - AND MEASUREMENT_VALUE_HARMONIZED IS NOT NULL - AND CONVERSION_FACTOR IS NOT NULL -GROUP BY OMOP_CONCEPT_ID, CONVERSION_FACTOR -ORDER BY OMOP_CONCEPT_ID, cnt DESC -" --format=TabSeparated > "$OUT_CF_COUNTS" -wc "$OUT_CF_COUNTS" -head "$OUT_CF_COUNTS" - -echo "BUILD AMBIGUOUSNESS TABLE BASED ON CONVERSION FACTOR PREVALENCE > 5% (INCLUDE TOTAL COUNT)" -python3 -c " -from collections import defaultdict -d, t = defaultdict(list), defaultdict(int) -with open('$OUT_CF_COUNTS') as f: - for l in f: - omop, cf, cnt = l.rstrip().split('\t') - cnt = int(cnt) - d[omop].append((cf, cnt)) - t[omop] += cnt -for omop in sorted(d, key=int): - shares = {cf: round(c / t[omop], 2) for cf, c in d[omop]} - threshold = 0.05 - ambiguous = 1 if len(shares) > 1 and sorted(shares.values(), reverse=True)[1] > threshold else 0 - total = t[omop] - print(f'{omop}\t' + '{' + ','.join(f'\"{cf}\":{v}' for cf, v in shares.items()) + f'}}\t{ambiguous}\t{total}') -" | sort > "$OUT_AMBIGUOUS" -head "$OUT_AMBIGUOUS" -wc "$OUT_AMBIGUOUS" - -echo "GET ALL EXTRACTED TESTS COUNTS" -clickhouse -q " -SELECT - TEST_NAME, - OMOP_CONCEPT_ID, - count() AS COUNT -FROM file('$PARQUET_TESTS', 'Parquet') -WHERE MEASUREMENT_VALUE_EXTRACTED IS NOT NULL -GROUP BY TEST_NAME, OMOP_CONCEPT_ID -ORDER BY COUNT DESC -" --format=TabSeparated | sort -k2,2 > "$OUT_TEST_COUNTS" - -wc "$OUT_TEST_COUNTS" -head "$OUT_TEST_COUNTS" - - -echo "JOIN AND FILL MISSING" -join -t $'\t' -1 2 -2 1 -a 1 "$OUT_TEST_COUNTS" "$OUT_AMBIGUOUS" \ -| sort -grk3 \ -| awk -F'\t' -v OFS='\t' '{for(i=1;i<=5;i++) if($i=="") $i=0; print $1,$2,$3,$4,$5}' > "$OUT_INJECTION" - -echo "SAMPLE JOINT OUTPUT" -head "$OUT_INJECTION" -wc "$OUT_INJECTION" - -echo "SUM & RELATIVE FRACTION OF PROBLEMATIC VS UNPROBLEMATIC (BY COLUMN 5)" - -awk -F'\t' ' -{ - # $3 = count, $5 = ambiguous flag - if ($5==1) prob+=$3; else nonprob+=$3 -} -END { - total = prob + nonprob; - printf "Problematic: %d (%.2f%%)\n", prob, (prob/total*100); - printf "Non-problematic: %d (%.2f%%)\n", nonprob, (nonprob/total*100); -} -' "$OUT_INJECTION" diff --git a/scripts/injection/parquet/run.sh b/scripts/injection/parquet/run.sh deleted file mode 100644 index 7e79ddf..0000000 --- a/scripts/injection/parquet/run.sh +++ /dev/null @@ -1,11 +0,0 @@ -INPUT_FILE="/home/pete/fg-3/kanta_v3/core/kanta_dev_2026_03_09.txt.gz" -TXT_GZ_FILE="INJECT.txt.gz" -TXT_QUERY="/home/pete/Dropbox/Projects/kanta_lab_preprocessing/scripts/injection/parquet/make_tsv_gzipped.sql" - - -clickhouse --param_filePathMungedTxtGz $INPUT_FILE --param_outputFile $TXT_GZ_FILE --queries-file $TXT_QUERY | gzip -c > $TXT_GZ_FILE - - -PARQ="INJECT.parquet" -PARQ_QUERY="/home/pete/Dropbox/Projects/kanta_lab_preprocessing/scripts/injection/parquet/make_parquet.sql" - clickhouse --param_filePathCleanTxtGz "$TXT_GZ_FILE" --queries-file $PARQ_QUERY > $PARQ diff --git a/scripts/injection/plot_exploration.py b/scripts/injection/plot_exploration.py new file mode 100644 index 0000000..593e08a --- /dev/null +++ b/scripts/injection/plot_exploration.py @@ -0,0 +1,66 @@ +#!/usr/bin/env python3 +""" +plot_exploration.py + +Scatter plot for unit injection exploration (TEST_NAME level). + +Importable: call make_scatter_plot(plot_name). +Standalone: reads plot_name_level.tsv from the current directory. +""" + +import argparse +from pathlib import Path + +import matplotlib.pyplot as plt +import numpy as np +import pandas as pd +from matplotlib.gridspec import GridSpec +from scipy.stats import gaussian_kde + +DEFAULT_OUTPUT = "test_names_exploration_scatter.png" + + +def make_scatter_plot(plot_name, output=DEFAULT_OUTPUT): + fig = plt.figure(figsize=(11, 7)) + gs = GridSpec(1, 2, width_ratios=[4, 1], wspace=0.05) + ax_scatter = fig.add_subplot(gs[0]) + ax_kde = fig.add_subplot(gs[1], sharey=ax_scatter) + + ax_scatter.scatter(plot_name["COUNT"], plot_name["top_prevalence"], + alpha=0.5, s=20) + ax_scatter.set_xlabel("Count (value, no unit)") + ax_scatter.set_ylabel("Top unit prevalence (%)") + ax_scatter.set_title("TEST_NAME level — injection candidates") + ax_scatter.set_xscale("log") + + prev = plot_name["top_prevalence"].dropna().values + ys = np.linspace(prev.min(), prev.max(), 500) + kde = gaussian_kde(prev, bw_method="scott") + ax_kde.fill_betweenx(ys, kde(ys), alpha=0.4, color="steelblue") + ax_kde.plot(kde(ys), ys, color="steelblue", lw=1.2) + ax_kde.set_xlabel("density") + ax_kde.tick_params(labelleft=False) + ax_kde.set_xlim(left=0) + + plt.savefig(output, dpi=150, bbox_inches="tight") + print(f"Saved {output}") + + +def main(): + p = argparse.ArgumentParser( + description="Generate exploration scatter plot from plot_name_level.tsv.", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + p.add_argument("--tsv", default="plot_name_level.tsv") + p.add_argument("--output", default=DEFAULT_OUTPUT) + p.add_argument("--force", action="store_true", help="Overwrite existing plot") + args = p.parse_args() + + if args.force: + Path(args.output).unlink(missing_ok=True) + + make_scatter_plot(pd.read_csv(args.tsv, sep="\t"), output=args.output) + + +if __name__ == "__main__": + main() From 2dc030195329f935950d4922d5967529c3a8a7d1 Mon Sep 17 00:00:00 2001 From: pete Date: Tue, 26 May 2026 16:11:54 +0300 Subject: [PATCH 04/20] README update --- scripts/injection/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/injection/README.md b/scripts/injection/README.md index 4364d75..54eab6a 100644 --- a/scripts/injection/README.md +++ b/scripts/injection/README.md @@ -4,7 +4,7 @@ The goal is to identify lab measurements that have a numeric value but are missi ## Summary -![scatter](test_names_exploration_scatter.png) +![scatter](/mnt/disks/data/kanta/inject/test_names_exploration_scatter.png) *Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements* From 8da46cdc1bad7400987ab767844fd406f48f7c10 Mon Sep 17 00:00:00 2001 From: pete Date: Tue, 26 May 2026 16:12:54 +0300 Subject: [PATCH 05/20] README update --- scripts/injection/README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/scripts/injection/README.md b/scripts/injection/README.md index 54eab6a..5ce02d5 100644 --- a/scripts/injection/README.md +++ b/scripts/injection/README.md @@ -4,7 +4,7 @@ The goal is to identify lab measurements that have a numeric value but are missi ## Summary -![scatter](/mnt/disks/data/kanta/inject/test_names_exploration_scatter.png) +![scatter](data/test_names_exploration_scatter.png) *Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements* From 6ab085cac1e63ff8ae8805657efc72a9265ca3b9 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 16:41:20 +0300 Subject: [PATCH 06/20] added decision tree for ambiguous and no data. integraed omop information for no data and in summaries --- scripts/injection/README.md | 3 + scripts/injection/explore_test_name.py | 260 +++++++++++-- scripts/injection/injection_engine.py | 59 +++ scripts/injection/omop_unit_table.py | 197 ++++++++++ scripts/injection/plot_exploration.py | 38 +- scripts/injection/split_eval.py | 489 +++++++++++++++++++++++++ 6 files changed, 1014 insertions(+), 32 deletions(-) create mode 100644 scripts/injection/omop_unit_table.py create mode 100644 scripts/injection/split_eval.py diff --git a/scripts/injection/README.md b/scripts/injection/README.md index 5ce02d5..5c3d560 100644 --- a/scripts/injection/README.md +++ b/scripts/injection/README.md @@ -151,6 +151,8 @@ KDE/ECDF rendering downsamples to 50k points. All statistics use the full arrays Before the ambiguous sub-distribution pass, the candidate distribution is tested for bimodality using two statistics: +The candidate array is subsampled to 50,000 points before the dip test and GMM fitting (the dip test is unreliable above ~72k samples and GMM fitting is also faster at this size). All statistics and the separator are computed on this subsample. + **Hartigan's dip test** (primary gate): p-value < `--dip-threshold` (default 0.05) declares non-unimodal. **Bimodality coefficient** (BC): `(skew² + 1) / (excess_kurtosis + 3(n−1)²/((n−2)(n−3)))`. Values above ~0.555 suggest bimodality. @@ -162,5 +164,6 @@ Both are computed in the space (linear or log) where a 2-component GMM achieves | ≥ threshold | — | `unimodal` | | < threshold | ≥ 0.555 | `bimodal` — split into low/high | | < threshold | < 0.555 | `bimodal_cautious` — split, modes overlap | +| — | — | `skipped` — pre-check passed; bimodality not tested | A diagnostic plot (`bimodal_{tag}.png`) is saved to `--dump-dir`. diff --git a/scripts/injection/explore_test_name.py b/scripts/injection/explore_test_name.py index cfb40ee..ef33366 100644 --- a/scripts/injection/explore_test_name.py +++ b/scripts/injection/explore_test_name.py @@ -8,7 +8,7 @@ Usage ----- - python3 explore_test_name.py PARQUET MIN_COUNT [options] + python3 explore_test_name.py PARQUET [options] """ import argparse @@ -16,12 +16,16 @@ import re import subprocess import sys +from io import StringIO from pathlib import Path import numpy as np import pandas as pd +import omop_unit_table as _omop + import injection_engine +import split_eval from plot_exploration import make_scatter_plot @@ -49,11 +53,15 @@ def clickhouse(query, **params): def query_counts(parquet, out="test_name_counts.tsv"): if Path(out).exists(): - print(f"{out} already exists, skipping.") - return pd.read_csv(out, sep="\t") + df = pd.read_csv(out, sep="\t", na_values=["\\N"]) + if "OMOP_CONCEPT_ID" in df.columns: + df["OMOP_CONCEPT_ID"] = pd.to_numeric(df["OMOP_CONCEPT_ID"], errors="coerce").astype("Int64") + print(f"{out} already exists, skipping.") + return df + print(f"{out} exists but missing OMOP_CONCEPT_ID — re-querying.") result = clickhouse(f""" - SELECT TEST_NAME, count() AS COUNT + SELECT TEST_NAME, count() AS COUNT, any(OMOP_CONCEPT_ID) AS OMOP_CONCEPT_ID FROM file('{parquet}') WHERE (MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_SOURCE IS NOT NULL) AND MEASUREMENT_UNIT_PRE_FIX IS NULL @@ -63,7 +71,8 @@ def query_counts(parquet, out="test_name_counts.tsv"): FORMAT TSVWithNames """) Path(out).write_text(result) - df = pd.read_csv(out, sep="\t") + df = pd.read_csv(out, sep="\t", na_values=["\\N"]) + df["OMOP_CONCEPT_ID"] = pd.to_numeric(df["OMOP_CONCEPT_ID"], errors="coerce").astype("Int64") print(f"Wrote {out} ({len(df)} rows)") return df @@ -135,6 +144,38 @@ def query_details(parquet, counts_file="test_name_counts.tsv", out="test_name_de # Plot table # --------------------------------------------------------------------------- +def load_omop_unit_table(parquet, out="omop_unit_table.tsv"): + if Path(out).exists(): + df = pd.read_csv(out, sep="\t") + if "OMOP_TOTAL_N" in df.columns: + print(f"{out} already exists, skipping.") + df["OMOP_CONCEPT_ID"] = pd.to_numeric(df["OMOP_CONCEPT_ID"], errors="coerce").astype("Int64") + df["OMOP_TOTAL_N"] = df["OMOP_TOTAL_N"].astype("Int64") + return df + print(f"{out} exists but missing OMOP_TOTAL_N — adding counts.") + else: + print("Building OMOP unit table...") + lab_df = _omop.load_lab(_omop.DATA_DIR / "LABfi_ALL.usagi.csv") + conv_df = _omop.load_conversions(_omop.DATA_DIR / "quantity_source_unit_conversion.tsv") + df = _omop.build_table(lab_df, conv_df) + + df["OMOP_CONCEPT_ID"] = pd.to_numeric(df["OMOP_CONCEPT_ID"], errors="coerce").astype("Int64") + raw = clickhouse(f""" + SELECT OMOP_CONCEPT_ID, count() AS OMOP_TOTAL_N + FROM file('{parquet}') + WHERE OMOP_CONCEPT_ID IS NOT NULL + GROUP BY OMOP_CONCEPT_ID + FORMAT TSVWithNames + """) + counts = pd.read_csv(StringIO(raw), sep="\t") + counts["OMOP_CONCEPT_ID"] = pd.to_numeric(counts["OMOP_CONCEPT_ID"], errors="coerce").astype("Int64") + counts["OMOP_TOTAL_N"] = counts["OMOP_TOTAL_N"].astype("Int64") + df = df.merge(counts, on="OMOP_CONCEPT_ID", how="outer") + df.to_csv(out, sep="\t", index=False, na_rep="NA") + print(f" Wrote {out} ({len(df)} rows)") + return df + + def build_plot_table(counts, details): def parse_top_prevalence(d): if pd.isna(d): @@ -220,6 +261,67 @@ def print_summary(plot_name, threshold): print(f"\n * = active threshold ({threshold}%)\n") +def print_assignment_summary(udf, adf, no_data, plot_name): + """Fraction of TEST_NAMEs/measurements successfully assigned a unit.""" + count_map = plot_name.set_index("TEST_NAME")["COUNT"].to_dict() + omop_names = set(plot_name[plot_name["OMOP_CONCEPT_ID"].notna()]["TEST_NAME"]) + + def _safe(df): + return df if df is not None and len(df) else None + + udf_ = _safe(udf) + adf_ = _safe(adf) + no_data_ = _safe(no_data) + + assigned = { + "UNAMBIGUOUS": set(udf_[udf_["OUTCOME"] == "PASS"]["TEST_NAME"]) if udf_ is not None else set(), + "AMBIGUOUS": set(adf_[adf_["OUTCOME"] == "PASS"]["TEST_NAME"]) if adf_ is not None else set(), + "NO_DATA": set(no_data_[no_data_["UNIT"].notna()]["TEST_NAME"]) if no_data_ is not None else set(), + } + processed = { + "UNAMBIGUOUS": set(udf_["TEST_NAME"]) if udf_ is not None else set(), + "AMBIGUOUS": set(adf_["TEST_NAME"]) if adf_ is not None else set(), + "NO_DATA": set(no_data_["TEST_NAME"]) if no_data_ is not None else set(), + } + + def _meas(names): + return sum(count_map.get(n, 0) for n in names) + + def _build_row(name_filter=None): + cells = [] + all_asgn = set() + all_proc = set() + for cat in ["UNAMBIGUOUS", "AMBIGUOUS", "NO_DATA"]: + asgn = assigned[cat] if name_filter is None else assigned[cat] & name_filter + proc = processed[cat] if name_filter is None else processed[cat] & name_filter + all_asgn |= asgn + all_proc |= proc + cells.append((f"{len(asgn):,}/{len(proc):,}", f"{_meas(asgn):,}/{_meas(proc):,}")) + cells.append((f"{len(all_asgn):,}/{len(all_proc):,}", f"{_meas(all_asgn):,}/{_meas(all_proc):,}")) + return cells + + rows = [ + ("All", _build_row()), + ("OMOP-mapped", _build_row(omop_names)), + ] + + nw = max(len(ns) for _, cells in rows for ns, _ in cells) + mw = max(len(ms) for _, cells in rows for _, ms in cells) + lw = 12 + cw = nw + 2 + mw + cols = ["UNAMBIGUOUS", "AMBIGUOUS", "NO_DATA", "TOTAL"] + + print("\nAssignment summary (successfully assigned)\n") + print(f"{'':>{lw}}" + "".join(f" {c:^{cw}}" for c in cols)) + print(f"{'':>{lw}}" + "".join(f" {'names':>{nw}} {'meas':>{mw}}" for _ in cols)) + div = f"{'':>{lw}}" + "".join(f" {'-'*nw} {'-'*mw}" for _ in cols) + print(div) + for label, cells in rows: + line = f"{label:<{lw}}" + "".join(f" {ns:>{nw}} {ms:>{mw}}" for ns, ms in cells) + print(line) + print(div) + + def dump_summary_md(plot_name, threshold, min_count, out="summary_table.md"): total = len(plot_name) total_n = int(plot_name["COUNT"].sum()) @@ -449,7 +551,8 @@ def _unit_tag(unit): def run_ambiguous(parquet, plot_name, details, dump_dir, - dip_threshold=0.05, min_target_n=30, test_mode=False): + dip_threshold=0.05, min_target_n=30, test_mode=False, + split_threshold=0.15): os.makedirs(dump_dir, exist_ok=True) ambig = plot_name[plot_name["CATEGORY"] == "AMBIGUOUS"].sort_values("COUNT", ascending=False) @@ -528,13 +631,54 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, any_precheck_pass = any(upd["OUTCOME"] == "PASS" for _, _, _, upd, *_ in precheck) - if any_precheck_pass: - print(f" pre-check passed → skipping bimodality split") + # Bimodal check always runs — needed for split score even when pre-check passed + bim = injection_engine.bimodal_check(c_vals, dip_threshold=dip_threshold) + injection_engine.plot_bimodal_check(bim, name, dump_dir) + print(f" bimodal={bim.status} sep={bim.separator:.4g}" + f" BC={bim.bc:.3f} dip_p={bim.dip_p:.3g}") + + # Evaluate whether splitting improves the fit + prefer_split = False + si = {} + sep = bim.separator + c_low = c_vals[c_vals <= sep] if not np.isnan(sep) else np.array([]) + c_high = c_vals[c_vals > sep] if not np.isnan(sep) else np.array([]) + if len(c_low) >= 2 and len(c_high) >= 2: + si = injection_engine.split_improvement(c_vals, c_low, c_high, unit_data) + print(f" split_improvement={si['improvement']:+.1%}" + f" same_unit={si['same_best_unit']}" + f" (global_KS={si['global_score']:.4f}" + f" split_KS={si['split_score']:.4f})") + if si["improvement"] > split_threshold and not si["same_best_unit"]: + prefer_split = True + print(f" → SPLIT preferred (threshold={split_threshold:.0%})") + + # Decision-tree figure + unit_data_fig = {unit: (unit_data[unit], upct) + for unit, upct in top_units if unit in unit_data} + global_ranks = split_eval.rank_units(c_vals, unit_data_fig) + low_ranks = split_eval.rank_units(c_low, unit_data_fig) if len(c_low) >= 2 else [] + high_ranks = split_eval.rank_units(c_high, unit_data_fig) if len(c_high) >= 2 else [] + split_eval.make_figure( + name=name, c_vals=c_vals, unit_data=unit_data_fig, + global_ranks=global_ranks, low_ranks=low_ranks, high_ranks=high_ranks, + c_low=c_low, c_high=c_high, sep=sep, bim=bim, + g_score=global_ranks[0][2] if global_ranks else np.nan, + s_score=si.get("split_score", np.nan), + improvement=si.get("improvement", 0.0), + out_path=os.path.join(dump_dir, f"split_eval_{tag}.png"), + ) + + if any_precheck_pass and not prefer_split: + print(f" pre-check passed → global result kept") for unit, upct, t_vals_u, upd, ks, t, mad in precheck: rows.append(dict( TEST_NAME=name, BIMODAL_STATUS="skipped", BIMODAL_SEP=np.nan, BIMODAL_BC=np.nan, BIMODAL_DIP_P=np.nan, + SCORE_GLOBAL=si.get("global_score", np.nan), + SCORE_SPLIT=si.get("split_score", np.nan), + SCORE_IMPROVEMENT=si.get("improvement", np.nan), SUB_DIST="all", UNIT=unit, UNIT_PREVALENCE=upct, PREVALENCE_DICT=prev_dict.get(name, "NA"), @@ -543,20 +687,20 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, )) continue - # No unit passes on the full distribution → bimodal check - bim = injection_engine.bimodal_check(c_vals, dip_threshold=dip_threshold) - injection_engine.plot_bimodal_check(bim, name, dump_dir) - print(f" bimodal={bim.status} sep={bim.separator:.4g}" - f" BC={bim.bc:.3f} dip_p={bim.dip_p:.3g}") + # Decide whether to split: bimodal detected, or split preferred by score + do_split = prefer_split or bim.status in ("bimodal", "bimodal_cautious") + bimodal_label = "split_by_score" if prefer_split else bim.status - if bim.status == "unimodal": - # Already ran "all" in pre-check — reuse those results - sub_label = "unimodal" + if not do_split: + # Unimodal, pre-check failed, split not preferred — reuse pre-check results for unit, upct, t_vals_u, upd, ks, t, mad in precheck: rows.append(dict( TEST_NAME=name, BIMODAL_STATUS=bim.status, BIMODAL_SEP=bim.separator, BIMODAL_BC=bim.bc, BIMODAL_DIP_P=bim.dip_p, + SCORE_GLOBAL=si.get("global_score", np.nan), + SCORE_SPLIT=si.get("split_score", np.nan), + SCORE_IMPROVEMENT=si.get("improvement", np.nan), SUB_DIST="all", UNIT=unit, UNIT_PREVALENCE=upct, PREVALENCE_DICT=prev_dict.get(name, "NA"), @@ -585,8 +729,11 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, ) rows.append(dict( TEST_NAME=name, - BIMODAL_STATUS=bim.status, + BIMODAL_STATUS=bimodal_label, BIMODAL_SEP=bim.separator, BIMODAL_BC=bim.bc, BIMODAL_DIP_P=bim.dip_p, + SCORE_GLOBAL=si.get("global_score", np.nan), + SCORE_SPLIT=si.get("split_score", np.nan), + SCORE_IMPROVEMENT=si.get("improvement", np.nan), SUB_DIST=sub_name, UNIT=unit, UNIT_PREVALENCE=upct, PREVALENCE_DICT=prev_dict.get(name, "NA"), @@ -621,7 +768,9 @@ def _outcome_rank(o): results = results[results["UNIT"] == results["BEST_UNIT"]].drop(columns=["_rank"]) col_order = [ - "TEST_NAME", "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", "SUB_DIST", + "TEST_NAME", "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", + "SCORE_GLOBAL", "SCORE_SPLIT", "SCORE_IMPROVEMENT", + "SUB_DIST", "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "BEST_UNIT", "N_CANDIDATE", "N_TARGET", "CAND_DECILES", "TARG_DECILES", @@ -768,6 +917,10 @@ def build_parser(): help="Run the injection engine on all tests (unambiguous + ambiguous)") p.add_argument("--dip-threshold", type=float, default=0.05, metavar="FLOAT", help="Hartigan dip test p-value threshold for bimodality detection") + p.add_argument("--split-threshold", type=float, default=0.15, metavar="FLOAT", + help="Minimum relative KS improvement to prefer a split over the global fit") + p.add_argument("--omop-unit-table", default="omop_unit_table.tsv", metavar="PATH", + help="Cache path for the OMOP unit table (built automatically if missing)") p.add_argument("--min-target-n", type=int, default=30, metavar="INT", help="Minimum reference records a unit must have to be tested (ambiguous pass)") p.add_argument("--test", action="store_true", @@ -789,24 +942,83 @@ def main(): print(f"Built plot_name_level.tsv ({len(plot_name)} rows, " f"min_count={args.min_count}, threshold={args.prevalence_threshold}%)") + omop_tbl = load_omop_unit_table(args.parquet, args.omop_unit_table) + omop_cat = omop_tbl.set_index("OMOP_CONCEPT_ID")["CATEGORY"] + + def _plot_category(row): + if row["CATEGORY"] != "NO_DATA": + return row["CATEGORY"] + oid = row.get("OMOP_CONCEPT_ID") + if pd.isna(oid): + return "NO_DATA (no OMOP)" + cat = omop_cat.get(oid) + if cat in ("SINGLE", "EQUIVALENT"): + return "NO_DATA (OMOP unit)" + return "NO_DATA (OMOP only)" + + plot_name["PLOT_CATEGORY"] = plot_name.apply(_plot_category, axis=1) make_scatter_plot(plot_name) print_summary(plot_name, args.prevalence_threshold) dump_summary_md(plot_name, args.prevalence_threshold, args.min_count) + omop_sub = plot_name[plot_name["OMOP_CONCEPT_ID"].notna()].copy() + print(f"\n── OMOP-mapped subset ({len(omop_sub):,} TEST_NAMEs) ──") + print_summary(omop_sub, args.prevalence_threshold) + dump_summary_md(omop_sub, args.prevalence_threshold, args.min_count, + out="omop_summary_table.md") + if args.inject: udf = run_unambiguous(args.parquet, plot_name, details, args.dump_dir, test_mode=args.test) adf = run_ambiguous(args.parquet, plot_name, details, args.dump_dir, dip_threshold=args.dip_threshold, - min_target_n=args.min_target_n, test_mode=args.test) + min_target_n=args.min_target_n, test_mode=args.test, + split_threshold=args.split_threshold) _write_unified(udf, adf) - no_data = plot_name[plot_name["CATEGORY"] == "NO_DATA"][["TEST_NAME"]].copy() - no_data["UNIT"] = "" - no_data.to_csv("no_data_results.tsv", sep="\t", index=False) - print(f"Wrote no_data_results.tsv ({len(no_data)} rows)") + no_data = plot_name[plot_name["CATEGORY"] == "NO_DATA"][["TEST_NAME", "COUNT", "OMOP_CONCEPT_ID"]].copy() - _check_coverage(plot_name, udf, adf, no_data) + no_data = no_data.merge( + omop_tbl[["OMOP_CONCEPT_ID", "OMOP_QUANTITY", "CATEGORY", "N_UNITS", "UNITS", + "CONVERSIONS", "CANONICAL_UNIT", "OMOP_TOTAL_N"]], + on="OMOP_CONCEPT_ID", how="left", + ) + no_data["UNIT"] = no_data["CANONICAL_UNIT"].where( + no_data["CATEGORY"].isin(["SINGLE", "EQUIVALENT"]) + ) + no_data["COUNT"] = no_data["COUNT"].astype("Int64") + no_data["OMOP_TOTAL_N"] = no_data["OMOP_TOTAL_N"].astype("Int64") + no_data["PREVALENCE"] = (no_data["COUNT"] / no_data["OMOP_TOTAL_N"]).round(4) + no_data = no_data.drop(columns=["CANONICAL_UNIT"]) + + no_data.to_csv("no_data_results.tsv", sep="\t", index=False, na_rep="NA") + n_injected = no_data["UNIT"].notna().sum() + print(f"Wrote no_data_results.tsv ({len(no_data)} rows, {n_injected} units injected via OMOP)") + + has_omop = no_data["OMOP_CONCEPT_ID"].notna() + has_unit = no_data["UNIT"].notna() + n_total = len(no_data) + summary_rows = [ + ("no OMOP", (~has_omop), ), + ("OMOP, unit injected", ( has_omop & has_unit), ), + ("OMOP, no unit", ( has_omop & ~has_unit), ), + ] + w = max(len(r[0]) for r in summary_rows) + print(f"\n {'':>{w}} n % prev (median)") + print(f" {'-'*w} ---- ----- -------------") + for label, mask in summary_rows: + n = mask.sum() + pct = 100 * n / n_total + prev_s = no_data.loc[mask, "PREVALENCE"].dropna() + prev_str = f"{prev_s.median():.1%}" if len(prev_s) else "NA" + print(f" {label:>{w}} {n:>4} {pct:>5.1f}% {prev_str:>13}") + print(f" {'-'*w} ----") + print(f" {'total':>{w}} {n_total:>4}") + + if not args.test: + _check_coverage(plot_name, udf, adf, no_data) + + print_assignment_summary(udf, adf, no_data, plot_name) if __name__ == "__main__": diff --git a/scripts/injection/injection_engine.py b/scripts/injection/injection_engine.py index 215311f..f36847d 100644 --- a/scripts/injection/injection_engine.py +++ b/scripts/injection/injection_engine.py @@ -343,6 +343,65 @@ def plot_bimodal_check(result, name, dump_dir): plt.close(fig) +# --------------------------------------------------------------------------- +# Split improvement scoring +# --------------------------------------------------------------------------- + +def _ks_stat_only(a, b): + """KS statistic as a float (no p-value).""" + if max(len(a), len(b)) > _BINNED_KS_N: + return _binned_ks(a, b)[0] + return float(stats.ks_2samp(a, b).statistic) + + +def rank_units_by_ks(c, unit_vals): + """ + c : candidate array + unit_vals : {unit: t_vals} + Returns list of (unit, ks_stat) sorted ascending by ks_stat. + """ + return sorted( + ((unit, _ks_stat_only(c, t)) for unit, t in unit_vals.items()), + key=lambda x: x[1], + ) + + +def split_improvement(c_vals, c_low, c_high, unit_vals): + """ + Compare size-weighted split KS against the global best KS. + + unit_vals : {unit: t_vals} + + Returns dict: + global_score, global_ranks, low_ranks, high_ranks, + split_score, improvement (positive = split is better), + same_best_unit (True suggests intrinsic bimodality) + """ + global_ranks = rank_units_by_ks(c_vals, unit_vals) + global_score = global_ranks[0][1] if global_ranks else np.nan + + low_ranks = rank_units_by_ks(c_low, unit_vals) if len(c_low) >= 2 else [] + high_ranks = rank_units_by_ks(c_high, unit_vals) if len(c_high) >= 2 else [] + + if not low_ranks or not high_ranks or np.isnan(global_score): + return dict( + global_score=global_score, global_ranks=global_ranks, + low_ranks=low_ranks, high_ranks=high_ranks, + split_score=np.nan, improvement=0.0, same_best_unit=True, + ) + + n_total = len(c_low) + len(c_high) + s_score = (len(c_low) * low_ranks[0][1] + len(c_high) * high_ranks[0][1]) / n_total + impr = (global_score - s_score) / global_score if global_score > 0 else 0.0 + + return dict( + global_score=global_score, global_ranks=global_ranks, + low_ranks=low_ranks, high_ranks=high_ranks, + split_score=s_score, improvement=impr, + same_best_unit=low_ranks[0][0] == high_ranks[0][0], + ) + + # --------------------------------------------------------------------------- # Pipeline # --------------------------------------------------------------------------- diff --git a/scripts/injection/omop_unit_table.py b/scripts/injection/omop_unit_table.py new file mode 100644 index 0000000..c6de758 --- /dev/null +++ b/scripts/injection/omop_unit_table.py @@ -0,0 +1,197 @@ +#!/usr/bin/env python3 +""" +omop_unit_table.py + +Build a per-OMOP-concept unit conversion table. + +Logic +----- +1. LABfi_ALL.usagi.csv → OMOP_CONCEPT_ID → omopQuantity (only these two fields matter) +2. quantity_source_unit_conversion.tsv → for each omopQuantity, what units exist + and what are their pairwise conversions? + +CATEGORY +-------- + SINGLE — only one unit defined for this quantity + EQUIVALENT — multiple units, all pairwise conversions = 1 + AMBIGUOUS — multiple units, at least one conversion ≠ 1 + NO_CONV — quantity known but not in conversion table + NO_QUANTITY — concept has no omopQuantity in LABfi + +Usage +----- + python3 omop_unit_table.py [--approved-only] [--out omop_unit_table.tsv] +""" + +import argparse +from pathlib import Path + +import pandas as pd + +DATA_DIR = Path("~/Dropbox/Projects/kanta_lab_preprocessing/src/kanta/finngen_qc/data").expanduser() + + +# --------------------------------------------------------------------------- +# Loaders +# --------------------------------------------------------------------------- + +def load_lab(path, approved_only=False): + """OMOP_CONCEPT_ID → (CONCEPT_NAME, omopQuantity). Units ignored.""" + df = pd.read_csv(path) + df = df[df["domainId"] == "Measurement"] + if approved_only: + df = df[df["mappingStatus"] == "APPROVED"] + df = df.rename(columns={ + "conceptId": "OMOP_CONCEPT_ID", + "conceptName": "CONCEPT_NAME", + "ADD_INFO:omopQuantity": "omop_quantity", + }) + return df[["OMOP_CONCEPT_ID", "CONCEPT_NAME", "omop_quantity"]].drop_duplicates() + + +def load_conversions(path): + df = pd.read_csv(path, sep="\t") + df = df.rename(columns={ + "omop_quantity": "omop_quantity", + "source_unit_valid": "unit_from", + "to_source_unit_valid": "unit_to", + "conversion": "factor", + }) + df = df[df["unit_from"].notna() & df["unit_to"].notna()] + df["factor"] = pd.to_numeric(df["factor"], errors="coerce") + return df[["omop_quantity", "unit_from", "unit_to", "factor"]] + + +# --------------------------------------------------------------------------- +# Core +# --------------------------------------------------------------------------- + +def build_table(lab_df, conv_df): + # Build per-quantity: valid units and conversion lookup + qty_units = {} # omop_quantity -> sorted list of units + conv_lookup = {} # (omop_quantity, unit_from, unit_to) -> factor + + for _, row in conv_df.iterrows(): + q = row["omop_quantity"] + qty_units.setdefault(q, set()) + if pd.notna(row["unit_from"]): + qty_units[q].add(row["unit_from"]) + if pd.notna(row["unit_to"]): + qty_units[q].add(row["unit_to"]) + if pd.notna(row["factor"]): + conv_lookup[(q, row["unit_from"], row["unit_to"])] = float(row["factor"]) + + qty_units = {q: sorted(us) for q, us in qty_units.items()} + + rows = [] + + for omop_id, grp in lab_df.groupby("OMOP_CONCEPT_ID"): + concept_name = grp["CONCEPT_NAME"].iloc[0] + omop_quantity = grp["omop_quantity"].iloc[0] + + if pd.isna(omop_quantity) or str(omop_quantity).strip() == "": + rows.append(dict( + OMOP_CONCEPT_ID=omop_id, CONCEPT_NAME=concept_name, + OMOP_QUANTITY=omop_quantity, N_UNITS=0, + UNITS="", CONVERSIONS="", CATEGORY="NO_QUANTITY", + CANONICAL_UNIT=pd.NA, + )) + continue + + units = qty_units.get(str(omop_quantity).strip(), []) + n_units = len(units) + + if n_units == 0: + rows.append(dict( + OMOP_CONCEPT_ID=omop_id, CONCEPT_NAME=concept_name, + OMOP_QUANTITY=omop_quantity, N_UNITS=0, + UNITS="", CONVERSIONS="", CATEGORY="NO_CONV", + CANONICAL_UNIT=pd.NA, + )) + continue + + if n_units == 1: + rows.append(dict( + OMOP_CONCEPT_ID=omop_id, CONCEPT_NAME=concept_name, + OMOP_QUANTITY=omop_quantity, N_UNITS=1, + UNITS=units[0], CONVERSIONS="1", CATEGORY="SINGLE", + CANONICAL_UNIT=units[0], + )) + continue + + # Multiple units — check pairwise conversions + factors = [] + missing = [] + for i, u1 in enumerate(units): + for u2 in units[i + 1:]: + fwd = conv_lookup.get((omop_quantity, u1, u2)) + rev = conv_lookup.get((omop_quantity, u2, u1)) + if fwd is not None: + factors.append(fwd) + elif rev is not None: + factors.append(rev) + else: + missing.append(f"{u1}↔{u2}") + + if missing: + category = "NO_CONV" + canonical = pd.NA + elif all(abs(f - 1.0) < 1e-9 for f in factors): + category = "EQUIVALENT" + canonical = units[0] # alphabetically first — all are equivalent + else: + category = "AMBIGUOUS" + canonical = pd.NA + + unique_factors = sorted(set(round(f, 8) for f in factors)) + rows.append(dict( + OMOP_CONCEPT_ID=omop_id, CONCEPT_NAME=concept_name, + OMOP_QUANTITY=omop_quantity, N_UNITS=n_units, + UNITS="|".join(units), + CONVERSIONS="|".join(str(f) for f in unique_factors), + CATEGORY=category, + CANONICAL_UNIT=canonical, + )) + + df = pd.DataFrame(rows).sort_values(["CATEGORY", "OMOP_CONCEPT_ID"]).reset_index(drop=True) + df["N_UNITS"] = df["N_UNITS"].astype("Int64") + return df + + +# --------------------------------------------------------------------------- +# Main +# --------------------------------------------------------------------------- + +def main(): + p = argparse.ArgumentParser( + description="Build per-OMOP-concept unit conversion table.", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + p.add_argument("--lab-file", default=str(DATA_DIR / "LABfi_ALL.usagi.csv")) + p.add_argument("--conv-file", default=str(DATA_DIR / "quantity_source_unit_conversion.tsv")) + p.add_argument("--out", default="omop_unit_table.tsv") + p.add_argument("--approved-only", action="store_true", + help="Only include APPROVED mappings") + args = p.parse_args() + + print(f"Loading lab mapping ({'APPROVED only' if args.approved_only else 'all statuses'})...") + lab_df = load_lab(args.lab_file, approved_only=args.approved_only) + print(f" {lab_df['OMOP_CONCEPT_ID'].nunique():>6} unique OMOP concepts") + + print("Loading conversion table...") + conv_df = load_conversions(args.conv_file) + print(f" {len(conv_df):>6} conversion entries") + + print("Building table...") + result = build_table(lab_df, conv_df) + + print(f"\nCategory breakdown ({len(result)} concepts total):") + for cat, n in result["CATEGORY"].value_counts().items(): + print(f" {cat:<15} {n:>5} ({100*n/len(result):.1f}%)") + + result.to_csv(args.out, sep="\t", index=False, na_rep="NA") + print(f"\nWrote {args.out}") + + +if __name__ == "__main__": + main() diff --git a/scripts/injection/plot_exploration.py b/scripts/injection/plot_exploration.py index 593e08a..a1c1d14 100644 --- a/scripts/injection/plot_exploration.py +++ b/scripts/injection/plot_exploration.py @@ -6,6 +6,9 @@ Importable: call make_scatter_plot(plot_name). Standalone: reads plot_name_level.tsv from the current directory. + +If plot_name contains a PLOT_CATEGORY column it is used to color points; +otherwise all points are drawn in a single colour. """ import argparse @@ -19,30 +22,49 @@ DEFAULT_OUTPUT = "test_names_exploration_scatter.png" +_COLORS = {"has OMOP": "steelblue", "no OMOP": "tomato"} + def make_scatter_plot(plot_name, output=DEFAULT_OUTPUT): - fig = plt.figure(figsize=(11, 7)) + fig = plt.figure(figsize=(12, 7)) gs = GridSpec(1, 2, width_ratios=[4, 1], wspace=0.05) ax_scatter = fig.add_subplot(gs[0]) ax_kde = fig.add_subplot(gs[1], sharey=ax_scatter) - ax_scatter.scatter(plot_name["COUNT"], plot_name["top_prevalence"], - alpha=0.5, s=20) + if "OMOP_CONCEPT_ID" in plot_name.columns: + groups = { + "has OMOP": plot_name[plot_name["OMOP_CONCEPT_ID"].notna()], + "no OMOP": plot_name[plot_name["OMOP_CONCEPT_ID"].isna()], + } + else: + groups = {"all": plot_name} + _COLORS["all"] = "steelblue" + + for label, sub in groups.items(): + ax_scatter.scatter(sub["COUNT"], sub["top_prevalence"], + alpha=0.5, s=20, + color=_COLORS[label], label=f"{label} (n={len(sub)})") + ax_scatter.legend(fontsize=8, markerscale=1.5, loc="upper right") ax_scatter.set_xlabel("Count (value, no unit)") ax_scatter.set_ylabel("Top unit prevalence (%)") ax_scatter.set_title("TEST_NAME level — injection candidates") ax_scatter.set_xscale("log") - prev = plot_name["top_prevalence"].dropna().values - ys = np.linspace(prev.min(), prev.max(), 500) - kde = gaussian_kde(prev, bw_method="scott") - ax_kde.fill_betweenx(ys, kde(ys), alpha=0.4, color="steelblue") - ax_kde.plot(kde(ys), ys, color="steelblue", lw=1.2) + for label, sub in groups.items(): + prev = sub["top_prevalence"].dropna().values + if len(prev) < 2: + continue + ys = np.linspace(prev.min(), prev.max(), 400) + kde = gaussian_kde(prev, bw_method="scott") + ax_kde.fill_betweenx(ys, kde(ys), alpha=0.2, color=_COLORS[label]) + ax_kde.plot(kde(ys), ys, color=_COLORS[label], lw=1.2) + ax_kde.set_xlabel("density") ax_kde.tick_params(labelleft=False) ax_kde.set_xlim(left=0) plt.savefig(output, dpi=150, bbox_inches="tight") + plt.close(fig) print(f"Saved {output}") diff --git a/scripts/injection/split_eval.py b/scripts/injection/split_eval.py new file mode 100644 index 0000000..5551d62 --- /dev/null +++ b/scripts/injection/split_eval.py @@ -0,0 +1,489 @@ +#!/usr/bin/env python3 +""" +split_eval.py + +For a single TEST_NAME, evaluate whether splitting the candidate distribution +by a GMM separator yields a better unit fit than treating it as a whole. + +Metric: size-weighted average KS statistic + global_score = best (lowest) KS over qualifying units for c_all + split_score = (n_low * best_KS(c_low, units) + + n_high * best_KS(c_high, units)) / n_total + improvement = (global_score − split_score) / global_score + +Usage +----- + python3 split_eval.py TEST_NAME --units "mmol/l:85.2,µmol/l:12.1" [options] + + Assumes candidate and target .npy arrays already exist in --dump-dir + (produced by explore_test_name.py). +""" + +import argparse +import os +import sys + +import matplotlib +matplotlib.use("Agg") +import matplotlib.pyplot as plt +import numpy as np +from scipy import stats + +import injection_engine + + +def _unit_tag(unit): + return unit.replace("/", "_").replace(" ", "_").replace("%", "pct") + + +def _name_tag(name): + return name.replace("/", "_").replace(" ", "_") + + +def _parse_units_arg(units_str): + """Parse 'unit1:pct1,unit2:pct2,...' → list of (unit, pct). pct defaults to 0.0.""" + pairs = [] + for item in units_str.split(","): + item = item.strip().strip("{}") + if not item: + continue + if ":" in item: + u, p = item.rsplit(":", 1) + pairs.append((u.strip(), float(p))) + else: + pairs.append((item.strip(), 0.0)) + return pairs + + +def load_candidate(name, dump_dir): + tag = _name_tag(name) + path = os.path.join(dump_dir, f"cand_{tag}.npy") + arr = np.load(path) + print(f" candidate: N={len(arr):,} ({path})") + return arr + + +def load_target(name, unit, dump_dir): + tag = _name_tag(name) + path = os.path.join(dump_dir, f"targ_{tag}_{_unit_tag(unit)}.npy") + return np.load(path) + + +# --------------------------------------------------------------------------- +# KS helper (stat only — no p-value needed for scoring) +# --------------------------------------------------------------------------- + +def _ks_stat(a, b): + n1, n2 = len(a), len(b) + if max(n1, n2) > 500_000: + lo, hi = min(a.min(), b.min()), max(a.max(), b.max()) + if lo == hi: + return 0.0 + bins = 100_000 + h1, _ = np.histogram(a, bins=bins, range=(lo, hi)) + h2, _ = np.histogram(b, bins=bins, range=(lo, hi)) + e1 = np.cumsum(h1) / n1 + e2 = np.cumsum(h2) / n2 + return float(np.max(np.abs(e1 - e2))) + return float(stats.ks_2samp(a, b).statistic) + + +# --------------------------------------------------------------------------- +# Comparison logic +# --------------------------------------------------------------------------- + +def rank_units(c, unit_data): + """ + For a candidate array c, compute KS against every unit. + Returns list of (unit, pct, ks_stat) sorted by ks_stat ascending. + """ + results = [] + for unit, (t_vals, pct) in unit_data.items(): + results.append((unit, pct, _ks_stat(c, t_vals))) + results.sort(key=lambda x: x[2]) + return results + + +def split_score(n_low, ks_low, n_high, ks_high): + """Size-weighted average KS across sub-distributions.""" + return (n_low * ks_low + n_high * ks_high) / (n_low + n_high) + + +# --------------------------------------------------------------------------- +# Full pipeline for display +# --------------------------------------------------------------------------- + +def run_full_pipeline(c, t, label): + """Run KS+T+MAD and return a one-line summary string + PipelineResult.""" + result = injection_engine.run_pipeline(c, t) + ks = next(s for s in result.steps if s.name == "KS") + t_ = next(s for s in result.steps if s.name == "T") + m = next(s for s in result.steps if s.name == "MAD") + summary = ( + f"{label:<40} " + f"KS={'P' if ks.passed else 'F'}({ks.details['stat']:.4f}) " + f"T={'P' if t_.passed else 'F'} " + f"MAD={'P' if m.passed else 'F'} " + f"→ {result.outcome} at {result.decided_by}" + ) + return summary, result + + +# --------------------------------------------------------------------------- +# Plotting +# --------------------------------------------------------------------------- + +_PLOT_MAX_N = 50_000 + + +def _sample(arr): + if len(arr) > _PLOT_MAX_N: + rng = np.random.default_rng(42) + return arr[np.sort(rng.choice(len(arr), _PLOT_MAX_N, replace=False))] + return arr + + +def _ecdf(arr): + x = np.sort(arr) + return x, np.arange(1, len(x) + 1) / len(x) + + +def _kde(ax, arr, label, color, lw=1.6, fill=True, ls="-"): + arr = _sample(arr) + if len(arr) < 2 or np.std(arr) == 0: + return + kde = stats.gaussian_kde(arr) + xs = np.linspace(arr.min(), arr.max(), 400) + ys = kde(xs) + ax.plot(xs, ys, color=color, label=label, lw=lw, ls=ls, alpha=0.9) + if fill: + ax.fill_between(xs, ys, color=color, alpha=0.12) + + +def _ecdf_plot(ax, arr, label, color): + x, y = _ecdf(_sample(arr)) + ax.step(x, y, where="post", color=color, label=label, alpha=0.85) + + +def _ks_marker(ax, c, t, ks_stat): + cs = _sample(c) + ts = _sample(t) + cx, _ = _ecdf(cs) + tx, _ = _ecdf(ts) + all_x = np.sort(np.unique(np.concatenate([cx, tx]))) + c_cdf = np.searchsorted(cx, all_x, side="right") / len(cx) + t_cdf = np.searchsorted(tx, all_x, side="right") / len(tx) + i = np.argmax(np.abs(c_cdf - t_cdf)) + y_lo, y_hi = sorted([c_cdf[i], t_cdf[i]]) + ax.plot([all_x[i], all_x[i]], [y_lo, y_hi], color="red", lw=2.5, + label=f"D={ks_stat:.4f}") + + +_COLORS = ["steelblue", "darkorange", "seagreen", "mediumpurple", "saddlebrown"] + + +def make_figure(name, c_vals, unit_data, + global_ranks, low_ranks, high_ranks, + c_low, c_high, sep, bim, + g_score, s_score, improvement, + out_path): + """ + 2 rows × 3 cols: + Row 0 — Global: KDE (all units) | ECDF (best unit) | GMM fit + Row 1 — Split: KDE low vs best | KDE high vs best | Score summary + """ + unit_colors = {u: _COLORS[i % len(_COLORS)] for i, u in enumerate(unit_data)} + + best_g_unit, _, best_g_ks = global_ranks[0] + best_l_unit, _, best_l_ks = low_ranks[0] if low_ranks else (None, 0, np.nan) + best_h_unit, _, best_h_ks = high_ranks[0] if high_ranks else (None, 0, np.nan) + + t_global = unit_data[best_g_unit][0] + t_low = unit_data[best_l_unit][0] if best_l_unit else np.array([]) + t_high = unit_data[best_h_unit][0] if best_h_unit else np.array([]) + + verdict = "SPLIT BETTER" if improvement > 0 else "GLOBAL BETTER" + same_unit = best_l_unit == best_h_unit + + fig, axes = plt.subplots(2, 3, figsize=(21, 10)) + fig.suptitle( + f"{name}" + f" global KS={g_score:.4f} split KS={s_score:.4f}" + f" improvement={improvement:+.1%}" + f" → {verdict}" + + (" [same unit → likely intrinsic]" if same_unit else ""), + fontsize=12, fontweight="bold", + ) + + # ── (0,0) Global KDE: candidate + all unit targets ────────────────── + ax = axes[0, 0] + _kde(ax, c_vals, "candidate (all)", "black", lw=2.2) + for unit, (t_vals, pct) in unit_data.items(): + is_best = (unit == best_g_unit) + _kde(ax, t_vals, + f"{unit} ({pct:.1f}%)", + unit_colors[unit], + lw=2.2 if is_best else 1.2, + ls="-" if is_best else "--", + fill=is_best) + ax.set_title("Global: candidate vs all units (KDE)") + ax.set_xlabel("value"); ax.legend(fontsize=8) + + # ── (0,1) Global ECDF: candidate vs best unit ──────────────────────── + ax = axes[0, 1] + _ecdf_plot(ax, c_vals, "candidate (all)", "black") + _ecdf_plot(ax, t_global, f"{best_g_unit} (global best)", "steelblue") + _ks_marker(ax, c_vals, t_global, best_g_ks) + ax.set_title(f"Global ECDF best={best_g_unit} KS={best_g_ks:.4f}") + ax.set_xlabel("value"); ax.set_ylabel("CDF"); ax.legend(fontsize=8) + + # ── (0,2) GMM bimodal plot ──────────────────────────────────────────── + ax = axes[0, 2] + if bim.fit: + fit = bim.fit + x_fit = fit["x_fit"] + lo_f, hi_f = np.percentile(x_fit, [0.5, 99.5]) + ax.hist(x_fit, bins=60, density=True, alpha=0.4, color="grey", + range=(lo_f, hi_f), label="candidate") + xf = np.linspace(lo_f, hi_f, 400) + for m, s, w in zip(fit["means_native"], fit["sigmas_native"], fit["weights"]): + ax.plot(xf, w * stats.norm.pdf(xf, m, s), lw=1.8, alpha=0.85) + if not np.isnan(fit.get("sep_native", np.nan)): + ax.axvline(fit["sep_native"], color="red", ls="--", + label=f"sep={sep:.4g}") + ax.set_xlabel("log(value)" if bim.lognormal else "value") + ax.set_title( + f"GMM status={bim.status}" + f" BC={bim.bc:.3f} dip_p={bim.dip_p:.3g}" + f" n_low={len(c_low):,} n_high={len(c_high):,}" + ) + ax.legend(fontsize=8) + + # ── (1,0) Split KDE: low sub vs its best unit ──────────────────────── + ax = axes[1, 0] + if len(c_low) >= 2: + _kde(ax, c_low, f"low (N={len(c_low):,})", "steelblue") + if len(t_low) >= 2: + _kde(ax, t_low, f"{best_l_unit} (best for low)", "darkorange", fill=False, ls="--") + ax.set_title(f"Split LOW best={best_l_unit} KS={best_l_ks:.4f}") + ax.set_xlabel("value"); ax.legend(fontsize=8) + + # ── (1,1) Split KDE: high sub vs its best unit ─────────────────────── + ax = axes[1, 1] + if len(c_high) >= 2: + _kde(ax, c_high, f"high (N={len(c_high):,})", "seagreen") + if len(t_high) >= 2: + _kde(ax, t_high, f"{best_h_unit} (best for high)", "darkorange", fill=False, ls="--") + ax.set_title(f"Split HIGH best={best_h_unit} KS={best_h_ks:.4f}") + ax.set_xlabel("value"); ax.legend(fontsize=8) + + # ── (1,2) Score summary text panel ────────────────────────────────── + ax = axes[1, 2] + ax.axis("off") + n_total = len(c_vals) + n_low = len(c_low) + n_high = len(c_high) + + lines = [ + "── SCORE SUMMARY ──────────────────────", + "", + f"GLOBAL KS = {g_score:.4f}", + ] + for u, p, k in global_ranks: + marker = " ←" if u == best_g_unit else "" + lines.append(f" {u:<18} KS={k:.4f}{marker}") + + lines += [ + "", + f"SPLIT weighted KS = {s_score:.4f}", + f" low N={n_low:,} ({100*n_low/n_total:.1f}%)", + ] + for u, p, k in low_ranks: + marker = " ←" if u == best_l_unit else "" + lines.append(f" {u:<16} KS={k:.4f}{marker}") + lines.append(f" high N={n_high:,} ({100*n_high/n_total:.1f}%)") + for u, p, k in high_ranks: + marker = " ←" if u == best_h_unit else "" + lines.append(f" {u:<16} KS={k:.4f}{marker}") + + lines += [ + "", + f"improvement = {improvement:+.1%}", + f"same unit? = {same_unit}", + f" low → {best_l_unit}", + f" high → {best_h_unit}", + "", + f"VERDICT: {verdict}", + ] + + ax.text(0.04, 0.97, "\n".join(lines), + transform=ax.transAxes, fontsize=9.5, va="top", family="monospace", + bbox=dict(boxstyle="round", facecolor="lightyellow", alpha=0.85)) + + plt.tight_layout() + plt.savefig(out_path, dpi=120, bbox_inches="tight") + plt.close(fig) + print(f" figure → {out_path}") + + +# --------------------------------------------------------------------------- +# Main +# --------------------------------------------------------------------------- + +def main(): + p = argparse.ArgumentParser( + description="Evaluate global vs split unit fit for a single TEST_NAME.", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + p.add_argument("test_name", help="TEST_NAME to evaluate") + p.add_argument("--units", required=True, + help="Comma-separated units to evaluate, optionally with pct: " + "'mmol/l:85.2,µmol/l:12.1'") + p.add_argument("--dump-dir", default="/mnt/disks/data/kanta/inject/tmp/", + help="Cache directory containing existing .npy arrays") + p.add_argument("--min-target-n", type=int, default=30, + help="Minimum records for a unit target to qualify") + p.add_argument("--dip-threshold",type=float, default=0.05, + help="Hartigan dip test p-value threshold for bimodality check") + p.add_argument("--out-dir", default=".", + help="Directory for output figure") + args = p.parse_args() + + name = args.test_name + + SEP = "=" * 72 + print(f"\n{SEP}") + print(f"SPLIT EVALUATION: {name}") + print(SEP) + + # ── 1. Candidate values ─────────────────────────────────────────────── + print("\n[1] Candidate values") + c_vals = load_candidate(name, args.dump_dir) + if len(c_vals) < 2: + sys.exit("ERROR: too few candidate values") + print(f" N={len(c_vals):,} " + f"median={np.median(c_vals):.4g} " + f"p5={np.percentile(c_vals,5):.4g} " + f"p95={np.percentile(c_vals,95):.4g}") + + # ── 2. Units (passed in) ────────────────────────────────────────────── + print(f"\n[2] Units") + top_units = _parse_units_arg(args.units) + if not top_units: + sys.exit("ERROR: --units produced no entries") + for u, pct in top_units: + print(f" {u:<22} {pct:>6.2f}%") + + # ── 3. Target arrays ────────────────────────────────────────────────── + print(f"\n[3] Target arrays (min_target_n={args.min_target_n})") + unit_data = {} # unit → (t_vals, pct) + for unit, pct in top_units: + t_vals = load_target(name, unit, args.dump_dir) + status = f"N={len(t_vals):,}" + if len(t_vals) < args.min_target_n: + status += " SKIP (too few)" + print(f" {unit:<22} {status}") + if len(t_vals) >= args.min_target_n: + unit_data[unit] = (t_vals, pct) + if not unit_data: + sys.exit("ERROR: no qualifying target distributions") + + # ── 4. Global comparison ────────────────────────────────────────────── + print("\n[4] Global comparison KS(c_all, unit)") + global_ranks = rank_units(c_vals, unit_data) + for unit, pct, ks in global_ranks: + tag_mark = " ← best" if unit == global_ranks[0][0] else "" + print(f" {unit:<22} KS={ks:.4f}{tag_mark}") + g_score = global_ranks[0][2] + + print("\n Full pipeline (global best unit):") + best_g_unit = global_ranks[0][0] + t_best_g = unit_data[best_g_unit][0] + summary, _ = run_full_pipeline(c_vals, t_best_g, f"c_all vs {best_g_unit}") + print(f" {summary}") + + # ── 5. Bimodal check + split ────────────────────────────────────────── + print(f"\n[5] Bimodal check (dip_threshold={args.dip_threshold})") + bim = injection_engine.bimodal_check(c_vals, dip_threshold=args.dip_threshold) + print(f" status={bim.status} sep={bim.separator:.4g}" + f" BC={bim.bc:.3f} dip_p={bim.dip_p:.3g}" + f" space={'log' if bim.lognormal else 'linear'}") + + sep = bim.separator + c_low = c_vals[c_vals <= sep] if not np.isnan(sep) else np.array([]) + c_high = c_vals[c_vals > sep] if not np.isnan(sep) else np.array([]) + n_low, n_high = len(c_low), len(c_high) + print(f" low: N={n_low:,} ({100*n_low/len(c_vals):.1f}%)" + f" high: N={n_high:,} ({100*n_high/len(c_vals):.1f}%)") + if n_low < 2 or n_high < 2: + print(" WARNING: one sub-distribution is too small — split metrics may be unreliable") + + # ── 6. Split comparison ─────────────────────────────────────────────── + print("\n[6] Split comparison KS(c_sub, unit)") + low_ranks = rank_units(c_low, unit_data) if n_low >= 2 else [] + high_ranks = rank_units(c_high, unit_data) if n_high >= 2 else [] + + print(" LOW sub-distribution:") + for unit, pct, ks in low_ranks: + tag_mark = " ← best" if unit == low_ranks[0][0] else "" + print(f" {unit:<22} KS={ks:.4f}{tag_mark}") + + print(" HIGH sub-distribution:") + for unit, pct, ks in high_ranks: + tag_mark = " ← best" if unit == high_ranks[0][0] else "" + print(f" {unit:<22} KS={ks:.4f}{tag_mark}") + + print("\n Full pipeline (best unit per sub):") + if low_ranks: + best_l_unit = low_ranks[0][0] + s, _ = run_full_pipeline(c_low, unit_data[best_l_unit][0], f"c_low vs {best_l_unit}") + print(f" {s}") + if high_ranks: + best_h_unit = high_ranks[0][0] + s, _ = run_full_pipeline(c_high, unit_data[best_h_unit][0], f"c_high vs {best_h_unit}") + print(f" {s}") + + # ── 7. Aggregated score ─────────────────────────────────────────────── + print(f"\n[7] Score aggregation") + if low_ranks and high_ranks: + best_l_ks = low_ranks[0][2] + best_h_ks = high_ranks[0][2] + s_score = split_score(n_low, best_l_ks, n_high, best_h_ks) + improvement = (g_score - s_score) / g_score if g_score > 0 else 0.0 + else: + s_score = np.nan + improvement = 0.0 + + best_l_unit = low_ranks[0][0] if low_ranks else "—" + best_h_unit = high_ranks[0][0] if high_ranks else "—" + same_unit = best_l_unit == best_h_unit + + print(f" global_score = {g_score:.4f} (best unit: {global_ranks[0][0]})") + print(f" split_score = {s_score:.4f} (size-weighted avg of per-sub bests)") + print(f" improvement = {improvement:+.1%}") + print(f" same best unit for both subs? {same_unit}" + f" (low={best_l_unit}, high={best_h_unit})") + + verdict = "SPLIT BETTER" if improvement > 0 else "GLOBAL BETTER" + print(f"\n{SEP}") + print(f"VERDICT: {verdict} (improvement={improvement:+.1%})") + if same_unit: + print(" NOTE: both sub-distributions prefer the same unit" + " — likely intrinsic bimodality, not a unit mix") + print(SEP) + + # ── 8. Figure ───────────────────────────────────────────────────────── + out_path = os.path.join(args.out_dir, f"split_eval_{_name_tag(name)}.png") + print(f"\n[8] Generating figure") + make_figure( + name=name, c_vals=c_vals, unit_data=unit_data, + global_ranks=global_ranks, + low_ranks=low_ranks, high_ranks=high_ranks, + c_low=c_low, c_high=c_high, sep=sep, bim=bim, + g_score=g_score, s_score=s_score, improvement=improvement, + out_path=out_path, + ) + + +if __name__ == "__main__": + main() From 662bde31dcf1c46d8cf971565c63fe5f40f081f9 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 16:54:22 +0300 Subject: [PATCH 07/20] updated REAMDE Co-Authored-By: Claude Sonnet 4.6 --- scripts/injection/README.md | 53 ++++++++++++++++++++++---- scripts/injection/explore_test_name.py | 12 ------ 2 files changed, 46 insertions(+), 19 deletions(-) diff --git a/scripts/injection/README.md b/scripts/injection/README.md index 5c3d560..9bd95cb 100644 --- a/scripts/injection/README.md +++ b/scripts/injection/README.md @@ -29,8 +29,10 @@ python3 explore_test_name.py [options] - `--prevalence-threshold FLOAT`: min dominant-unit prevalence (%) to classify a TEST_NAME as UNAMBIGUOUS (default: 98) - `--min-target-n INT`: minimum reference records a unit must have; tests below this are classified NO_DATA (default: 30) - `--dump-dir PATH`: cache directory for per-test `.npy` arrays (default: `/mnt/disks/data/kanta/inject/tmp/`) +- `--omop-unit-table PATH`: cache path for the OMOP unit table; built automatically on first run (default: `omop_unit_table.tsv`) - `--inject`: run the injection engine (unambiguous + ambiguous + no_data passes) - `--dip-threshold FLOAT`: Hartigan dip test p-value threshold for bimodality (default: 0.05) +- `--split-threshold FLOAT`: minimum relative KS improvement required to prefer a score-based split over the global fit (default: 0.15) - `--test`: small-sample mode — one test per COUNT decile (unambiguous) and top 10 by volume (ambiguous) ### Caching behaviour @@ -85,6 +87,20 @@ One row per TEST_NAME. Columns include `COUNT`, `N_WITH_UNIT`, `top_prevalence`, The injection engine only runs tests classified as UNAMBIGUOUS or AMBIGUOUS. NO_DATA tests are written directly to `no_data_results.tsv`. +### OMOP unit table (`omop_unit_table.tsv`) + +Built once from the OMOP LAB mapping files and enriched with per-concept record counts queried from the parquet file. Cached at `--omop-unit-table`. Each OMOP concept is assigned a `CATEGORY`: + +- `SINGLE` — only one unit observed in the OMOP data +- `EQUIVALENT` — multiple units present but all mutually convertible; a `CANONICAL_UNIT` is available +- `MULTIPLE` — multiple non-equivalent units; no single canonical unit can be assigned + +This table is used to enrich `no_data_results.tsv` with canonical units. + +Two summary tables are written: +- `summary_table.md` — all TEST_NAMEs +- `omop_summary_table.md` — OMOP-mapped subset only + --- ## Step 4 — Injection engine (`--inject`) @@ -103,18 +119,35 @@ TEST_NAMEs with `CATEGORY == AMBIGUOUS`. Only units with prevalence > 1% and at Pipeline per TEST_NAME: -1. **Pre-check**: run the full (unsplit) candidate distribution against each qualifying unit. If any unit passes, record those results and skip bimodality entirely. -2. **Bimodality check** (only if pre-check fails): test the candidate distribution for bimodality (see below). If bimodal, split into low/high sub-distributions and re-run the engine on each sub-distribution × unit. +1. **Pre-check**: run the full (unsplit) candidate distribution against each qualifying unit. +2. **Bimodality check** (always runs, even if pre-check passed): test the candidate distribution for bimodality and compute `split_improvement` — the relative KS gain when the candidate is split at the GMM separator vs. treated globally. +3. **Split decision**: a split is preferred if `split_improvement > --split-threshold` AND the two halves favour different best units (`same_best_unit == False`). If splitting is not preferred and any pre-check passed, the global result is kept. +4. **Sub-distribution engine** (only if splitting is preferred): the candidate is split into low/high halves at the GMM separator and the engine is re-run on each half × unit. One row per `(TEST_NAME, SUB_DIST)` — the best unit only. Best unit selection: PASS > FAIL > SKIP, then highest `UNIT_PREVALENCE` as tiebreaker — we prefer the dominant clinical unit when two units both pass. -Columns: `TEST_NAME`, `BIMODAL_STATUS`, `BIMODAL_SEP`, `BIMODAL_BC`, `BIMODAL_DIP_P`, `SUB_DIST`, `UNIT`, `UNIT_PREVALENCE`, `PREVALENCE_DICT`, `BEST_UNIT`, `N_CANDIDATE`, `N_TARGET`, `CAND_DECILES`, `TARG_DECILES`, `KS_STAT`, `KS_MLOGP`, `KS_PASS`, `T_STAT`, `T_MLOGP`, `T_PASS`, `MAD_DIST`, `MAD_THRESHOLD`, `MAD_PASS`, `OUTCOME`, `NOTES`. +A `split_eval_{tag}.png` decision-tree figure is saved to `--dump-dir` for every TEST_NAME. + +Columns: `TEST_NAME`, `BIMODAL_STATUS`, `BIMODAL_SEP`, `BIMODAL_BC`, `BIMODAL_DIP_P`, `SCORE_GLOBAL`, `SCORE_SPLIT`, `SCORE_IMPROVEMENT`, `SUB_DIST`, `UNIT`, `UNIT_PREVALENCE`, `PREVALENCE_DICT`, `BEST_UNIT`, `N_CANDIDATE`, `N_TARGET`, `CAND_DECILES`, `TARG_DECILES`, `KS_STAT`, `KS_MLOGP`, `KS_PASS`, `T_STAT`, `T_MLOGP`, `T_PASS`, `MAD_DIST`, `MAD_THRESHOLD`, `MAD_PASS`, `OUTCOME`, `NOTES`. + +- `SCORE_GLOBAL`: best KS statistic achieved across all units on the full candidate distribution (lower = better fit) +- `SCORE_SPLIT`: mean of the best KS statistics for the low and high sub-distributions +- `SCORE_IMPROVEMENT`: `(SCORE_GLOBAL − SCORE_SPLIT) / SCORE_GLOBAL` — relative improvement from splitting ### No-data pass → `no_data_results.tsv` -TEST_NAMEs with `CATEGORY == NO_DATA`. No engine is run; unit is left blank. +TEST_NAMEs with `CATEGORY == NO_DATA`. No engine is run. The result is enriched with OMOP unit table information; a canonical unit is injected where the OMOP concept has category SINGLE or EQUIVALENT. + +Columns: `TEST_NAME`, `COUNT`, `OMOP_CONCEPT_ID`, `OMOP_QUANTITY`, `CATEGORY`, `N_UNITS`, `UNITS`, `CONVERSIONS`, `OMOP_TOTAL_N`, `UNIT`, `PREVALENCE`. + +- `CATEGORY`: OMOP unit category (`SINGLE`, `EQUIVALENT`, `MULTIPLE`, or NA) +- `UNIT`: canonical unit from the OMOP table if available, otherwise blank +- `PREVALENCE`: fraction of OMOP concept records that are no-unit (`COUNT / OMOP_TOTAL_N`) -Columns: `TEST_NAME`, `UNIT` +After writing, a breakdown is printed: +- no OMOP — TEST_NAMEs with no concept ID +- OMOP, unit injected — concept has SINGLE/EQUIVALENT category +- OMOP, no unit — concept mapped but MULTIPLE or unknown unit ### Unified output → `injection_results.tsv` @@ -122,7 +155,11 @@ Merge of the unambiguous and ambiguous results with a `TYPE` column (`unambiguou ### Coverage check -After all three passes, a checksum validates that the union of the three output files equals the full set of TEST_NAMEs in `plot_name_level.tsv`, with no overlaps and no missing entries. +After all three passes, a checksum validates that the union of the three output files equals the full set of TEST_NAMEs in `plot_name_level.tsv`, with no overlaps and no missing entries. Skipped in `--test` mode. + +### Assignment summary + +Printed at the end of `--inject`. Shows, for each category (UNAMBIGUOUS, AMBIGUOUS, NO_DATA) and in total, how many TEST_NAMEs and measurements received a unit (PASS rows), broken out for all TEST_NAMEs and the OMOP-mapped subset. --- @@ -164,6 +201,8 @@ Both are computed in the space (linear or log) where a 2-component GMM achieves | ≥ threshold | — | `unimodal` | | < threshold | ≥ 0.555 | `bimodal` — split into low/high | | < threshold | < 0.555 | `bimodal_cautious` — split, modes overlap | -| — | — | `skipped` — pre-check passed; bimodality not tested | +| — | — | `skipped` — pre-check passed and split not preferred | + +`split_by_score` is a separate label (not dip-test-derived) assigned when the split is triggered by score improvement (`SCORE_IMPROVEMENT > --split-threshold` and the two halves favour different units), regardless of dip test outcome. A diagnostic plot (`bimodal_{tag}.png`) is saved to `--dump-dir`. diff --git a/scripts/injection/explore_test_name.py b/scripts/injection/explore_test_name.py index ef33366..39f2aaa 100644 --- a/scripts/injection/explore_test_name.py +++ b/scripts/injection/explore_test_name.py @@ -945,18 +945,6 @@ def main(): omop_tbl = load_omop_unit_table(args.parquet, args.omop_unit_table) omop_cat = omop_tbl.set_index("OMOP_CONCEPT_ID")["CATEGORY"] - def _plot_category(row): - if row["CATEGORY"] != "NO_DATA": - return row["CATEGORY"] - oid = row.get("OMOP_CONCEPT_ID") - if pd.isna(oid): - return "NO_DATA (no OMOP)" - cat = omop_cat.get(oid) - if cat in ("SINGLE", "EQUIVALENT"): - return "NO_DATA (OMOP unit)" - return "NO_DATA (OMOP only)" - - plot_name["PLOT_CATEGORY"] = plot_name.apply(_plot_category, axis=1) make_scatter_plot(plot_name) print_summary(plot_name, args.prevalence_threshold) dump_summary_md(plot_name, args.prevalence_threshold, args.min_count) From 9dd55bb0b1239b15f8df075924992e736f98ede9 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 17:07:07 +0300 Subject: [PATCH 08/20] README: document unit injection pipeline and NO_DATA handling Co-Authored-By: Claude Sonnet 4.6 --- README.md | 20 ++++++++++++++++++++ 1 file changed, 20 insertions(+) diff --git a/README.md b/README.md index f2a068f..6565bf7 100644 --- a/README.md +++ b/README.md @@ -69,6 +69,26 @@ The raw to output column mapping is as follows: ![Summary of the wdl pipeline](./kanta_pipeline.png) +# UNIT INJECTION + +Many lab records carry a numeric value but no unit (the `MEASUREMENT_UNIT_PRE_FIX` field is NULL). The unit injection pipeline ([`scripts/injection/`](/scripts/injection/)) identifies these records and, where possible, assigns a unit by comparing their value distribution against records of the same `TEST_NAME` that already have a unit. + +Each `TEST_NAME` is classified into one of three categories based on the amount of reference data available (records that have both a value and a unit): + +| Category | Condition | How a unit is assigned | +|---|---|---| +| `UNAMBIGUOUS` | One unit accounts for ≥ threshold% of reference records | Distribution comparison against that dominant unit via KS / t / MAD tests | +| `AMBIGUOUS` | Multiple units present; no single one dominates | Per-unit comparison, optionally after splitting a bimodal distribution | +| `NO_DATA` | Fewer than `--min-target-n` reference records with any unit | No engine run; unit rescued via OMOP (see below) | + +## NO_DATA handling + +`NO_DATA` TEST_NAMEs have too little reference data for a statistical distribution comparison. Instead, they are enriched using the [OMOP unit table](/scripts/injection/omop_unit_table.tsv): if the OMOP concept mapped to a `NO_DATA` test has category `SINGLE` (only one unit ever observed) or `EQUIVALENT` (multiple units but all mutually convertible), the canonical OMOP unit is injected directly. Tests with OMOP category `MULTIPLE` or with no OMOP mapping receive no unit. + +Results are written to `no_data_results.tsv`. At the active 98% threshold (~500 min-count), ~28% of TEST_NAMEs (≈202) fall into this category, representing ~3.5% of measurements. + +For full details on the injection engine, bimodality detection, and output columns, see the [injection README](/scripts/injection/README.md). + # MERGE OF RAW DATA Inputs reports and responses are sorted over the same keys and merged From d898d32e9c6abff3230ab91041a7f58b826a8902 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 23:47:57 +0300 Subject: [PATCH 09/20] working html website, now workign on new version --- scripts/injection/build_site.py | 394 +++++++ scripts/injection/data/assignment_summary.md | 11 + scripts/injection/data/injection_results.tsv | 419 +++++++ scripts/injection/data/plot_name_level.tsv | 1026 ----------------- scripts/injection/data/summary_table.md | 12 +- .../data/test_names_exploration_scatter.png | Bin 87646 -> 111788 bytes scripts/injection/explore_test_name.py | 164 ++- scripts/injection/html/doc.html | 268 +++++ scripts/injection/html/index.html | 203 ++++ scripts/injection/injection_engine.py | 95 +- scripts/injection/parquet/build.sh | 35 + scripts/injection/plot_exploration.py | 3 +- 12 files changed, 1501 insertions(+), 1129 deletions(-) create mode 100644 scripts/injection/build_site.py create mode 100644 scripts/injection/data/assignment_summary.md create mode 100644 scripts/injection/data/injection_results.tsv delete mode 100644 scripts/injection/data/plot_name_level.tsv create mode 100644 scripts/injection/html/doc.html create mode 100644 scripts/injection/html/index.html create mode 100644 scripts/injection/parquet/build.sh diff --git a/scripts/injection/build_site.py b/scripts/injection/build_site.py new file mode 100644 index 0000000..d682991 --- /dev/null +++ b/scripts/injection/build_site.py @@ -0,0 +1,394 @@ +#!/usr/bin/env python3 +""" +build_site.py + +Generate a local HTML site from injection pipeline outputs. + +Usage: + python3 build_site.py [--out-dir PATH] + +Reads from {out_dir}/data/ and {out_dir}/plots/, writes index.html and doc.html +to {out_dir}/. Pass --out-dir to match what you used with explore_test_name.py. +""" + +import argparse +import json +from pathlib import Path + +import markdown +import pandas as pd + + +# --------------------------------------------------------------------------- +# Column label overrides and preferred display order. +# Columns not listed here are appended after these in their original TSV order. +# --------------------------------------------------------------------------- + +COL_LABELS = { + "TEST_NAME": "Test name", + "TYPE": "Type", + "CUTOFF": "Cutoff", + "OUTCOME": "Outcome", + "UNIT": "Unit", + "UNIT_PREVALENCE": "Unit prev (%)", + "N_CANDIDATE": "N cand", + "N_TARGET": "N target", + "KS_STAT": "KS stat", + "KS_MLOGP": "KS −log10p", + "KS_PASS": "KS pass", + "T_STAT": "T stat", + "T_MLOGP": "T −log10p", + "T_PASS": "T pass", + "MAD_DIST": "MAD dist", + "MAD_THRESHOLD": "MAD thr", + "MAD_PASS": "MAD pass", + "NOTES": "Notes", +} + +COL_ORDER = list(COL_LABELS.keys()) + +# Pixel widths for columns that are inherently short +COL_WIDTHS = { + "TYPE": 80, + "CUTOFF": 80, + "OUTCOME": 75, + "KS_PASS": 70, + "T_PASS": 70, + "MAD_PASS": 70, + "KS_STAT": 75, + "KS_MLOGP": 85, + "T_STAT": 75, + "T_MLOGP": 85, + "MAD_DIST": 80, + "MAD_THRESHOLD": 80, + "UNIT_PREVALENCE": 90, + "N_CANDIDATE": 85, + "N_TARGET": 75, + "SUB_DIST": 70, +} + +# Columns to drop entirely from the landing table (reserved for per-test pages) +EXCLUDE_COLS = { + "SUB_DIST", + "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", + "SCORE_GLOBAL", "SCORE_SPLIT", "SCORE_IMPROVEMENT", + "CAND_DECILES", "TARG_DECILES", + "PREVALENCE_DICT", +} + + +# --------------------------------------------------------------------------- +# HTML templates (use __MARKER__ substitution to avoid Python/JS brace clash) +# --------------------------------------------------------------------------- + +_INDEX = """ + + + + + Unit injection results + + + + + +

+
+

Unit injection results

+ + __SCATTER_BLOCK__ + + __SUMMARY_SECTION__ + +

Per-column search: text columns support regex (e.g. ^PASS$, + mmol). Numeric columns support comparisons: <3, + >=20, !=0. The global box top-right searches all columns with regex.

+ +
+ + + __FOOTERS__ + __HEADERS__ + + +
+
+ + + + + + + +""" + +_DOC = """ + + + + + Documentation — unit injection + + + + + +
+ __README_HTML__ + + +""" + + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + +def _find_scatter(data_dir: Path, out_dir: Path) -> str: + p = data_dir / "test_names_exploration_scatter.png" + if p.exists(): + return str(p.resolve().relative_to(out_dir.resolve())) + return "" + + +def _md_to_html(path: Path) -> str: + if not path.exists(): + return "" + return markdown.markdown(path.read_text(), extensions=["tables", "fenced_code"]) + + +def _summary_section(data_dir: Path) -> str: + parts = [] + for fname, title in (("summary_table.md", "Category summary"), + ("assignment_summary.md", "Assignment summary")): + html = _md_to_html(data_dir / fname) + if html: + parts.append(f'

{title}

{html}') + if not parts: + return "" + return '
' + "".join(parts) + "
" + + +def _scatter_block(rel_path: str) -> str: + if not rel_path: + return '

Scatter plot not found.

' + return (f'
' + f'Scatter: TEST_NAMEs by count and prevalence' + f'
') + + +# --------------------------------------------------------------------------- +# Page builders +# --------------------------------------------------------------------------- + +def build_index(out_dir: Path, data_dir: Path, + inj_path: Path = None, scatter_override: str = None) -> None: + inj = inj_path or data_dir / "injection_results.tsv" + if not inj.exists(): + print(f"Warning: {inj} not found — table will be empty") + df = pd.DataFrame(columns=COL_ORDER) + else: + df = pd.read_csv(inj, sep="\t", na_values=["NA"]) + + # COL_ORDER first (if present), then any remaining TSV columns, minus excluded ones + ordered = [c for c in COL_ORDER if c in df.columns] + remaining = [c for c in df.columns if c not in set(ordered) and c not in EXCLUDE_COLS] + all_cols = ordered + remaining + cols = [(c, COL_LABELS.get(c, c)) for c in all_cols] + + df_out = df[all_cols].copy().fillna("") + if "CUTOFF" in df_out.columns: + df_out["CUTOFF"] = df_out["CUTOFF"].replace(float("inf"), "∞") + rows = df_out.to_dict(orient="records") + + # Which column indices hold numeric data + numeric_set = {i for i, c in enumerate(all_cols) + if pd.api.types.is_numeric_dtype(df[c])} + + # Build columns array with widths embedded; mark wide columns for CSS + wide_cols = {"TEST_NAME", "NOTES", "UNIT"} + def _col_def(k, l): + d = {"data": k, "title": l} + if k in COL_WIDTHS: + d["width"] = f"{COL_WIDTHS[k]}px" + if k in wide_cols: + d["className"] = "col-wide" + return d + + headers = "".join(f"{label}" for _, label in cols) + footers = "".join(f'' + for _, label in cols) + data_json = json.dumps(rows, allow_nan=False) + columns_json = json.dumps([_col_def(k, l) for k, l in cols]) + numeric_cols_json = json.dumps({i: True for i in numeric_set}) + outcome_idx = next((i for i, (k, _) in enumerate(cols) if k == "OUTCOME"), 3) + scatter_path = scatter_override if scatter_override is not None else _find_scatter(data_dir, out_dir) + + html = (_INDEX + .replace("__SCATTER_BLOCK__", _scatter_block(scatter_path)) + .replace("__SUMMARY_SECTION__", _summary_section(data_dir)) + .replace("__HEADERS__", headers) + .replace("__FOOTERS__", footers) + .replace("__DATA_JSON__", data_json) + .replace("__COLUMNS_JSON__", columns_json) + .replace("__NUMERIC_COLS_JSON__", numeric_cols_json) + .replace("__OUTCOME_COL_IDX__", str(outcome_idx))) + + out = out_dir / "index.html" + out.write_text(html, encoding="utf-8") + print(f"Wrote {out} ({len(rows)} rows)") + + +def build_doc(out_dir: Path, readme_path: Path) -> None: + text = readme_path.read_text() + readme_html = markdown.markdown(text, extensions=["tables", "fenced_code"]) + html = _DOC.replace("__README_HTML__", readme_html) + out = out_dir / "doc.html" + out.write_text(html) + print(f"Wrote {out}") + + +# --------------------------------------------------------------------------- +# CLI +# --------------------------------------------------------------------------- + +def main(): + p = argparse.ArgumentParser( + description="Build HTML site from injection pipeline outputs.", + formatter_class=argparse.ArgumentDefaultsHelpFormatter, + ) + p.add_argument("--data-dir", default=".", metavar="PATH", + help="Directory containing all pipeline outputs (TSVs, PNGs, MDs)") + p.add_argument("--out-dir", default=None, metavar="PATH", + help="Directory where index.html and doc.html are written " + "(default: same as --data-dir)") + p.add_argument("--injection-results", default=None, metavar="PATH", + help="Override path for injection_results.tsv") + p.add_argument("--scatter", default=None, metavar="PATH", + help="Scatter plot filename relative to --data-dir (default: auto-detected)") + p.add_argument("--readme", default=None, metavar="PATH", + help="Path to README.md (default: README.md next to this script)") + args = p.parse_args() + + data_dir = Path(args.data_dir) + out_dir = Path(args.out_dir) if args.out_dir else Path(".") + readme = Path(args.readme) if args.readme else Path(__file__).parent / "README.md" + inj = Path(args.injection_results) if args.injection_results else None + scatter = args.scatter + + build_index(out_dir, data_dir, inj_path=inj, scatter_override=scatter) + build_doc(out_dir, readme) + + +if __name__ == "__main__": + main() diff --git a/scripts/injection/data/assignment_summary.md b/scripts/injection/data/assignment_summary.md new file mode 100644 index 0000000..d82bd36 --- /dev/null +++ b/scripts/injection/data/assignment_summary.md @@ -0,0 +1,11 @@ +``` + +Assignment summary (successfully assigned) + + UNAMBIGUOUS AMBIGUOUS NO_DATA TOTAL + names meas names meas names meas names meas + ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- +All 10/10 2,874,565/2,874,565 10/10 5,300,918/5,300,918 26/140 284,033/1,062,191 46/160 8,459,516/9,237,674 +OMOP-mapped 10/10 2,874,565/2,874,565 10/10 5,300,918/5,300,918 26/61 284,033/797,892 46/81 8,459,516/8,973,375 + ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- +``` diff --git a/scripts/injection/data/injection_results.tsv b/scripts/injection/data/injection_results.tsv new file mode 100644 index 0000000..7a02839 --- /dev/null +++ b/scripts/injection/data/injection_results.tsv @@ -0,0 +1,419 @@ +TYPE TEST_NAME BIMODAL_STATUS BIMODAL_SEP BIMODAL_BC BIMODAL_DIP_P SUB_DIST UNIT UNIT_PREVALENCE PREVALENCE_DICT BEST_UNIT N_CANDIDATE N_TARGET CAND_DECILES TARG_DECILES KS_STAT KS_MLOGP KS_PASS T_STAT T_MLOGP T_PASS MAD_DIST MAD_THRESHOLD MAD_PASS OUTCOME NOTES +unambiguous b-eryt NA NA NA NA all e12/l 99.99 {e12/l:99.99,%:0.01,e9/l:0} e12/l 2702234 8026175 [3.25,3.63,3.9,4.1,4.28,4.44,4.6,4.79,5.04] [3.3,3.7,3.99,4.2,4.35,4.5,4.67,4.83,5.1] 0.05101 300 PASS -81.68 300 FAIL 0.07 1.35 PASS PASS PASS_at_KS_(2/3) +unambiguous b-leuk NA NA NA NA all e9/l 100 {e9/l:100,g/l:0,form:0} e9/l 2610059 7601140 [4.4,5.2,5.8,6.4,7,7.7,8.6,9.7,11.7] [4.3,5.1,5.7,6.3,6.9,7.5,8.3,9.5,11.5] 0.03003 300 PASS 40.72 300 FAIL 0.1 4.8 PASS PASS PASS_at_KS_(2/3) +unambiguous b-trom NA NA NA NA all e9/l 100 {e9/l:100,%:0,form:0} e9/l 2413303 7894206 [150,183,207,227,246,267,291,324,381] [154,187,209,229,247,267,291,321,374] 0.01194 228.8 PASS 15.29 52.07 FAIL 1 156 PASS PASS PASS_at_KS_(2/3) +unambiguous p-inr NA NA NA NA all inr 99.17 {inr:99.17,ng:0.52,form:0.31} inr 1094306 73174 [1.5,1.9,2.1,2.3,2.4,2.6,2.7,3,3.3] [1,1.3,1.9,2.1,2.3,2.4,2.6,2.8,3.2] 0.1414 300 PASS 69.28 300 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous b-hb NA NA NA NA all g/l 99.99 {g/l:99.99,e9/l:0.01,form:0} g/l 895512 10047206 [106,116,124,129,133,137,142,147,154] [99,110,119,125,130,135,140,145,152] 0.07401 300 PASS 177.8 300 FAIL 3 39 PASS PASS PASS_at_KS_(2/3) +unambiguous e-mcv NA NA NA NA all fl 99.96 {fl:99.96,%:0.03,pg:0} fl 863209 10019368 [84.6,87,89,90,91,93,94,96,99] [85,87,89,90,91,93,94,96,99] 0.009422 61 PASS -18.11 72.59 FAIL 0 9 PASS PASS PASS_at_KS_(2/3) +unambiguous e-mch NA NA NA NA all pg 99.78 {pg:99.78,pg/cell:0.21,fl:0} pg 859269 10022306 [27,29,29,30,30,31,31,32,33] [28,29,29,30,30,31,31,32,33] 0.01713 201.5 PASS -5.64 7.768 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-gfreepi NA NA NA NA all ml/min/173m2 99.11 {ml/min/173m2:99.11,form:0.89} ml/min/173m2 752397 1889100 [39,51,59,67,74,80,86,92,101] [38,54,65,73,80,86,91,97,106] 0.09026 300 PASS 0.6265 0.2749 PASS 6 48 PASS PASS PASS_at_KS_(3/3) +unambiguous p-k NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/mol:0,nmol/l:0} mmol/l 701228 6736993 [3.5,3.7,3.8,3.9,4,4.1,4.2,4.3,4.5] [3.5,3.7,3.8,3.9,4,4.1,4.2,4.3,4.6] 0.04774 300 PASS 8.691 17.45 FAIL 0 0.9 PASS PASS PASS_at_KS_(2/3) +unambiguous b-neut NA NA NA NA all e9/l 98.61 {e9/l:98.61,%:1.39} e9/l 678979 1796762 [1.7,2.32,2.81,3.27,3.74,4.29,4.97,5.95,7.77] [1.68,2.28,2.73,3.19,3.63,4.17,4.8,5.74,7.5] 0.02295 225.1 PASS 26.64 155.6 FAIL 0.11 3.87 PASS PASS PASS_at_KS_(2/3) +unambiguous p-na NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0,1:0} mmol/l 615417 6700235 [134,137,138,139,140,141,142,142,144] [134,136,138,139,140,140,141,142,143] 0.08943 300 PASS 110.5 300 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous u-ph NA NA NA NA all form 98.78 {form:98.78,ph:1.22} form 614126 18003 [5.5,5.5,6,6,6.5,7,7,7,7.5] [5,5,5,5.5,6,6,6.5,7,7] 0.2368 300 PASS 78.83 300 FAIL 0.5 3 PASS PASS PASS_at_KS_(2/3) +unambiguous p-krea NA NA NA NA all umol/l 99.98 {umol/l:99.98,umol:0.02,ml/min/173m2:0} umol/l 597169 7087388 [56,63,68,73,79,86,94,106,128] [53,60,65,70,76,82,90,104,135] 0.05594 300 PASS -81.6 300 FAIL 3 45 PASS PASS PASS_at_KS_(2/3) +unambiguous p-alat NA NA NA NA all u/l 100 {u/l:100,umol/l:0,mmol/l:0} u/l 484108 4339404 [13,16,18,21,24,27,32,40,56] [13,16,18,21,24,28,33,42,61] 0.01793 121.3 PASS -61.36 300 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) +unambiguous e-rdw NA NA NA NA all % 100 {%:100} % 445075 5838138 [13,13,13,14,14,14,15,15,17] [12.6,13,13,13.5,14,14,15,16,17] 0.04145 300 PASS -18.65 76.9 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-gluk NA NA NA NA all mmol/l 99.96 {mmol/l:99.96,nmol/l:0.04,mmol/:0} mmol/l 377861 1527267 [5.2,5.5,5.7,5.9,6.1,6.4,6.7,7.2,8.2] [5,5.3,5.5,5.7,5.8,6.1,6.4,6.9,7.8] 5.211e-06 -0 FAIL -0.9174 0.445 PASS 0.3 1.5 PASS PASS PASS_at_T_(2/3) +unambiguous b-baso NA NA NA NA all e9/l 98.99 {e9/l:98.99,%:1.01} e9/l 358577 1025695 [0.01,0.02,0.03,0.03,0.04,0.04,0.05,0.06,0.08] [0,0.02,0.02,0.03,0.04,0.04,0.05,0.07,0.1] 0.06985 300 PASS 17 64.07 FAIL 0 0.06 PASS PASS PASS_at_KS_(2/3) +unambiguous b-hba1c NA NA NA NA all mmol/mol 99.68 {mmol/mol:99.68,mmol/m:0.17,mmol:0.07} mmol/mol 356117 1619587 [34,37,38,40,42,44,47,52,62] [33,35,37,38,40,42,44.8,50,60] 0.1172 300 PASS 68.38 300 FAIL 2 15 PASS PASS PASS_at_KS_(2/3) +unambiguous p-crp NA NA NA NA all mg/l 100 {mg/l:100,mg/ml:0,alle:0} mg/l 329485 3909221 [2,4,6,10,15,23,37,58,99] [3,5,8,13,21,34,52,81,133] 0.08114 300 PASS -122 300 FAIL 6 54 PASS PASS PASS_at_KS_(2/3) +unambiguous b-erblast NA NA NA NA all e9/l 100 {e9/l:100} e9/l 314346 313463 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.003567 1.435 PASS 8.538 16.86 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous e-mchc NA NA NA NA all g/l 100 {g/l:100,e9/l:0,form:0} g/l 306131 6813807 [314,320,326,330,333,336,339,343,348] [315,321,325,328,331,333,337,340,346] 0.07143 300 PASS 35.87 280.8 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-kol-ldl NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0,mmoil/l:0} mmol/l 300160 1258918 [1.6,2,2.2,2.5,2.8,3.1,3.4,3.78,4.2] [1.5,1.8,2.1,2.38,2.6,2.9,3.2,3.6,4.1] 0.07917 300 PASS 78.61 300 FAIL 0.2 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-kol NA NA NA NA all mmol/l 100 {mmol/l:100,mmol:0,mmol/:0} mmol/l 246075 1160366 [3.4,3.8,4.1,4.5,4.8,5.1,5.4,5.8,6.3] [3.2,3.6,4,4.3,4.6,4.9,5.2,5.6,6.2] 0.08252 300 PASS 72.12 300 FAIL 0.2 2.4 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-trigly NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0} mmol/l 239400 1104071 [0.7,0.85,1,1.1,1.25,1.41,1.67,1.99,2.55] [0.7,0.82,0.96,1.1,1.21,1.4,1.6,1.89,2.4] 0.03363 193.1 PASS 21.77 104.2 FAIL 0.04 1.17 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-kol-hdl NA NA NA NA all mmol/l 100 {mmol/l:100,mml/l:0,mmol:0} mmol/l 235506 1110652 [0.96,1.1,1.2,1.31,1.42,1.54,1.68,1.85,2.11] [0.95,1.09,1.2,1.3,1.4,1.5,1.63,1.8,2.03] 0.03251 178.1 PASS 30.77 206.9 FAIL 0.02 0.84 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-gfre NA NA NA NA all ml/min/173m2 99.63 {ml/min/173m2:99.63,form:0.37,mi/min/173m2:0} ml/min/173m2 216785 1096392 [42,54,63,71,77,83,88,93,102] [41,57,67,75,82,87,92,98,106.1] 0.08308 300 PASS -56.47 300 FAIL 5 45 PASS PASS PASS_at_KS_(2/3) +unambiguous p-t4-v NA NA NA NA all pmol/l 100 {pmol/l:100,nmol/l:0,pmo/l:0} pmol/l 203419 904186 [12,13,14,14.9,15.5,16.2,17,18.1,19.9] [12,13,14,14.7,15.2,16,17,18,19.5] 0.0401 231.7 PASS 21.9 105.5 FAIL 0.3 5.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-afos NA NA NA NA all u/l 100 {u/l:100,umol/l:0} u/l 179506 2452551 [47,55,61,67,74,81,91,106,134] [49,57,64,70,77,85,95,111,151] 0.04779 300 PASS -42.81 300 FAIL 3 57 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-ph NA NA NA NA all ph 99.15 {ph:99.15,form:0.64,1:0.21} ph 174741 931 [7.3,7.33,7.35,7.37,7.38,7.39,7.41,7.42,7.45] [7.31,7.34,7.36,7.37,7.38,7.39,7.4,7.42,7.44] 0.06548 3.169 PASS -1.378 0.7736 PASS 0 0.09 PASS PASS PASS_at_KS_(3/3) +unambiguous b-erybla NA NA NA NA all e9/l 100 {e9/l:100} e9/l 169159 1041960 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.02442 75.13 PASS 19.22 81.51 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-eryt NA NA NA NA all e6/l 98.22 {e6/l:98.22,u/field:0.92,form:0.43} e6/l 157713 273727 [1,2,4,5,8,13,23,52,193] [2.2,4,6,7.8,10,13,19,30.9,86.7] 0.1553 300 PASS -5.124 6.523 FAIL 2 19.5 PASS PASS PASS_at_KS_(2/3) +unambiguous u-leuk NA NA NA NA all e6/l 99.11 {e6/l:99.11,u/field:0.6,/sunf:0.27} e6/l 156801 294204 [1,1,2,4,7,13,29,88,402] [0.8,1,2,3,5,8,16.8,46,216] 0.07322 300 PASS -3.965 4.134 FAIL 2 12 PASS PASS PASS_at_KS_(2/3) +unambiguous b-la NA NA NA NA all mm/h 99.95 {mm/h:99.95,mmol:0.03,form:0.01} mm/h 156217 1232795 [2,5,6,8,10,15,21,28,41] [2,4,5,7,9,12,16,25,38] 0.06215 300 PASS 1.287 0.7029 PASS 1 18 PASS PASS PASS_at_KS_(3/3) +unambiguous u-lier NA NA NA NA all e6/l 100 {e6/l:100,u/field:0} e6/l 155357 195506 [0,0,0,0,0,0,0,1,3] [0,0,0,0,0,0,0.13,0.81,1.22] 0.09197 300 PASS 48.69 300 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-levyep NA NA NA NA all e6/l 99.53 {e6/l:99.53,u/field:0.47} e6/l 135481 81771 [0,0,0,0,0,1,2,4,11] [0,0,0,0,1,1,2,4,9] 0.09894 300 PASS 5.548 7.539 FAIL 1 3 PASS PASS PASS_at_KS_(2/3) +unambiguous u-pienep NA NA NA NA all e6/l 100 {e6/l:100} e6/l 135163 65516 [0,0,0,0,0,1,1,2,4] [0,0,0,0,0,0.9,1,2,4] 0.05883 132.5 PASS -1.225 0.6567 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous cb-ph NA NA NA NA all ph 100 {ph:100} ph 104918 9565 [7.35,7.38,7.39,7.41,7.42,7.43,7.44,7.45,7.47] [7.35,7.37,7.39,7.41,7.42,7.43,7.44,7.46,7.48] 0.02779 5.587 PASS -0.9305 0.4533 PASS 0 0.09 PASS PASS PASS_at_KS_(3/3) +unambiguous p-gt NA NA NA NA all u/l 100 {u/l:100,mg/ml:0,mg/l:0} u/l 103122 716550 [15,20,26,33,44,58,78,114,200] [15,19,23,29,36,47,65,100,195] 0.07536 300 PASS 5.969 8.621 FAIL 8 57 PASS PASS PASS_at_KS_(2/3) +unambiguous u-krea NA NA NA NA all mmol/l 98.91 {mmol/l:98.91,umol/l:1.09,g/l:0} mmol/l 102588 389195 [3.3,4.4,5.3,6.3,7.4,8.7,10.3,12.8,18.2] [3.1,4.1,4.9,5.8,6.8,7.9,9.3,11.1,14.2] 0.06325 282.1 PASS 71.26 300 FAIL 0.6 7.8 PASS PASS PASS_at_KS_(2/3) +unambiguous hdl/kol NA NA NA NA all % 100 {%:100} % 89962 130585 [21,25,28,30,33,36,39,42,47] [21,24,27,30,32,35,38,41,46] 0.033 50.09 PASS 15.48 53.27 FAIL 1 21 PASS PASS PASS_at_KS_(2/3) +unambiguous p-psa NA NA NA NA all ug/l 100 {ug/l:100,µh/l:0} ug/l 85734 353554 [0.36,0.61,0.89,1.2,1.62,2.2,3.02,4.4,6.9] [0.25,0.52,0.82,1.2,1.74,2.54,3.8,5.9,10.6] 0.06999 293.6 PASS -32.53 231.1 FAIL 0.12 4.08 PASS PASS PASS_at_KS_(2/3) +unambiguous fb-leuk NA NA NA NA all e9/l 100 {e9/l:100} e9/l 78470 326274 [4.5,5.2,5.7,6.2,6.7,7.3,8,8.9,10.4] [4.5,5.1,5.6,6.1,6.6,7.2,7.9,8.8,10.4] 0.01482 11.77 PASS 0.9066 0.4382 PASS 0.1 4.2 PASS PASS PASS_at_KS_(3/3) +unambiguous p-kol-ldl NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 76361 340811 [1.3,1.5,1.7,2,2.2,2.5,2.9,3.3,3.8] [1.3,1.5,1.8,2,2.3,2.6,2.9,3.3,3.8] 0.01497 11.84 PASS -8.846 18.04 FAIL 0.1 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous b-tromb NA NA NA NA all e9/l 100 {e9/l:100} e9/l 75012 323035 [168,193,212,229,246,264,286,314,359] [163,190,210,228,245,263,284,313,361] 0.01738 15.68 PASS 4.206 4.584 FAIL 1 144 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ferrit NA NA NA NA all ug/l 100 {ug/l:100} ug/l 65282 414832 [12,19,28,39,54,77,111,168,282] [14,23,34,48,67,96,142,224,419] 0.06433 202.6 PASS -32.04 224.1 FAIL 13 147 PASS PASS PASS_at_KS_(2/3) +unambiguous p-kol NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 63596 235312 [3,3.4,3.7,4,4.3,4.6,4.9,5.3,5.9] [3,3.4,3.7,4,4.3,4.6,5,5.4,5.9] 0.02577 28.58 PASS -10.74 26.15 FAIL 0 2.4 PASS PASS PASS_at_KS_(2/3) +unambiguous p-kol-hdl NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 61142 221234 [0.97,1.09,1.2,1.3,1.4,1.51,1.64,1.8,2.03] [0.96,1.09,1.2,1.3,1.4,1.51,1.63,1.79,2.02] 0.006651 1.542 PASS 3.266 2.963 FAIL 0 0.84 PASS PASS PASS_at_KS_(2/3) +unambiguous p-trigly NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 60090 219531 [0.72,0.88,1,1.12,1.28,1.44,1.66,1.97,2.51] [0.7,0.84,0.97,1.1,1.24,1.4,1.62,1.92,2.49] 0.02559 26.55 PASS 3.328 3.058 FAIL 0.04 1.17 PASS PASS PASS_at_KS_(2/3) +unambiguous u-alb NA NA NA NA all mg/l 100 {mg/l:100,mg/ml:0,mg/mmol:0} mg/l 54491 245848 [3,4,5,7,9.4,14,24.3,45.9,123] [3.7,5,6,9,13,21.5,42,102,337] 0.09064 300 PASS -43.91 300 FAIL 3.6 27 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-be NA NA NA NA all mmol/l 99.98 {mmol/l:99.98,ml:0.01,%:0} mmol/l 52627 328149 [-7.2,-4.9,-3.7,-2.8,-2.2,-1.6,-1.1,-0.7,-0.3] [-4.6,-2.4,-0.8,0.2,1,1.9,2.9,4.2,6.3] 0.5981 300 FAIL -216.4 300 FAIL 3.2 7.5 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-alb NA NA NA NA all g/l 100 {g/l:100,%:0} g/l 51547 870387 [26,30,33,34.4,36,37,38,39.2,41] [25,29,32,34,35.6,37,38,39.4,41] 0.04602 89.32 PASS 17.96 71.18 FAIL 0.4 10.8 PASS PASS PASS_at_KS_(2/3) +unambiguous u-albkre NA NA NA NA all mg/mmol 100 {mg/mmol:100,g/mol:0} mg/mmol 51403 242629 [0.3,0.4,0.6,0.8,1.2,1.9,3.4,7,20.5] [0.3,0.5,0.7,1,1.6,2.9,6.2,16.1,60.6] 0.08722 280.5 PASS -1.503 0.8765 PASS 0.4 3.9 PASS PASS PASS_at_KS_(3/3) +unambiguous l-lymf(a) NA NA NA NA all % 100 {%:100} % 50542 588720 [14,19,22,26,28,31,34,38,44] [12,17,21,24,27,30,34,38,44] 0.04828 94.06 PASS 21.39 100.4 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +unambiguous u-gluk-o NA NA NA NA all estimate 99.32 {estimate:99.32,form:0.67,A:0.01} estimate 50039 123942 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01171 3.946 PASS 4.074 4.334 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous l-mono(a) NA NA NA NA all % 100 {%:100} % 49676 588958 [6,7,8,8,9,10,11,12,13] [6,7,8,8,9,10,11,12,13] 0.01509 8.768 PASS -0.3816 0.1532 PASS 0 6 PASS PASS PASS_at_KS_(3/3) +unambiguous l-eos(a) NA NA NA NA all % 100 {%:100} % 49313 92061 [0,1,2,2,2,3,4,5,6] [0,1,2,2,2,3,4,4,6] 0.0186 9.351 PASS 7.754 14.05 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous l-neut(a) NA NA NA NA all % 100 {%:100} % 48854 590444 [41,47,51,54,58,61,64,68,74] [41,48,52,55,59,62,66,70,77] 0.0498 96.99 PASS -20.59 93.1 FAIL 1 27 PASS PASS PASS_at_KS_(2/3) +unambiguous u-nitr-o NA NA NA NA all estimate 99.34 {estimate:99.34,form:0.66,A:0} estimate 48542 124895 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.0008223 -0 FAIL 3.955 4.116 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous l-baso(a) NA NA NA NA all % 100 {%:100} % 48061 93247 [0,0,0,1,1,1,1,1,1] [0,0,1,1,1,1,1,1,1] 0.1053 300 PASS -33.15 238.8 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 46427 126442 [-7.4,-5.3,-4,-3.1,-2.4,-1.8,-1.2,-0.7,-0.3] [-3.4,-0.8,0.3,1,1.7,2.4,3.2,4.2,5.9] 0.7185 300 FAIL -239 300 FAIL 4.1 5.4 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-b12-tc2 NA NA NA NA all pmol/l 100 {pmol/l:100,>35:0} pmol/l 46070 176282 [51,65,76,87,97,107,117,130,160] [52,66,76.7,86,95.1,105,114,124,138] 0.07646 185.4 PASS 24.8 134.4 FAIL 1.9 71.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-bil NA NA NA NA all umol/l 100 {umol/l:100} umol/l 45706 1372979 [5,6,7,8,9,11,13,17,26] [5,6,7,8,9,11,13,16.4,25] 0.03003 34.39 PASS -1.03 0.5186 PASS 0 9 PASS PASS PASS_at_KS_(3/3) +unambiguous u-suhtih NA NA NA NA all kg/l 99.91 {kg/l:99.91,ratio:0.09} kg/l 41978 4621 [1.009,1.011,1.013,1.015,1.016,1.018,1.02,1.022,1.025] [1.01,1.01,1.01,1.01,1.015,1.015,1.015,1.02,1.02] 0.2869 300 PASS 19.31 81.92 FAIL 0.001 0.015 PASS PASS PASS_at_KS_(2/3) +unambiguous p-probnp NA NA NA NA all ng/l 100 {ng/l:100} ng/l 41763 317468 [81,133,211,338,555,907,1400,2220,4148] [81,146,246,412,695,1144,1849,3080,6216] 0.06289 126.6 PASS -36.62 290.5 FAIL 140 1800 PASS PASS PASS_at_KS_(2/3) +unambiguous u-alb-o NA NA NA NA all estimate 99.75 {estimate:99.75,form:0.25,A:0} estimate 41443 115398 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.0002578 -0 FAIL 0.961 0.4729 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous u-eryt-o NA NA NA NA all estimate 99.32 {estimate:99.32,form:0.68,eru/ul:0} estimate 40464 103663 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01896 8.797 PASS 7.44 12.99 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-leuk-o NA NA NA NA all estimate 99.05 {estimate:99.05,form:0.86,u/field:0.05} estimate 39068 102815 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.04043 39.92 PASS 8.452 16.53 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous p-psa-v NA NA NA NA all ug/l 99.99 {ug/l:99.99,form:0.01,%:0} ug/l 38748 112760 [0.22,0.34,0.44,0.54,0.65,0.78,0.92,1.11,1.54] [0.23,0.34,0.45,0.56,0.69,0.8,1,1.24,1.7] 0.03829 36.44 PASS -14.73 48.34 FAIL 0.04 0.96 PASS PASS PASS_at_KS_(2/3) +unambiguous p-d-25 NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 38104 55698 [47,58,66,74,80,88,96,107,124] [47,57,64,71,77,84,93,103,120] 0.04497 39.47 PASS 12.91 37.36 FAIL 3 54 PASS PASS PASS_at_KS_(2/3) +unambiguous s-k/l-s-v NA NA NA NA all ratio 99.15 {ratio:99.15,1:0.69,mg/l:0.16} ratio 37831 2440 [0.17,0.77,1.02,1.21,1.4,1.63,2.01,3.43,14.3] [0.12,0.79,0.987,1.19,1.445,1.76,3.09,10,30.9] 0.09989 19.63 PASS 1.874 1.215 PASS 0.045 2.445 PASS PASS PASS_at_KS_(3/3) +unambiguous p-uraat NA NA NA NA all umol/l 98.74 {umol/l:98.74,mmol/l:1.26} umol/l 37337 226132 [246,288,322,353,383,416,450,492,549] [225,266,298,327,355,385,420,463,526] 0.09345 243.3 PASS 37.11 296.8 FAIL 28 234 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 36614 63821 [-6.7,-4.6,-3.3,-2.4,-1.6,-1,-0.6,-0.2,2] [-2.8,0,0.7,1.3,2,2.8,3.8,5.2,7.7] 0.6474 300 FAIL -155.1 300 FAIL 3.6 5.7 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-tfr NA NA NA NA all mg/l 100 {mg/l:100} mg/l 35728 152596 [2.1,2.5,2.9,3.2,3.6,4.1,4.8,5.8,7.5] [0.8,1.3,2.1,2.5,2.9,3.3,3.8,4.6,6.2] 0.2209 300 PASS 57.88 300 FAIL 0.7 3.9 PASS PASS PASS_at_KS_(2/3) +unambiguous p-gluk NA NA NA NA all mmol/l 99.96 {mmol/l:99.96,mmol:0.04,%:0} mmol/l 34995 1187642 [5,5.5,5.8,6,6.4,7,7.6,8.8,11.4] [5.1,5.5,5.8,6.2,6.6,7.1,7.8,8.8,10.8] 0.05953 104.5 PASS 3.159 2.8 FAIL 0.2 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-tnt NA NA NA NA all ng/l 99.98 {ng/l:99.98,ug/l:0.02} ng/l 32887 400470 [7,9,11,15,18,23,30,42,74] [7,9,12,15,19,25,34,51,105] 0.04291 48.34 PASS -29.16 185.5 FAIL 1 33 PASS PASS PASS_at_KS_(2/3) +unambiguous l-monos NA NA NA NA all % 99.4 {%:99.4,e9/l:0.6} % 31974 434312 [6,7,8,8,9,10,11,12,13] [5,7,7.4,8,9,10,10.1,11.7,13] 0.03102 24.6 PASS 2.538 1.953 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-ph NA NA NA NA all ph 100 {ph:100} ph 30367 986 [7.34,7.36,7.37,7.38,7.39,7.4,7.41,7.42,7.44] [7.38,7.4,7.41,7.42,7.43,7.43,7.44,7.45,7.47] 0.3802 123.9 FAIL 0.9998 0.4983 PASS 0.04 0.06 PASS PASS PASS_at_T_(2/3) +unambiguous ca++/7.40 NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 27423 98719 [1.18,1.2,1.2,1.22,1.23,1.25,1.27,1.3,1.33] [1.14,1.18,1.21,1.22,1.23,1.24,1.26,1.27,1.31] 0.1306 300 PASS 27.76 167.5 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous ca-ion NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 27272 99169 [1.18,1.2,1.21,1.23,1.24,1.26,1.28,1.3,1.32] [1.14,1.18,1.21,1.23,1.24,1.26,1.27,1.29,1.33] 0.1066 211.3 PASS 3.516 3.358 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous fe-folaat NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 27167 76563 [313.6,396.2,479,591,763,1023,1309,1617,2032] [354,452,568,727,968,1302,1580,1854,2290] 0.09833 168.5 PASS -31.8 219.1 FAIL 205 1626 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-folaat NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 26471 163828 [6.9,8.9,10.9,13.2,16.3,21,27.9,37.2,51] [7.5,9.7,11.9,14.2,17,20.8,25.9,32.9,42.44] 0.05394 57.34 PASS 11.64 30.51 FAIL 0.7 23.1 PASS PASS PASS_at_KS_(2/3) +unambiguous b-retik NA NA NA NA all e9/l 99.94 {e9/l:99.94,%:0.06} e9/l 26123 65705 [36.9,46,53.5,60.7,68,76.3,87.8,103.3,134.1] [37,47,54,61,68,76,86,101,130] 0.02002 6.213 PASS 1.564 0.9285 PASS 0 60 PASS PASS PASS_at_KS_(3/3) +unambiguous p-amyl NA NA NA NA all u/l 100 {u/l:100,umol/l:0} u/l 25904 342833 [29,37,43,49,54,60,68,79,100] [26,34,40,46,52,59,68,80,104] 0.04508 42.25 PASS -10.49 25 FAIL 2 51 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ca NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 25414 398611 [2.19,2.25,2.28,2.31,2.34,2.37,2.4,2.44,2.51] [2.21,2.27,2.31,2.34,2.37,2.4,2.44,2.47,2.53] 0.1137 268.8 PASS -28.26 172.6 FAIL 0.03 0.24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca-ion NA NA NA NA all mmol/l 100 {mmol/l:100,mmol:0} mmol/l 25366 460023 [1.15,1.19,1.21,1.22,1.24,1.25,1.27,1.3,1.34] [1.14,1.18,1.2,1.21,1.23,1.24,1.26,1.28,1.31] 0.08483 150.2 PASS 17.13 64.7 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous p-psa-suh NA NA NA NA all % 98.61 {%:98.61,form:1.12,ug/l:0.26} % 24327 93796 [0.22,8,12,15,18,20.6,24,28,33.4] [9,12,14,16.8,19,22,25,29,36] 0.1437 300 PASS -34.01 248.8 FAIL 1 21 PASS PASS PASS_at_KS_(2/3) +unambiguous l-neut NA NA NA NA all % 98.82 {%:98.82,e9/l:1.18,osuus:0} % 24285 378348 [3,5,26,44,51,56,60,65,72] [42,48,52,55.5,59,62,65.8,70,76] 0.2856 300 PASS -95.32 300 FAIL 8 27 PASS PASS PASS_at_KS_(2/3) +unambiguous oma-crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 21682 1347 [6,8,12,16,22,30,42,61,96] [6,8,10,13.4,19,26,36,53,81] 0.0552 3.073 PASS 3.631 3.535 FAIL 3 36 PASS PASS PASS_at_KS_(2/3) +unambiguous p-asat NA NA NA NA all u/l 99.95 {u/l:99.95,umol/l:0.05,u/l37:0} u/l 21421 444746 [18,21,24,26,29,34,40,50,73] [17,19,22,24,27,30,35,44,70] 0.07457 98.55 PASS -6.633 10.48 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-glomerulussuodosnopeus,ckd-epi-kaava NA NA NA NA all ml/min/173m2 99.79 {ml/min/173m2:99.79,form:0.21} ml/min/173m2 21275 5606 [37,50,60,68,76,82,88,94,102] [38,49,58,65,72,79,84,89,95] 0.08282 26.2 PASS 7.857 14.36 FAIL 4 48 PASS PASS PASS_at_KS_(2/3) +unambiguous l-eos NA NA NA NA all % 99.56 {%:99.56,e9/l:0.44} % 21090 942601 [0,0.9,1,1.9,2,3,3.2,4.5,6.8] [0,1,1,2,2,3,3.9,4,6] 0.07833 109.8 PASS -5.632 7.745 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous l-neutr NA NA NA NA all % 99.66 {%:99.66,e9/l:0.34,e9:0} % 20755 86909 [43,49,53,56,59,63,66,70,75] [44,49,53,56,59,62.4,66,70,76] 0.01054 1.318 PASS -1.996 1.338 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) +unambiguous p-t4v NA NA NA NA all pmol/l 100 {pmol/l:100} pmol/l 20621 90249 [12.2,13.4,14.2,14.9,15.6,16.3,17.2,18.3,20] [12.7,13.8,14.6,15.3,16,16.7,17.5,18.5,20] 0.05243 39.81 PASS -10.15 23.44 FAIL 0.4 5.7 PASS PASS PASS_at_KS_(2/3) +unambiguous s-b12-vit NA NA NA NA all pmol/l 100 {pmol/l:100,u:0,pmol/:0} pmol/l 20314 76509 [227,280,325,370,417,476,551,650,835] [232,281,321,361,403,452,513,601,768] 0.05142 36.61 PASS 9.714 21.55 FAIL 14 354 PASS PASS PASS_at_KS_(2/3) +unambiguous l-eosin NA NA NA NA all % 100 {%:100} % 19838 82317 [1,1,2,2,3,3,4,5,7] [1,1,2,2,3,3,4,5,6] 0.01263 1.919 PASS 1.953 1.294 PASS 0 3 PASS PASS PASS_at_KS_(3/3) +unambiguous l-lymfos NA NA NA NA all % 100 {%:100} % 19480 83981 [13,17,21,24,26,29,32,36,41] [13,18,21,24,27,30,33,36,42] 0.01782 4.064 PASS -1.254 0.6779 PASS 1 21 PASS PASS PASS_at_KS_(3/3) +unambiguous b-basof NA NA NA NA all e9/l 100 {e9/l:100} e9/l 19447 4729 [0.02,0.03,0.03,0.04,0.04,0.05,0.06,0.07,0.08] [0.02,0.02,0.03,0.04,0.04,0.05,0.05,0.06,0.08] 0.04398 6.105 PASS 7.268 12.4 FAIL 0 0.06 PASS PASS PASS_at_KS_(2/3) +unambiguous b-eosin NA NA NA NA all e9/l 100 {e9/l:100} e9/l 19437 12142 [0.04,0.08,0.11,0.14,0.17,0.2,0.25,0.32,0.44] [0.04,0.08,0.11,0.14,0.17,0.21,0.25,0.31,0.44] 0.009323 0.2745 FAIL 0.6328 0.2783 PASS 0 0.27 PASS PASS PASS_at_T_(2/3) +unambiguous l-basof NA NA NA NA all % 100 {%:100} % 19372 84273 [0,0,1,1,1,1,1,1,1] [0,0,1,1,1,1,1,1,1] 0.02437 7.833 PASS 9.941 22.52 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ca-albk NA NA NA NA all mmol/l 99.95 {mmol/l:99.95,form:0.05,mmol:0} mmol/l 18846 165475 [2.29,2.34,2.37,2.4,2.43,2.46,2.5,2.54,2.61] [2.34,2.39,2.42,2.44,2.47,2.5,2.53,2.57,2.63] 0.1538 300 PASS -33.69 242.1 FAIL 0.04 0.21 PASS PASS PASS_at_KS_(2/3) +unambiguous oma-gluk NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 18525 53 [5.4,6.1,6.8,7.5,8.4,9.3,10.5,12.1,14.7] [5.22,5.74,6.1,6.4,6.7,7.12,8,8.6,11.12] 0.2829 3.519 PASS 5.572 6.066 FAIL 1.7 3.3 PASS PASS PASS_at_KS_(2/3) +unambiguous u-epit NA NA NA NA all e6/l 99.79 {e6/l:99.79,u/field:0.19,u:0.02} e6/l 18155 168750 [0,1,1,1.5,2,3,4,7,14] [0.2,1,1,1.9,2.1,3.2,5,8.1,16.9] 0.04272 25.71 PASS -6.438 9.907 FAIL 0.1 5.1 PASS PASS PASS_at_KS_(2/3) +unambiguous l-lymf NA NA NA NA all % 99.19 {%:99.19,e9/l:0.81} % 17952 287233 [10,15.82,19,23,27,31,35,40.7,49] [12.3,18,21.2,25,28,31,34,38,44] 0.0618 55.82 PASS 2.945 2.49 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ck NA NA NA NA all u/l 100 {u/l:100} u/l 17899 260925 [46,62,75,90,108,133,170,242,409] [43,58,71,86,104,129,169,252,545] 0.03098 13.67 PASS -14.94 49.58 FAIL 4 150 PASS PASS PASS_at_KS_(2/3) +unambiguous l-baso NA NA NA NA all % 99.56 {%:99.56,e9/l:0.43,e/l:0} % 17874 929196 [0,0,0,0.5,1,1,1,1,1] [0,0,0,1,1,1,1,1,1] 0.06496 64.1 PASS -1.288 0.7036 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous s-ph(akt) NA NA NA NA all ph 100 {ph:100} ph 16686 97114 [7.35,7.37,7.38,7.39,7.4,7.4,7.41,7.42,7.44] [7.34,7.36,7.38,7.39,7.4,7.41,7.42,7.43,7.45] 0.08186 82.73 PASS -6.569 10.29 FAIL 0 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca(7.4) NA NA NA NA all mmol/l 99.92 {mmol/l:99.92,nmol/l:0.08} mmol/l 16482 115493 [1.18,1.2,1.22,1.23,1.24,1.25,1.27,1.28,1.32] [1.12,1.16,1.19,1.21,1.22,1.24,1.25,1.27,1.31] 0.1685 300 PASS 42.01 300 FAIL 0.02 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous b-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 15770 19712 [-7.5,-5.5,-4.3,-3.4,-2.6,-2,-1.4,-0.9,-0.4] [0.5,1.1,1.7,2.3,3,3.9,5,6.6,9.2] 0.9739 300 FAIL -193.4 300 FAIL 5.6 6 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-d-25 NA NA NA NA all nmol/l 100 {nmol/l:100,mmol/l:0,nmol/:0} nmol/l 15496 380163 [46,55,63,70,76,83,91,102,119] [46,56,63,69,76,82,90,100,116] 0.01766 3.739 PASS 3.216 2.885 FAIL 0 51 PASS PASS PASS_at_KS_(2/3) +unambiguous f-calpro NA NA NA NA all ug/g 100 {ug/g:100,ug/l:0,<100:0} ug/g 13490 130628 [17,27,39,57,85,129,202,355,794.1] [14,23,35,54,81,128,213,394,911] 0.03985 16.58 PASS -2.582 2.007 FAIL 4 195 PASS PASS PASS_at_KS_(2/3) +unambiguous u-osmole NA NA NA NA all mosm/kgh2o 100 {mosm/kgh2o:100} mosm/kgh2o 13152 70655 [364,436,491,542,590,642,700,769,869] [347,415,470,522,570,625,687,762,869] 0.04625 20.33 PASS 7.362 12.72 FAIL 20 411 PASS PASS PASS_at_KS_(2/3) +unambiguous psa-v/psa NA NA NA NA all % 100 {%:100} % 13127 25356 [9.6,12.5,14.9,17.2,19.4,21.8,24.4,27.9,33] [8.4,11,13.3,15.6,17.8,20.2,23,26.6,32.4] 0.07657 43.82 PASS 11.36 29.1 FAIL 1.6 18.3 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-transf NA NA NA NA all g/l 100 {g/l:100} g/l 12905 144990 [1.8,2,2.1,2.25,2.4,2.56,2.7,2.98,3.2] [1.53,1.74,1.9,2.04,2.2,2.31,2.5,2.7,3] 0.1737 300 PASS 40.95 300 FAIL 0.2 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-cdt NA NA NA NA all % 99.96 {%:99.96,u/l:0.04,mg/l:0} % 12434 89543 [1.2,1.4,1.5,1.6,1.6,1.7,1.9,2.1,2.9] [0.8,1.1,1.3,1.4,1.5,1.6,1.7,1.9,2.3] 0.1676 267.7 PASS 30.97 203.7 FAIL 0.1 0.9 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca-iona NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 12323 382345 [1.13,1.17,1.19,1.21,1.23,1.24,1.26,1.28,1.32] [1.14,1.18,1.2,1.22,1.23,1.25,1.26,1.29,1.32] 0.03902 15.51 PASS -8.946 18.38 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous e-retik NA NA NA NA all % 99.98 {%:99.98,pg:0.01,e9/l:0} % 12082 121560 [0.8,1,1.2,1.3,1.5,1.7,2,2.3,3] [0.9,1.1,1.3,1.5,1.7,1.9,2.2,2.7,3.7] 0.09935 94.16 PASS -17.22 65.1 FAIL 0.2 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous p-fidd NA NA NA NA all mg/l 100 {mg/l:100,mikrog/ml:0,ug/l:0} mg/l 12060 116811 [0.29,0.3,0.4,0.5,0.6,0.8,1,1.6,3] [0.22,0.3,0.4,0.6,0.7,1,1.44,2.2,4.5] 0.09284 81.71 PASS -14.73 48.09 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous p-mg NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 11982 247648 [0.64,0.7,0.74,0.78,0.81,0.83,0.86,0.9,0.95] [0.64,0.7,0.74,0.77,0.8,0.83,0.85,0.89,0.94] 0.03404 11.21 PASS 2.421 1.81 FAIL 0.01 0.24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca(akt) NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 11963 86215 [1.18,1.2,1.22,1.23,1.24,1.26,1.27,1.29,1.33] [1.11,1.15,1.18,1.2,1.22,1.23,1.25,1.27,1.31] 0.2276 300 PASS 45.35 300 FAIL 0.02 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous hdl/kol. NA NA NA NA all % 100 {%:100} % 11551 1944 [23,27,30,33,36,38,41,45,49] [21,24,28,31,33,36,40,44,49] 0.08936 11.28 PASS 6.189 9.153 FAIL 3 24 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-fe NA NA NA NA all umol/l 100 {umol/l:100,µmol/l:0,ug/l:0} umol/l 11441 141841 [5,7,8.3,10,11.9,13.9,16,18.6,22.5] [5,7,8.8,10.3,11.9,13.5,15.5,18,22] 0.0343 10.53 PASS 1.835 1.177 PASS 0 12.9 PASS PASS PASS_at_KS_(3/3) +unambiguous fs-ca-ion NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 10667 11278 [1.19,1.22,1.23,1.24,1.25,1.27,1.28,1.3,1.33] [1.16,1.2,1.21,1.23,1.24,1.26,1.27,1.3,1.35] 0.1108 58.37 PASS 1 0.4985 PASS 0.01 0.12 PASS PASS PASS_at_KS_(3/3) +unambiguous b-lymf NA NA NA NA all e9/l 98.42 {e9/l:98.42,%:1.58} e9/l 10416 275628 [0.97,1.2,1.41,1.6,1.81,2.02,2.29,2.66,3.315] [0.86,1.14,1.36,1.55,1.74,1.95,2.19,2.5,2.99] 0.04474 17.17 PASS 2.462 1.859 FAIL 0.07 1.59 PASS PASS PASS_at_KS_(2/3) +unambiguous b-erytroblastit NA NA NA NA all e9/l 100 {e9/l:100} e9/l 10388 151903 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.03874 12.39 PASS -16.36 59.39 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-prot-o NA NA NA NA all form 99.89 {form:99.89,mg/dl:0.11} form 9860 936 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,1] 0.04588 1.277 FAIL -3.484 3.287 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-t4-v NA NA NA NA all pmol/l 100 {pmol/l:100,pmol:0} pmol/l 9709 242498 [11,12,12,13,13,14,14,15,17] [11,12,12.9,13.1,14,14.5,15.1,16.01,17.5] 0.1618 213.2 PASS -15.97 56 FAIL 1 5.1 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-gluk-hy NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 9537 6395 [5.3,6.5,7.5,8.5,9.5,10.6,11.9,13.4,15.6] [5.4,6.5,7.5,8.5,9.5,10.4,11.6,13.3,15.6] 0.02434 1.677 PASS -1.27 0.6904 PASS 0 7.8 PASS PASS PASS_at_KS_(3/3) +unambiguous nu-albkrea NA NA NA NA all mg/mmol 100 {mg/mmol:100} mg/mmol 9489 11439 [0.2,0.4,0.5,0.7,1,1.6,2.8,6,17.9] [0.3,0.5,0.7,0.9,1.3,2.1,3.8,8.2,27.3] 0.09281 38.61 PASS -6.811 11 FAIL 0.3 2.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-iga NA NA NA NA all g/l 100 {g/l:100} g/l 9343 52529 [1.06,1.4,1.63,1.9,2.1,2.4,2.74,3.2,4.16] [0.74,1.16,1.46,1.73,2.03,2.37,2.77,3.35,4.51] 0.08621 51.01 PASS -6.038 8.799 FAIL 0.07 2.46 PASS PASS PASS_at_KS_(2/3) +unambiguous p-b12-vit NA NA NA NA all pmol/l 100 {pmol/l:100} pmol/l 9340 37066 [194,243,285,326,371,423,487,577,720] [208,258,299,339,381,429,489,575,748] 0.03999 10.07 PASS -6.574 10.3 FAIL 10 351 PASS PASS PASS_at_KS_(2/3) +unambiguous p-crp-o NA NA NA NA all mg/l 100 {mg/l:100,u/l:0} mg/l 9102 29537 [7,9,13,18,24,33,45,65,98] [6,8,11,14,20,28,40,58,91] 0.07448 33.29 PASS 8.707 17.46 FAIL 4 39 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-pco2 NA NA NA NA all kpa 100 {kpa:100} kpa 9039 107718 [4.2,4.7,5,5,5,5.3,5.7,6,6.7] [4.2,4.5,4.7,4.9,5.1,5.3,5.6,5.9,6.6] 0.1277 118.3 PASS 3.557 3.424 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-pi NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 8841 175027 [0.8,0.9,0.98,1.02,1.1,1.15,1.21,1.32,1.54] [0.78,0.9,0.99,1.07,1.16,1.25,1.38,1.56,1.85] 0.1446 153.3 PASS -25.19 135.2 FAIL 0.06 0.72 PASS PASS PASS_at_KS_(2/3) +unambiguous p-inr-vt NA NA NA NA all inr 100 {inr:100} inr 8487 1439 [1.3,1.8,2,2.1,2.3,2.4,2.6,2.9,3.3] [1,1,1,1,1.1,1.3,1.9,2.4,2.9] 0.5129 297.5 FAIL 23.72 115.7 FAIL 1.2 0.3 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous fp-ca NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 8418 53236 [2.23,2.29,2.31,2.35,2.38,2.4,2.43,2.49,2.55] [2.19,2.25,2.29,2.33,2.35,2.38,2.42,2.45,2.51] 0.1007 63.87 PASS 18.9 77.73 FAIL 0.03 0.24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-pappa NA NA NA NA all mu/l 99.6 {mu/l:99.6,form:0.4} mu/l 8226 33727 [255,396,527,664,822,1000,1220,1550,2150] [274,426,564,707,859.8,1045,1280,1622,2232] 0.02933 4.649 PASS -2.662 2.11 FAIL 37.85 1286 PASS PASS PASS_at_KS_(2/3) +unambiguous p-t3-v NA NA NA NA all pmol/l 100 {pmol/l:100} pmol/l 8195 73828 [3.5,3.9,4.1,4.3,4.5,4.8,5,5.4,6.2] [3.5,3.8,4.1,4.3,4.6,4.8,5.1,5.5,6.2] 0.0259 4.005 PASS -0.7015 0.3161 PASS 0.1 1.8 PASS PASS PASS_at_KS_(3/3) +unambiguous s-iglck-v NA NA NA NA all mg/l 100 {mg/l:100} mg/l 7877 39042 [9.6,13.9,18.4,23.5,30,40.1,55.8,89.68,220] [7.8,12.1,16.2,21,27.1,35.7,50.3,81.2,172] 0.05025 14.1 PASS 3.239 2.92 FAIL 2.9 49.8 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-hco3-st NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 7860 64090 [20.9,22.4,23.9,24.7,25.3,26.1,27.2,28.82,31.2] [21,22.4,23.3,24,25,25.6,26.3,27.5,29.5] 0.1021 63.24 PASS 12.93 37.18 FAIL 0.3 6 PASS PASS PASS_at_KS_(2/3) +unambiguous s-iglcl-v NA NA NA NA all mg/l 100 {mg/l:100} mg/l 7669 38822 [6.5,9.7,12.8,16,19.6,25,32.9,49.8,124] [6.1,9.2,12,15.1,19,23.9,31.8,48.6,118] 0.03176 5.319 PASS -2.897 2.424 FAIL 0.6 31.5 PASS PASS PASS_at_KS_(2/3) +unambiguous crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 7205 71 [6,9,12,16,22,30,42,58,90] [6,8,12,16,25,38,58,64,88] 0.1079 0.4437 FAIL -0.6403 0.2806 PASS 3 57 PASS PASS PASS_at_T_(2/3) +unambiguous p-ck-mbm NA NA NA NA all ug/l 100 {ug/l:100} ug/l 7160 69802 [1.3,1.7,2,2.3,2.6,3.1,3.8,4.9,7.81] [1.1,1.5,1.9,2.2,2.8,3.4,4.5,7.1,18] 0.0901 45.59 PASS -19.06 79.34 FAIL 0.2 4.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-testo NA NA NA NA all nmol/l 99.93 {nmol/l:99.93,pmol/l:0.03,form:0.03} nmol/l 6954 77552 [2.9,6.5,8.1,9.5,11,13,15.7,19,23.87] [1.5,6.6,9,11,12.8,14.7,17,19.8,24.4] 0.09349 48.27 PASS -2.242 1.603 FAIL 1.8 15.6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-pi NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 6629 179614 [0.69,0.81,0.9,0.98,1.05,1.14,1.23,1.37,1.6] [0.74,0.87,0.97,1.05,1.13,1.23,1.35,1.51,1.79] 0.105 61.07 PASS -18.9 77.09 FAIL 0.08 0.72 PASS PASS PASS_at_KS_(2/3) +unambiguous u-osmest NA NA NA NA all mosm/kgh2o 100 {mosm/kgh2o:100,mo/kg/h2o:0,mo/kgh2o:0} mosm/kgh2o 6305 89312 [291,363,418,465,515,573,634.2,703,803.4] [262,327,378,425,472,523,584,656,768] 0.08677 38.3 PASS 14.79 48.04 FAIL 43 390 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-krea NA NA NA NA all umol/l 100 {umol/l:100} umol/l 6255 759945 [62,70,77,87,96,103,110,121,146] [56,62,68,73,78,84,92,105,140] 0.246 300 PASS 6.138 9.052 FAIL 18 45 PASS PASS PASS_at_KS_(2/3) +unambiguous p-tt NA NA NA NA all % 100 {%:100,form:0} % 6023 465481 [41,57,67,77,86,94,102,112,126] [50,65,74,82,88,95,102,110,121] 0.08411 36.31 PASS -5.824 8.218 FAIL 2 54 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ld NA NA NA NA all u/l 100 {u/l:100} u/l 5895 215599 [163,180,193,207,221,238,258,289,357] [166,184,198,212,226,244,269,310,413] 0.04455 9.609 PASS -10.44 24.61 FAIL 5 126 PASS PASS PASS_at_KS_(2/3) +unambiguous p-bil-kj NA NA NA NA all umol/l 100 {umol/l:100} umol/l 5806 124636 [2,3,3,4,5,6,7,9,15] [3,3,4,4,5,6,8,11,26] 0.06147 17.94 PASS -9.79 21.76 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous b-leukosyytit NA NA NA NA all e9/l 100 {e9/l:100,1:0} e9/l 5646 370214 [4.8,6,7,8.3,8.7,9.2,9.9,10.8,13] [4.4,5.1,5.7,6.2,6.8,7.4,8.2,9.3,11.3] 0.3046 300 FAIL 21.83 100.9 FAIL 1.9 4.8 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-urea NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 5615 168276 [4.1,5.4,6.8,8.5,10.5,12.7,15.3,18.8,24.7] [4.2,5.5,6.9,8.7,10.9,13.4,16.4,20,25.3] 0.0386 6.745 PASS -3.726 3.708 FAIL 0.4 16.2 PASS PASS PASS_at_KS_(2/3) +unambiguous crp-pika NA NA NA NA all mg/l 100 {mg/l:100} mg/l 5400 3081 [6,8,11,16,23,33,47,69,103] [7,9,13,18,25,34,47,69,106] 0.05675 5.211 PASS -1.678 1.029 PASS 2 51 PASS PASS PASS_at_KS_(3/3) +unambiguous -trfesat NA NA NA NA all % 100 {%:100,g/l:0} % 5367 49060 [8,12,16,19,22,26,29,34,41] [9.2,13.8,17,20,23,26.26,30,34.7,42] 0.05622 13.01 PASS -6.034 8.775 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +unambiguous p-amylp NA NA NA NA all u/l 100 {u/l:100} u/l 5279 91217 [13,18,21,24,28,31,35,43,60] [14,20,23,26,30,34,40,51,85] 0.07912 26.89 PASS -8.148 15.35 FAIL 2 30 PASS PASS PASS_at_KS_(2/3) +unambiguous s-prot NA NA NA NA all g/l 100 {g/l:100} g/l 5242 87590 [59,62.5,65,67,68.4,70,71.5,73.9,77] [57,61,63,65,67,69,70.6,73,76.2] 0.09527 38.8 PASS 10.78 26.12 FAIL 1.4 15 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-urea NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 5232 124584 [5,6.6,8,9.7,11.4,13.6,16.1,19.88,25] [5,6.9,8.9,11.3,13.9,16.5,19.2,22.4,27.3] 0.1204 63.19 PASS -14.53 46.26 FAIL 2.5 18.9 PASS PASS PASS_at_KS_(2/3) +unambiguous 14272 NA NA NA NA all e9/l 100 {e9/l:100} e9/l 5212 79059 [1.5,2,2.5,2.9,3.4,3.9,4.7,5.8,8.1] [1.06,1.72,2.24,2.72,3.24,3.83,4.61,5.76,8.02] 0.07552 23.97 PASS 3.429 3.214 FAIL 0.16 4.38 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava NA NA NA NA all ml/min/173m2 99.81 {ml/min/173m2:99.81,1:0.19} ml/min/173m2 5151 202854 [30,38.2,44,49,53,57,62,69,82] [34,48,59,68,75,82,87,93,101] 0.3791 300 FAIL -57.84 300 FAIL 22 51 PASS PASS PASS_at_MAD_(1/3) +unambiguous -nt NA NA NA NA all mm 100 {mm:100} mm 5019 11772 [0.8,0.9,1,1.1,1.2,1.2,1.3,1.5,1.7] [0.9,1,1.1,1.2,1.27,1.34,1.49,1.6,1.8] 0.1319 53.08 PASS -11.64 30.4 FAIL 0.07 0.75 PASS PASS PASS_at_KS_(2/3) +unambiguous s-hcgbv/d NA NA NA NA all ug/l 100 {ug/l:100} ug/l 4990 14513 [22.4,30.3,37.1,44.7,52.7,62.64,74.9,91.5,120] [22.6,31.2,38.7,46.3,55,64.9,77.8,94.1,125.5] 0.02665 1.997 PASS -3.451 3.251 FAIL 2.3 70.5 PASS PASS PASS_at_KS_(2/3) +unambiguous s-mkomp-1 NA NA NA NA all g/l 100 {g/l:100} g/l 4885 29826 [0,0,0,1.1,2.5,4.2,7.1,11.4,19.1] [0,0,0,0,0,0.3,1.8,5.1,11.2] 0.2583 246.7 PASS 21.27 96.01 FAIL 2.5 0 FAIL PASS PASS_at_KS_(1/3) +unambiguous s-li NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 4651 33555 [0.4,0.5,0.58,0.6,0.7,0.72,0.8,0.9,1] [0.4,0.5,0.54,0.6,0.69,0.7,0.8,0.9,1] 0.02917 2.728 PASS 1.317 0.726 PASS 0.01 0.51 PASS PASS PASS_at_KS_(3/3) +unambiguous p-ca-iona NA NA NA NA all mmol/l 100 {mmol/l:100,%:0,kpa:0} mmol/l 4581 404577 [1.1,1.14,1.16,1.17,1.19,1.21,1.23,1.25,1.29] [1.04,1.08,1.11,1.13,1.15,1.17,1.19,1.21,1.25] 0.2532 255.7 PASS 33.65 230.1 FAIL 0.04 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous s-valpr NA NA NA NA all umol/l 99.9 {umol/l:99.9,%:0.1} umol/l 4307 31514 [197,257,299.8,340.4,382,423,465,517,588.4] [221,285,332,372,409,446,487,533,601] 0.0818 21.78 PASS -10.07 22.95 FAIL 27 300 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ca-ion. NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 4300 356672 [1.11,1.14,1.16,1.18,1.2,1.21,1.23,1.26,1.29] [1.03,1.08,1.11,1.13,1.16,1.18,1.2,1.22,1.25] 0.251 235.6 PASS 41.48 300 FAIL 0.04 0.18 PASS PASS PASS_at_KS_(2/3) +unambiguous u-albkrea NA NA NA NA all mg/mmol 99.24 {mg/mmol:99.24,mg/mmol/l:0.76} mg/mmol 4132 10589 [0.4,0.7,1.1,1.9,3.4,4.9,7.7,14.4,36.99] [0.3,0.4,0.6,0.7,1,1.3,1.8,3,9.12] 0.343 300 FAIL 9.367 20 FAIL 2.4 1.8 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous fs-trigly NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,form:0} mmol/l 3980 258906 [0.6,0.72,0.83,0.93,1.06,1.2,1.39,1.64,2.11] [0.7,0.84,0.98,1.11,1.27,1.45,1.68,2,2.57] 0.1417 68.43 PASS -20.61 89.3 FAIL 0.21 1.26 PASS PASS PASS_at_KS_(2/3) +unambiguous b-crp-vt NA NA NA NA all mg/l 99.98 {mg/l:99.98,crp:0.02,g/l:0.01} mg/l 3965 16204 [2.64,5.7,8,12,18,26,40,57,89] [6,8,11,14,19,27,38,54,88] 0.1545 66.18 PASS -1.14 0.5947 PASS 1 36 PASS PASS PASS_at_KS_(3/3) +unambiguous sy-leuk NA NA NA NA all e6/l 99.75 {e6/l:99.75,e9/l:0.25} e6/l 3964 11394 [117.3,262.6,500,1123,2804,5405,1.011e+04,1.868e+04,3.801e+04] [100.3,225,510,1400,3320,6503,1.12e+04,1.91e+04,3.72e+04] 0.03253 2.413 PASS -0.3365 0.1328 PASS 516 9654 PASS PASS PASS_at_KS_(3/3) +unambiguous b-ghba1cp NA NA NA NA all % 100 {%:100} % 3927 888 [6,6.3,6.6,6.9,7.2,7.4,7.8,8.2,8.8] [5.9,6.1,6.5,6.8,7.1,7.52,7.9,8.3,9.4] 0.06144 2.095 PASS -3.643 3.545 FAIL 0.1 2.7 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-kol-hdl NA NA NA NA all mmol/l 100 {mmol/l:100,form:0,mmol/:0} mmol/l 3887 254480 [1.03,1.16,1.25,1.34,1.43,1.53,1.64,1.77,1.96] [1,1.1,1.2,1.3,1.4,1.5,1.6,1.74,2] 0.07186 16.91 PASS 1.839 1.18 PASS 0.03 0.75 PASS PASS PASS_at_KS_(3/3) +unambiguous fs-kol NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0,form:0} mmol/l 3794 255206 [3.5,4,4.3,4.6,4.9,5.2,5.5,5.8,6.4] [3.7,4.2,4.5,4.8,5,5.3,5.6,5.9,6.4] 0.06004 11.43 PASS -6.382 9.711 FAIL 0.1 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-kol-ldl NA NA NA NA all mmol/l 100 {mmol/l:100,form:0,mmol/:0} mmol/l 3772 255211 [1.7,2.2,2.5,2.8,3.1,3.4,3.671,3.996,4.5] [1.9,2.3,2.6,2.9,3.1,3.4,3.7,4,4.5] 0.04679 6.785 PASS -3.555 3.417 FAIL 0 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous p-bnp NA NA NA NA all ng/l 99.98 {ng/l:99.98,ng/ml:0.02} ng/l 3770 88507 [42,72,109,144,194,258,352,511.4,899.1] [20,36,58,88,131,195,292,462,895] 0.1578 78.37 PASS 2.555 1.973 FAIL 63 312 PASS PASS PASS_at_KS_(2/3) +unambiguous p-igg NA NA NA NA all g/l 100 {g/l:100} g/l 3736 73214 [6,7.4,8.6,9.5,10.4,11.4,12.6,14.5,17.95] [5,6.6,7.7,8.7,9.6,10.6,11.7,13.3,16.6] 0.1016 31.71 PASS 8.605 16.97 FAIL 0.8 7.8 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-glukoosi,ihopistosn,vieritestihoitoyksikössä NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 3716 1349 [5.3,6.2,7.1,8,9.1,10.3,11.9,13.9,16.9] [5.2,6.2,7,7.9,8.9,10.2,11.9,14.2,17.2] 0.0217 0.1369 FAIL 0.5007 0.21 PASS 0.2 8.4 PASS PASS PASS_at_T_(2/3) +unambiguous ab-emäsylimäärä NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 3701 9136 [-9.2,-6.4,-4.8,-3.7,-2.8,-2.1,-1.6,-1.1,-0.5] [-0.8,0.4,1.1,1.7,2.4,3.3,4.5,6.1,8.9] 0.8699 300 FAIL -89.69 300 FAIL 5.2 6 PASS PASS PASS_at_MAD_(1/3) +unambiguous u-sg NA NA NA NA all kg/l 100 {kg/l:100} kg/l 3697 130 [1.005,1.005,1.01,1.01,1.015,1.015,1.02,1.02,1.025] [1.01,1.01,1.01,1.015,1.015,1.017,1.02,1.02,1.025] 0.182 3.385 PASS 2 1.341 FAIL 0 0.015 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-emäsylimäärä NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 3632 12064 [-9.1,-6.3,-4.6,-3.5,-2.6,-2,-1.3,-0.8,-0.3] [-2.6,-0.2,0.7,1.3,2.1,2.8,3.6,4.7,6.7] 0.7533 300 FAIL -77.35 300 FAIL 4.7 5.7 PASS PASS PASS_at_MAD_(1/3) +unambiguous b-ph NA NA NA NA all ph 100 {ph:100} ph 3554 35592 [7.31,7.34,7.36,7.38,7.39,7.41,7.43,7.44,7.46] [7.35,7.38,7.4,7.41,7.42,7.43,7.44,7.46,7.48] 0.2071 121.3 PASS -23.05 109.9 FAIL 0.03 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-pco2 NA NA NA NA all kpa 100 {kpa:100} kpa 3514 187248 [4.523,5,5.2,5.4,5.7,5.9,6.2,6.5,7.1] [4.7,5.1,5.3,5.6,5.8,6,6.3,6.6,7.1] 0.06585 12.72 PASS -5.987 8.629 FAIL 0.1 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-po2 NA NA NA NA all kpa 100 {kpa:100} kpa 3497 134116 [3.2,3.8,4.386,4.8,5.2,5.6,6.2,7.4,10] [2.8,3.4,3.9,4.3,4.7,5.1,5.7,6.5,8.3] 0.1189 41.73 PASS 13.92 42.21 FAIL 0.5 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous mb-ph NA NA NA NA all ph 100 {ph:100} ph 3444 279 [7.29,7.32,7.34,7.36,7.373,7.39,7.401,7.419,7.435] [7.318,7.34,7.36,7.37,7.38,7.4,7.41,7.42,7.44] 0.13 3.535 PASS -3.9 3.936 FAIL 0.007 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous b-crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 3350 2366 [5,7,9,12,17,24,35,54,87] [6,8,9,13,18,25,35,55,90] 0.09378 10.34 PASS -1.146 0.5987 PASS 1 33 PASS PASS PASS_at_KS_(3/3) +unambiguous p-gluk-vt NA NA NA NA all mmol/l 98.08 {mmol/l:98.08,1:1.92} mmol/l 3313 2048 [5,5.7,6.4,7.2,8.2,9.5,11,12.8,15.9] [4.5,4.7,4.9,5.1,5.4,5.8,6.5,7.56,9.63] 0.3966 177.7 FAIL 20.93 92.33 FAIL 2.8 2.4 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous ab-po2 NA NA NA NA all kpa 99.99 {kpa:99.99,mmol/l:0,%:0} kpa 3269 391556 [6.7,7.7,8.2,8.8,9.4,10,10.9,12,14.2] [8.1,9.1,9.9,10.6,11.4,12.4,13.8,16.2,21.5] 0.2746 215.8 PASS -43.56 300 FAIL 2 7.2 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-pco2 NA NA NA NA all kpa 99.99 {kpa:99.99,mmol/l:0,%:0} kpa 3239 392179 [3.9,4.3,4.6,4.8,5,5.3,5.7,6.3,7.4] [4.1,4.5,4.7,5,5.2,5.4,5.6,5.9,6.5] 0.07603 15.87 PASS 3.66 3.592 FAIL 0.2 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous li-leuk NA NA NA NA all e6/l 100 {e6/l:100} e6/l 3193 10896 [0,0,1,1,2,3,4,10,65.6] [0,0,1,1,2,3,5,11,58] 0.03269 2 PASS -2.785 2.27 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous li-eryt NA NA NA NA all e6/l 100 {e6/l:100} e6/l 3189 11741 [0,0,0,1,3,10,43.6,199.4,1766] [0,0,1,2,4,12,45,232,2250] 0.02869 1.501 PASS 0.6696 0.2983 PASS 1 12 PASS PASS PASS_at_KS_(3/3) +unambiguous p-crp-vt NA NA NA NA all mg/l 100 {mg/l:100} mg/l 3141 6868 [5,6.9,9,14,20,28,40,59,91] [5,7,10,14,20,28,40,61,94] 0.0366 2.22 PASS -0.7086 0.3201 PASS 0 42 PASS PASS PASS_at_KS_(3/3) +unambiguous b-crp-o NA NA NA NA all mg/l 100 {mg/l:100} mg/l 3125 1516 [7,10,14,19,26,35,47,67,98] [6,8,11,15,21,28,40,59,90] 0.08443 6.057 PASS 3.708 3.672 FAIL 5 42 PASS PASS PASS_at_KS_(2/3) +unambiguous s-psa NA NA NA NA all ug/l 99.99 {ug/l:99.99,mg/l:0.01,%:0} ug/l 3123 88424 [0.37,0.57,0.73,0.95,1.3,1.7,2.6,4.2,7.5] [0.39,0.57,0.75,0.97,1.24,1.63,2.26,3.3,5.4] 0.05689 8.201 PASS 2.235 1.593 FAIL 0.06 2.22 PASS PASS PASS_at_KS_(2/3) +unambiguous p-apcres. NA NA NA NA all form 100 {form:100} form 3090 64 [2.5,2.7,2.8,2.9,2.9,3,3,3.1,3.2] [2.7,2.8,2.8,2.8,2.9,2.9,2.9,3,3] 0.1794 1.512 PASS -0.7183 0.3234 PASS 0 0.3 PASS PASS PASS_at_KS_(3/3) +unambiguous cp-gluk NA NA NA NA all mmol/l 99.85 {mmol/l:99.85,mmol/:0.15} mmol/l 3068 1987 [5.9,6.8,7.8,9,10.25,11.9,13.89,15.96,19.2] [5.1,6.3,7.7,9.1,10.6,12.7,14.4,16.4,19.3] 0.06829 4.613 PASS 0.1958 0.07327 PASS 0.35 12.6 PASS PASS PASS_at_KS_(3/3) +unambiguous lieriöt NA NA NA NA all e6/l 100 {e6/l:100} e6/l 2938 23942 [0,0,0,0,0,0,0.1,0.3,0.9] [0,0,0,0,0,0.1,0.3,0.42,1] 0.1694 65.4 PASS -0.1685 0.06237 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous crp(päiv.hoitaja) NA NA NA NA all mg/l 99.18 {mg/l:99.18,g/l:0.27,mg/:0.27} mg/l 2927 361 [6,8,10,14,19,27,39.2,56,91.4] [6,7,9,12,15,21,28,47,71] 0.09255 2.122 PASS 3.49 3.279 FAIL 4 27 PASS PASS PASS_at_KS_(2/3) +unambiguous u-happamuusaste(kval) NA NA NA NA all form 100 {form:100} form 2872 32 [5,5.5,5.5,5.5,6,6,6,6.5,7] [5,5.5,5.5,5.5,5.5,6,6,6.5,7] 0.09706 0.04638 FAIL 0.1506 0.05489 PASS 0.5 1.5 PASS PASS PASS_at_T_(2/3) +unambiguous p-cea NA NA NA NA all ug/l 100 {ug/l:100} ug/l 2813 49240 [1.2,1.7,2,2.2,3,3.1,4,5,6.9] [1.6,2.1,2.4,2.8,3.4,4.3,5.9,10,33] 0.181 76.06 PASS -8.645 17.17 FAIL 0.4 4.5 PASS PASS PASS_at_KS_(2/3) +unambiguous happamuusaste,laskimoveri NA NA NA NA all ph 100 {ph:100} ph 2733 819 [7.32,7.35,7.36,7.38,7.39,7.4,7.41,7.43,7.45] [7.3,7.34,7.36,7.37,7.39,7.4,7.41,7.43,7.45] 0.05006 1.088 FAIL 2.574 1.993 FAIL 0 0.09 PASS PASS PASS_at_MAD_(1/3) +unambiguous tffesat NA NA NA NA all % 100 {%:100} % 2726 900 [7.6,10.8,13.7,16.6,19.4,22.3,25.9,30.3,37] [8.19,11.68,15,18.1,21.2,24.34,27.63,31.84,38.41] 0.07481 3.017 PASS -2.62 2.051 FAIL 1.8 23.7 PASS PASS PASS_at_KS_(2/3) +unambiguous u-lieriöt NA NA NA NA all e6/l 99.54 {e6/l:99.54,u/field:0.46,u/ul:0} e6/l 2719 59778 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0.14,0.42,1] 0.3489 282.7 FAIL -27.96 168.5 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-gamma NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2700 28537 [5.6,6.68,7.5,8.2,9.2,10.1,11.2,12.7,15.9] [4.5,6.3,7.5,8.5,9.5,10.5,11.7,13.5,17.3] 0.06216 8.004 PASS -2.571 1.992 FAIL 0.3 8.1 PASS PASS PASS_at_KS_(2/3) +unambiguous erytroblastit NA NA NA NA all e9/l 100 {e9/l:100} e9/l 2691 141098 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.04834 5.075 PASS -6.487 9.984 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-hco3-st NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 2612 255830 [20,22,23,24,25,26,27,28,30] [21,22,23,24,25,25,26,27,29] 0.05808 7.299 PASS 3.353 3.091 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-kysc NA NA NA NA all mg/l 100 {mg/l:100} mg/l 2572 52852 [0.76,0.9,1.013,1.13,1.27,1.44,1.64,1.91,2.359] [0.85,0.96,1.08,1.23,1.42,1.64,1.93,2.35,3.15] 0.1083 24.79 PASS -18.23 69.86 FAIL 0.15 1.41 PASS PASS PASS_at_KS_(2/3) +unambiguous s-alfa-2 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2555 27644 [5.7,6.2,6.5,6.8,7.1,7.5,7.9,8.4,9.4] [5.5,5.9,6.3,6.7,7,7.4,7.8,8.4,9.37] 0.06415 8.084 PASS 4.402 4.955 FAIL 0.1 3 PASS PASS PASS_at_KS_(2/3) +unambiguous s-alfa-1 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2552 27708 [1.5,1.7,1.9,2.1,2.4,2.6,2.9,3.2,3.8] [2.2,2.4,2.6,2.7,2.9,3,3.2,3.5,4.1] 0.3316 228.8 FAIL -23.7 113 FAIL 0.5 1.2 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-album NA NA NA NA all g/l 100 {g/l:100} g/l 2547 25430 [31.4,35,37.3,39,40.3,41.5,43,44.5,46.3] [31,34.3,36.2,37.6,38.7,39.8,40.9,42.1,43.7] 0.1625 53.15 PASS 12.94 36.55 FAIL 1.6 9 PASS PASS PASS_at_KS_(2/3) +unambiguous s-beta-2 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2541 27334 [2.1,2.4,2.6,2.8,3,3.3,3.6,4.1,4.8] [2.3,2.6,2.8,3.1,3.4,3.6,4,4.5,5.5] 0.1285 33.22 PASS -15.11 49.61 FAIL 0.4 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous s-beta-1 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2540 27387 [3.4,3.7,3.9,4,4.2,4.4,4.6,4.8,5.2] [3.3,3.5,3.7,3.9,4,4.2,4.4,4.6,5] 0.1268 32.31 PASS 5.524 7.448 FAIL 0.2 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-norklot NA NA NA NA all nmol/l 99.98 {nmol/l:99.98,umol/l:0.02} nmol/l 2538 22343 [321,458.4,572,704.8,826,970,1111,1326,1687] [344,489,614,734,863,1000,1166,1390,1713] 0.03663 2.367 PASS -2.018 1.36 FAIL 37 1041 PASS PASS PASS_at_KS_(2/3) +unambiguous p-korsol NA NA NA NA all nmol/l 100 {nmol/l:100,pmol/l:0} nmol/l 2505 51414 [185,261,314,350,394,434,482,539,637.6] [84,204.6,266,312,352,391,434,486,567] 0.1124 26 PASS 13.05 37.1 FAIL 42 330 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg4 NA NA NA NA all g/l 99.98 {g/l:99.98,form:0.02} g/l 2503 9778 [0.119,0.2164,0.3326,0.4408,0.58,0.7958,1.1,1.69,2.93] [0.11,0.209,0.31,0.439,0.59,0.787,1.06,1.56,2.623] 0.02386 0.6934 FAIL 4.122 4.413 FAIL 0.01 1.209 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-igm NA NA NA NA all g/l 100 {g/l:100} g/l 2460 38211 [0.4,0.6,0.76,0.94,1,1.2,1.58,2.29,5.028] [0.26,0.4,0.56,0.7,0.88,1.09,1.35,1.8,3.34] 0.1456 42.47 PASS 2.462 1.858 FAIL 0.12 1.44 PASS PASS PASS_at_KS_(2/3) +unambiguous l-nlt NA NA NA NA all % 100 {%:100} % 2422 7143 [16,28,38,45,52,59,65,72,81] [25,38,46,53,59,65,70,76,83] 0.1145 20.38 PASS -11.13 27.64 FAIL 7 45 PASS PASS PASS_at_KS_(2/3) +unambiguous s-iga NA NA NA NA all g/l 100 {g/l:100,mg/l:0} g/l 2410 35623 [0.99,1.32,1.55,1.8,2.05,2.33,2.69,3.27,4.331] [1.05,1.34,1.56,1.77,1.99,2.23,2.53,2.93,3.66] 0.05965 6.697 PASS 6.321 9.512 FAIL 0.06 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous s-van NA NA NA NA all mg/l 100 {mg/l:100} mg/l 2406 34483 [7.3,9,10.5,11.7,13,14.1,15.6,17.8,21.4] [6.9,8.6,10,11.1,12.4,13.7,15,17,19.8] 0.04717 4.062 PASS 5.626 7.692 FAIL 0.6 10.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-cea NA NA NA NA all ug/l 100 {ug/l:100,<5:0} ug/l 2353 87770 [1.1,1.3,1.6,1.9,2.2,2.7,3.5,4.66,7.3] [1.1,1.4,1.7,2,2.4,3.1,4.1,6.3,17.4] 0.07905 12.18 PASS -16.63 61.01 FAIL 0.2 3.3 PASS PASS PASS_at_KS_(2/3) +unambiguous zb-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 2350 2420 [-6.1,-4.1,-3.2,-2.6,-2,-1.5,-1.2,-0.7,-0.4] [0.4,0.8,1.2,1.7,2.2,2.9,3.8,4.9,7.4] 1 300 FAIL -70.65 300 FAIL 4.2 4.2 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-crp-hy NA NA NA NA all mg/l 100 {mg/l:100} mg/l 2326 6913 [7,10,13,18,24,33,46,66,101.5] [6,8,11,15,21,29,41,59,91] 0.06881 6.886 PASS 4.653 5.47 FAIL 3 42 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-trfesat NA NA NA NA all % 100 {%:100} % 2313 88543 [8,11,14,17,20,24,28,34,41.8] [9,13,16,19,22,25,28,33,40] 0.08891 15.23 PASS -2.173 1.525 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-k NA NA NA NA all mmol/l 100 {mmol/l:100,mml/l:0} mmol/l 2255 138249 [3.8,3.9,4.1,4.1,4.2,4.3,4.3,4.4,4.6] [3.8,4,4.1,4.2,4.2,4.3,4.4,4.5,4.6] 0.05636 5.841 PASS -4.525 5.198 FAIL 0 0.6 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-laktaat NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 2205 299118 [0.9,1,1.1,1.2,1.4,1.6,1.8,2.2,3] [0.5,0.7,0.8,0.9,1,1.2,1.4,1.7,2.3] 0.2916 164.6 PASS 13.23 37.77 FAIL 0.4 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous pf-eryt NA NA NA NA all e6/l 99.86 {e6/l:99.86,e9/l:0.14} e6/l 2155 3474 [300,700,1121,1900,3200,5600,1.11e+04,2.434e+04,7.96e+04] [300,800,1740,3300,6000,1.04e+04,2e+04,4.594e+04,1.3e+05] 0.1203 16.49 PASS -1.241 0.6679 PASS 2800 1.694e+04 PASS PASS PASS_at_KS_(3/3) +unambiguous vb-happamuusaste NA NA NA NA all 1 100 {1:100} 1 2150 59 [7.31,7.34,7.36,7.37,7.388,7.4,7.41,7.43,7.45] [7.288,7.35,7.38,7.39,7.4,7.41,7.426,7.434,7.452] 0.1619 1.058 FAIL -1.075 0.5427 PASS 0.012 0.09 PASS PASS PASS_at_T_(2/3) +unambiguous pf-leuk NA NA NA NA all e6/l 99.02 {e6/l:99.02,e9/l:0.98} e6/l 2145 4958 [143.8,262.8,405.6,585,804,1129,1638,2613,4980] [123.7,230,367,548.8,780.5,1120,1674,2547,4805] 0.0346 1.268 FAIL 1.1 0.5666 PASS 23.5 1804 PASS PASS PASS_at_T_(2/3) +unambiguous pt-gfre-md NA NA NA NA all ml/min/173m2 99.94 {ml/min/173m2:99.94,form:0.06} ml/min/173m2 2116 26941 [34,44,51,56,60,69,77,85,96] [34,45,52,57,61,72,81,90,101] 0.0529 4.485 PASS -4.037 4.253 FAIL 1 54 PASS PASS PASS_at_KS_(2/3) +unambiguous u-lieriö NA NA NA NA all e6/l 100 {e6/l:100} e6/l 2104 5122 [0,0,0,0,0.11,0.11,0.23,0.34,0.81] [0,0,0,0,0,0,0,0.1,1] 0.3671 178.8 FAIL -2.826 2.326 FAIL 0.11 0 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous l-myel NA NA NA NA all % 100 {%:100} % 2051 13362 [0,0,0,0,0,1,1,2,4] [0,0,0,0,1,1,1,2,4] 0.06706 6.669 PASS -0.8266 0.3888 PASS 1 3 PASS PASS PASS_at_KS_(3/3) +unambiguous s-tfr NA NA NA NA all mg/l 99.99 {mg/l:99.99,mg:0.01} mg/l 2018 75736 [1.8,2.2,2.6,3.1,3.6,4.2,5.1,6.3,8.1] [1,1.2,1.5,1.9,2.4,2.8,3.3,4.1,5.6] 0.2886 144.8 PASS 20.34 83.32 FAIL 1.2 3.3 PASS PASS PASS_at_KS_(2/3) +unambiguous s-trigly NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,mmol:0} mmol/l 1993 30438 [0.62,0.76,0.87,0.99,1.11,1.27,1.484,1.736,2.19] [0.7,0.8,0.95,1.1,1.2,1.4,1.6,1.9,2.5] 0.09324 13.88 PASS -8.974 18.25 FAIL 0.09 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous b-tacro NA NA NA NA all ug/l 100 {ug/l:100} ug/l 1993 43350 [4.3,5.1,6,6.8,7.5,8.5,9.8,11,13] [4.5,5.3,6,6.6,7.2,8,8.8,9.9,11.7] 0.09282 14.01 PASS 5.29 6.871 FAIL 0.3 5.4 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg1 NA NA NA NA all g/l 99.96 {g/l:99.96,form:0.04} g/l 1991 4826 [4.27,4.96,5.5,5.97,6.55,7.08,7.72,8.66,10.1] [3.7,4.5,5.08,5.6,6.14,6.7,7.31,8.2,9.73] 0.08725 9.061 PASS 5.43 7.219 FAIL 0.41 4.32 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg2 NA NA NA NA all g/l 99.96 {g/l:99.96,form:0.04} g/l 1988 4814 [1.42,1.854,2.14,2.41,2.67,3.01,3.35,3.9,4.64] [1.27,1.72,2.08,2.39,2.69,3.06,3.43,4,4.89] 0.04364 2.043 PASS -0.7587 0.3487 PASS 0.02 2.61 PASS PASS PASS_at_KS_(3/3) +unambiguous s-kol-hdl NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,mmol/mol:0} mmol/l 1987 33871 [0.99,1.12,1.22,1.31,1.39,1.49,1.6,1.74,1.94] [1,1.1,1.2,1.3,1.4,1.5,1.6,1.79,2] 0.03836 2.11 PASS -4.253 4.66 FAIL 0.01 0.78 PASS PASS PASS_at_KS_(2/3) +unambiguous l-nst NA NA NA NA all % 100 {%:100} % 1987 7096 [0,0,0,0,1,1,1,2,5] [0,0,0,0,1,1,1,2,5] 0.009132 0.0002801 FAIL 0.05908 0.02096 PASS 0 3 PASS PASS PASS_at_T_(2/3) +unambiguous s-dnanab. NA NA NA NA all kiu/l 100 {kiu/l:100} kiu/l 1975 1572 [0.6,0.8,0.9,1.1,1.3,1.7,2.3,3.2,5] [0.7,0.9,1.3,2.2,6.55,14,22,37,76] 0.4659 171.5 FAIL -18.91 71.35 FAIL 5.25 17.85 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-luakptt NA NA NA NA all ratio 99.45 {ratio:99.45,form:0.55} ratio 1952 1258 [0.97,1,1.01,1.03,1.04,1.06,1.08,1.11,1.17] [0.98,1,1.02,1.04,1.05,1.07,1.1,1.13,1.2] 0.07757 3.729 PASS -2.819 2.315 FAIL 0.01 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg3 NA NA NA NA all g/l 99.96 {g/l:99.96,form:0.04} g/l 1951 4826 [0.13,0.17,0.2,0.24,0.27,0.31,0.37,0.45,0.58] [0.13,0.18,0.22,0.26,0.31,0.36,0.44,0.55,0.72] 0.09618 10.91 PASS -7.247 12.32 FAIL 0.04 0.39 PASS PASS PASS_at_KS_(2/3) +unambiguous p-fsh NA NA NA NA all u/l 100 {u/l:100} u/l 1935 8372 [3.3,4.6,5.7,6.9,8.4,13,23.74,45,71] [3.41,4.8,5.9,7.2,9.4,15,30,52,73] 0.04243 2.172 PASS -2.927 2.462 FAIL 1 17.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-luakrvv NA NA NA NA all ratio 99.45 {ratio:99.45,form:0.55} ratio 1926 1256 [0.89,0.92,0.94,0.96,0.98,1,1.03,1.06,1.14] [0.89,0.93,0.95,0.97,0.99,1.01,1.04,1.08,1.18] 0.06371 2.404 PASS -2.024 1.366 FAIL 0.01 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous p-prl NA NA NA NA all mu/l 99.81 {mu/l:99.81,nmol/l:0.19} mu/l 1914 8542 [150,186,222,261.2,306,364,439.1,550,784] [138.1,185,224,261,306,361,436,572,938.9] 0.03245 1.14 FAIL -5.431 7.242 FAIL 0 372 PASS PASS PASS_at_MAD_(1/3) +unambiguous l-bas NA NA NA NA all % 100 {%:100} % 1904 7218 [0.2,0.3,0.4,0.4,0.5,0.6,0.7,0.8,1] [0.1,0.2,0.3,0.4,0.4,0.5,0.6,0.7,0.9] 0.1096 15.48 PASS 7.773 13.97 FAIL 0.1 0.6 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-crp-hy NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1836 10332 [1.8,3.2,5,7,9,13,19.5,34,61] [4.7,7,10,14,20,29,42,62,95] 0.2423 80.31 PASS -17.14 62.17 FAIL 11 42 PASS PASS PASS_at_KS_(2/3) +unambiguous p-haptog NA NA NA NA all g/l 100 {g/l:100} g/l 1821 18301 [0.65,0.9,1.09,1.3,1.5,1.69,1.96,2.26,2.78] [0.41,0.7,0.92,1.12,1.33,1.54,1.8,2.14,2.66] 0.09576 12.94 PASS 7.152 11.94 FAIL 0.17 1.68 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-t NA NA NA NA all °c 100 {°c:100} °c 1813 1617 [36.2,36.5,36.7,36.9,37,37,37.1,37.4,37.8] [36.3,36.5,36.8,37,37,37,37.3,37.5,38] 0.0633 2.698 PASS -2.93 2.467 FAIL 0 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous p-aptt NA NA NA NA all s 100 {s:100} s 1806 143489 [24,25,26,27,29,30,32,35,39] [25,26,27,28.5,30,31,33,36,46] 0.09448 13.59 PASS -13.92 41.3 FAIL 1 12 PASS PASS PASS_at_KS_(2/3) +unambiguous p-prealb NA NA NA NA all g/l 98.99 {g/l:98.99,mg/l:1.01} g/l 1802 17703 [0.13,0.16,0.19,0.2,0.22,0.24,0.27,0.31,138.8] [0.09,0.13,0.16,0.18,0.2,0.22,0.24,0.26,0.29] 0.1505 32.11 PASS 16.05 53.57 FAIL 0.02 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous s-kol-ldl NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmool/l:0,mmol/:0} mmol/l 1798 30028 [1.6,2.1,2.4,2.7,2.9,3.3,3.6,3.9,4.5] [1.8,2.2,2.4,2.7,2.9,3.1,3.4,3.7,4.1] 0.09459 12.93 PASS 4.63 5.409 FAIL 0 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous cu-alb NA NA NA NA all ug/min 99.93 {ug/min:99.93,mg:0.07} ug/min 1778 5389 [3,5,8,15,26,47,85,173.2,428.6] [4,6,10,18,29,48.8,84,161,427.4] 0.04503 2.07 PASS 0.05861 0.02079 PASS 3 75 PASS PASS PASS_at_KS_(3/3) +unambiguous b-retind NA NA NA NA all osuus 100 {osuus:100} osuus 1744 9157 [0.4,0.5,0.6,0.7,0.8,0.9,1,1.2,1.5] [0.4,0.5,0.7,0.8,0.9,1,1.2,1.5,1.9] 0.1196 17.99 PASS -10.57 24.99 FAIL 0.1 0.9 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-gluk-po NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1737 782 [4.7,5.9,7,8.1,9.2,10.6,12.4,14.68,18.3] [4.6,5.82,7.3,8.4,9.4,10.7,12,14.18,17.49] 0.03385 0.2577 FAIL 0.504 0.2116 PASS 0.2 9.75 PASS PASS PASS_at_T_(2/3) +unambiguous f-elast1 NA NA NA NA all ug/g 99.93 {ug/g:99.93,âug/g:0.07} ug/g 1732 10975 [61.1,124,185,235,292,348,398.7,448,494.9] [48,95,144.2,197,248,302.4,357,412,470] 0.0885 9.918 PASS 7.52 13.11 FAIL 44 396 PASS PASS PASS_at_KS_(2/3) +unambiguous l-prom NA NA NA NA all % 100 {%:100} % 1731 9986 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,1] 0.02093 0.276 FAIL -2.235 1.594 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous e-erytrosyytit,kokojakauma NA NA NA NA all % 100 {%:100} % 1729 117212 [14,15,15,15,16,16,17,18,19] [13,13,13,13,14,14,15,16,17] 0.5122 300 FAIL 37.93 230.7 FAIL 2 3 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-mkomp-2 NA NA NA NA all g/l 100 {g/l:100} g/l 1703 27016 [0,0,0,0,0,0,0,0,0.3] [0,0,0,0,0,0,0,0,0] 0.0506 3.277 PASS 4.632 5.413 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous ly-t-cd4/8 NA NA NA NA all ratio 100 {ratio:100} ratio 1701 115 [0.5,0.8,1.1,1.3,1.5,1.8,2.1,2.6,3.6] [0.6,0.8,1,1.26,1.6,1.84,2.08,2.42,3.16] 0.05797 0.07576 FAIL 1.434 0.8134 PASS 0.1 2.1 PASS PASS PASS_at_T_(2/3) +unambiguous l-metam NA NA NA NA all % 100 {%:100} % 1617 7291 [0,0,0,0,0,1,1,1,2] [0,0,0,0,0,1,1,2,3] 0.06055 3.936 PASS -5.99 8.629 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous s-crp NA NA NA NA all mg/l 99.97 {mg/l:99.97,form:0.03,mg/ml:0} mg/l 1601 153116 [2.1,6,8,11,14,19,28,43,77] [1,2,5,7,10,14,20,32,58] 0.1583 34.43 PASS 7.877 14.22 FAIL 4 24.3 PASS PASS PASS_at_KS_(2/3) +unambiguous b-peth NA NA NA NA all umol/l 99.99 {umol/l:99.99,umol/:0.01} umol/l 1586 18209 [0.07,0.12,0.18,0.27,0.36,0.5,0.69,0.98,1.52] [0.06,0.09,0.14,0.2,0.29,0.41,0.59,0.88,1.41] 0.0811 8.068 PASS 4.388 4.917 FAIL 0.07 0.63 PASS PASS PASS_at_KS_(2/3) +unambiguous l-bla NA NA NA NA all % 100 {%:100} % 1582 9301 [0,0,0,0,0,0,0,0,1] [0,0,0,0,0,0,0,0,0] 0.05241 2.943 PASS 1.476 0.8539 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous s-igg NA NA NA NA all g/l 100 {g/l:100} g/l 1567 20871 [5.912,7.672,8.67,9.5,10.27,11.1,12,13.61,17.09] [5.59,7.17,8.2,9.1,9.9,10.8,11.8,13.2,16] 0.05565 3.639 PASS 4.038 4.25 FAIL 0.37 6.9 PASS PASS PASS_at_KS_(2/3) +unambiguous p-glukpoc NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1562 957 [5.9,6.5,7,7.6,8.3,9.1,9.8,11.1,13.1] [6.06,6.7,7.3,7.8,8.4,9.2,10.2,11.2,12.94] 0.0537 1.205 FAIL -3.181 2.822 FAIL 0.1 5.1 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-mkomp-3 NA NA NA NA all g/l 100 {g/l:100} g/l 1542 25589 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.003735 -0 FAIL 1.195 0.6341 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous nu-alb NA NA NA NA all ug/min 100 {ug/min:100} ug/min 1512 442 [1,2.2,4,8,20,33,54,100.8,231.8] [3,6.2,8.3,12,15,18,26,72,195.4] 0.1773 9.15 PASS 2.014 1.354 FAIL 5 27 PASS PASS PASS_at_KS_(2/3) +unambiguous cu-alb-mi NA NA NA NA all ug/min 100 {ug/min:100} ug/min 1510 5748 [2,4,8,19,31.05,54,96,164.2,347.7] [2,3,4,6,9.9,17,34.39,79,218] 0.2215 51.18 PASS 1.206 0.6418 PASS 21.15 23.7 PASS PASS PASS_at_KS_(3/3) +unambiguous s-korsol NA NA NA NA all nmol/l 99.99 {nmol/l:99.99,umol/l:0,nmol/:0} nmol/l 1508 43706 [80.7,202.4,273,322,370.5,414,471.9,542.6,663.6] [138,244,308,360,409,460,517,589,699] 0.09016 10.04 PASS -7.142 11.86 FAIL 38.5 408 PASS PASS PASS_at_KS_(2/3) +unambiguous b-inrpika NA NA NA NA all inr 100 {inr:100} inr 1503 1540 [2,2.2,2.4,2.5,2.6,2.8,2.9,3.2,3.5] [2,2.1,2.3,2.4,2.6,2.7,2.9,3.1,3.4] 0.04325 0.9526 FAIL 2.358 1.734 FAIL 0 1.2 PASS PASS PASS_at_MAD_(1/3) +unambiguous myel NA NA NA NA all % 100 {%:100} % 1491 4482 [0,0,0,0,0,0,1,1,3.5] [0,0,0,0,0,0,1,1,3] 0.0565 2.823 PASS 1.955 1.295 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous prom NA NA NA NA all % 100 {%:100} % 1475 4479 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.02467 0.3016 FAIL 3.061 2.652 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous u-epipien NA NA NA NA all e6/l 100 {e6/l:100} e6/l 1465 16238 [0,0.1,0.44,0.9,1.5,2.3,3.4,5.1,8.7] [0.1,0.2,0.4,0.6,0.8,1,1.6,2.5,4.8] 0.2005 47.09 PASS 8.468 16.24 FAIL 0.7 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous happamuusaste,kapillaariveri NA NA NA NA all ph 100 {ph:100} ph 1457 122 [7.33,7.36,7.38,7.39,7.4,7.42,7.43,7.44,7.46] [7.35,7.38,7.39,7.41,7.42,7.43,7.44,7.45,7.48] 0.1377 1.599 PASS -3.045 2.558 FAIL 0.02 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous bla NA NA NA NA all % 100 {%:100} % 1446 3320 [0,0,0,0,0,0,0,0,1] [0,0,0,0,0,0,0,0,0] 0.03304 0.6665 FAIL -1.082 0.5537 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous u-leuk-bv NA NA NA NA all e6/l 100 {e6/l:100} e6/l 1442 17865 [1,1.6,2.43,3.7,5.95,12.12,34.37,128.6,621] [0.9,1.7,2.7,4.2,7.3,14.04,34.2,115.4,596.2] 0.0376 1.349 PASS -0.1062 0.03837 PASS 1.35 19.2 PASS PASS PASS_at_KS_(3/3) +unambiguous fs-sappih NA NA NA NA all umol/l 100 {umol/l:100} umol/l 1438 3976 [2,2.5,3,4,4.8,6,6.9,8.2,12.2] [1.6,2,2.4,3,3.7,4.5,5.7,7.6,13.3] 0.1293 15.12 PASS -0.9085 0.4393 PASS 1.1 5.1 PASS PASS PASS_at_KS_(3/3) +unambiguous s-igg-sum NA NA NA NA all g/l 100 {g/l:100} g/l 1434 477 [7.15,8.28,9.149,9.91,10.74,11.57,12.7,14.21,17.21] [6.898,8.282,9.118,9.748,10.9,11.91,13.04,14.71,18.14] 0.03981 0.219 FAIL -0.4105 0.1665 PASS 0.16 7.14 PASS PASS PASS_at_T_(2/3) +unambiguous s-mkomp-4 NA NA NA NA all g/l 100 {g/l:100} g/l 1434 25572 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.000743 -0 FAIL -1.039 0.5247 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous i-statcrea NA NA NA NA all umol/l 98.17 {umol/l:98.17,mmol/l:1.83} umol/l 1433 161 [55,65,71,79,88,98,110.4,129,166.6] [54,61,66,72,82,88,95,108,121] 0.1425 2.304 PASS 4.047 4.162 FAIL 6 63 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ige NA NA NA NA all u/ml 99.97 {u/ml:99.97,u/l:0.03} u/ml 1427 34187 [8,14.92,24,35,57.3,93.04,149,250.8,536.4] [8,15,23.7,36,54.7,84,137,248,607] 0.02957 0.7485 FAIL -1.366 0.764 PASS 2.6 134.1 PASS PASS PASS_at_T_(2/3) +unambiguous nlt NA NA NA NA all % 100 {%:100} % 1410 4470 [15,24,35,43,49,54,60,68,76] [25,40,48,53,57.75,62,67,73,80] 0.1787 29.65 PASS -11.72 30.23 FAIL 8.75 38.25 PASS PASS PASS_at_KS_(2/3) +unambiguous p-k-vt NA NA NA NA all mmol/l 98.21 {mmol/l:98.21,1:1.79} mmol/l 1404 2199 [3.4,3.6,3.7,3.8,3.9,4,4.1,4.3,4.5] [3.4,3.6,3.8,3.9,4,4,4.2,4.3,4.5] 0.02996 0.3822 FAIL -0.1062 0.03836 PASS 0.1 0.9 PASS PASS PASS_at_T_(2/3) +unambiguous metam NA NA NA NA all % 100 {%:100} % 1398 3264 [0,0,0,0,0,0,0,1,3] [0,0,0,0,0,0,1,1,3] 0.1022 8.638 PASS 0.008348 0.002902 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous nst NA NA NA NA all % 100 {%:100} % 1385 3292 [0,0,0,0,0,1,1,2,5] [0,0,0,0,1,1,1,2,5] 0.08924 6.481 PASS -2.057 1.401 FAIL 1 3 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-glukoosi NA NA NA NA all mmol/l 99.93 {mmol/l:99.93,nmol/l:0.07} mmol/l 1356 21503 [6.1,6.2,6.4,6.6,6.8,7,7.4,7.9,9.2] [5.1,5.3,5.5,5.7,5.9,6.1,6.5,7,8] 0.5693 300 FAIL 19.53 75 FAIL 0.9 1.8 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-igf1sds NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 1323 85 [-2.4,-1.5,-0.9,-0.6,-0.2,0.3,0.8,1.3,2.2] [0.4,0.6,0.82,0.96,1.2,1.4,1.5,2.3,2.72] 0.5314 20.76 FAIL -9.756 15.71 FAIL 1.4 1.5 PASS PASS PASS_at_MAD_(1/3) +unambiguous tromboplastiiniaika,inr-tulostus,plasmasta NA NA NA NA all inr 99.91 {inr:99.91,1:0.09} inr 1310 15979 [1,1.1,1.2,1.5,2,2.2,2.4,2.7,3] [1,1,1.1,1.4,1.9,2.2,2.5,2.7,3.1] 0.055 2.898 PASS 0.1715 0.06354 PASS 0.1 2.4 PASS PASS PASS_at_KS_(3/3) +unambiguous b-mo/abs NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1306 797 [0.37,0.43,0.48,0.53,0.57,0.63,0.69,0.77,0.91] [0.36,0.43,0.49,0.54,0.58,0.65,0.71,0.79,0.93] 0.03945 0.3865 FAIL -0.2467 0.09411 PASS 0.01 0.42 PASS PASS PASS_at_T_(2/3) +unambiguous b-ly/abs NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1306 797 [1.08,1.32,1.54,1.71,1.89,2.08,2.24,2.53,2.95] [0.916,1.15,1.35,1.53,1.75,1.93,2.14,2.418,3.028] 0.1056 4.535 PASS 2.854 2.359 FAIL 0.14 1.56 PASS PASS PASS_at_KS_(2/3) +unambiguous b-ba/abs NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1306 797 [0.02,0.02,0.03,0.03,0.03,0.04,0.05,0.05,0.07] [0.02,0.02,0.03,0.03,0.04,0.04,0.05,0.05,0.06] 0.06841 1.737 PASS 1.33 0.7357 PASS 0.01 0.03 PASS PASS PASS_at_KS_(3/3) +unambiguous b-hb-vt NA NA NA NA all g/l 99.66 {g/l:99.66,hb:0.34} g/l 1301 2922 [98,111,119,124,129,134,140,146,154] [106,116,122,127,131,135,140,146,154] 0.07122 3.694 PASS -3.499 3.322 FAIL 2 36 PASS PASS PASS_at_KS_(2/3) +unambiguous u-epilevy NA NA NA NA all e6/l 100 {e6/l:100} e6/l 1298 14634 [0.1,0.3,0.7,1.3,2.2,3.7,7.2,12.36,25.2] [0,0.1,0.3,0.5,0.9,1.3,2.2,4.3,10.4] 0.2038 43.16 PASS 9.13 18.63 FAIL 1.3 2.4 PASS PASS PASS_at_KS_(2/3) +unambiguous u-a1miglo NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1294 344 [7.1,9.5,12.09,15.52,19.5,25.6,33.31,43.44,64.98] [6.03,7.5,9.49,12,16,24.48,37.1,55.08,97.23] 0.1196 3.123 PASS -2.659 2.09 FAIL 3.5 29.7 PASS PASS PASS_at_KS_(2/3) +unambiguous emäsylimäärä,laskimoveri NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1291 2438 [-7.8,-5.5,-4,-3.2,-2.4,-1.7,-1.2,-0.8,-0.4] [0.5,1.2,1.7,2.3,2.9,3.5,4.3,5.3,6.9] 0.9852 300 FAIL -59.48 300 FAIL 5.3 4.8 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous du-ca NA NA NA NA all mmol 98.36 {mmol:98.36,mmol/24h:1.59,*sai:0.05} mmol 1285 12333 [1.7,2.8,3.728,4.54,5.67,6.588,7.682,8.782,10.3] [1.77,2.74,3.61,4.5,5.39,6.3,7.4,8.7,10.76] 0.03778 1.153 FAIL -0.2523 0.09644 PASS 0.28 7.08 PASS PASS PASS_at_T_(2/3) +unambiguous crp(vo:nyhteydessäotettu),tth NA NA NA NA all mg/l 99.37 {mg/l:99.37,alle:0.63} mg/l 1267 158 [5,5,5,8,8,8,13,22,44] [5,5,5,6,8,9,13.9,18,37.9] 0.09585 0.8513 FAIL 1.094 0.5602 PASS 0 9 PASS PASS PASS_at_T_(2/3) +unambiguous pika-crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1257 3592 [6,8.92,12,19,26,35,50,69.8,101.4] [6,8,11,15,21,30,42,61,93] 0.06889 3.564 PASS 3.121 2.738 FAIL 5 42 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-hb NA NA NA NA all g/l 100 {g/l:100} g/l 1251 15173 [94,105,112,119,124,130,135,142,152] [98,107,115,122,128,134,140,147,157] 0.08193 6.471 PASS -5.985 8.565 FAIL 4 48 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-po2 NA NA NA NA all kpa 100 {kpa:100} kpa 1248 47686 [6.3,7.1,7.9,8.5,9.2,10,10.8,11.7,12.83] [6.3,7,7.6,8.2,8.7,9.3,10,10.8,11.9] 0.1074 11.93 PASS 7.035 11.49 FAIL 0.5 4.5 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ana NA NA NA NA all titre 99.99 {titre:99.99,mmol/mol:0.01} titre 1248 16685 [80,160,320,320,320,320,640,640,1280] [80,160,160,320,320,320,400,640,1280] 0.1359 18.43 PASS 2.543 1.955 FAIL 0 480 PASS PASS PASS_at_KS_(2/3) +unambiguous p-fibr NA NA NA NA all g/l 100 {g/l:100} g/l 1233 38558 [2,2.3,2.6,2.9,3.1,3.4,3.8,4.3,5.18] [1.7,2.2,2.5,2.8,3.2,3.5,4,4.6,5.6] 0.06094 3.573 PASS -3.062 2.65 FAIL 0.1 2.91 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca-i7.4 NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1232 45578 [1.18,1.21,1.23,1.25,1.26,1.27,1.29,1.3,1.33] [1.17,1.2,1.22,1.24,1.25,1.27,1.28,1.3,1.34] 0.05625 3.015 PASS 3.286 2.982 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous i-statna NA NA NA NA all mmol/l 98.26 {mmol/l:98.26,mmol/:1.16,umol/l:0.58} mmol/l 1231 169 [132,135,137,138,139,140,141,142,143] [134,136,137,139,140,140,141,142,143] 0.0551 0.1344 FAIL -0.9083 0.438 PASS 1 6 PASS PASS PASS_at_T_(2/3) +unambiguous i-statk NA NA NA NA all mmol/l 98.81 {mmol/l:98.81,umol/l:0.6,mmol/:0.6} mmol/l 1230 166 [3.3,3.6,3.7,3.8,3.9,4,4.2,4.3,4.6] [3.3,3.5,3.6,3.8,3.9,4,4.2,4.3,4.5] 0.06251 0.2274 FAIL -0.9169 0.4431 PASS 0 0.9 PASS PASS PASS_at_T_(2/3) +unambiguous li-igg/alb NA NA NA NA all osuus 99.76 {osuus:99.76,ratio:0.24} osuus 1212 823 [0.09,0.1,0.11,0.13,0.14,0.15,0.17,0.2,0.28] [0.09,0.1,0.11,0.12,0.13,0.14,0.15,0.17,0.238] 0.08623 2.899 PASS 2.772 2.249 FAIL 0.01 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous p-gfreepi NA NA NA NA all ml/min/173m2 100 {ml/min/173m2:100} ml/min/173m2 1212 6373 [18.72,36.14,45.36,51.5,55.85,59.66,65.24,69.9,76.9] [23.24,37.04,43.5,48.7,53,56.3,59.6,65.8,73.1] 0.1066 9.811 PASS 3.509 3.335 FAIL 2.85 33.6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-omagluk NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1212 255 [5.4,5.9,6.4,6.8,7.3,7.9,8.4,9.5,12.1] [5.8,6.2,6.6,6.9,7.3,7.8,8.7,9.6,11.36] 0.07709 0.8125 FAIL 0.3778 0.1514 PASS 0 3.6 PASS PASS PASS_at_T_(2/3) +unambiguous p-kreatiniini NA NA NA NA all umol/l 100 {umol/l:100} umol/l 1210 116933 [59,98,104,110,117,127,143,166,209] [55,61,66,71,77,83,91,103,130] 0.5727 300 FAIL 20.52 79.93 FAIL 40 45 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-hcg-tot NA NA NA NA all iu/l 100 {iu/l:100} iu/l 1197 3737 [4.8,11.8,27.38,66.42,147.2,352,1044,3432,1.564e+04] [4,10.32,28.4,72.58,183.5,425.9,1037,3053,1.542e+04] 0.03315 0.5771 FAIL -0.2025 0.07594 PASS 36.3 540.9 PASS PASS PASS_at_T_(2/3) +unambiguous s-shbg NA NA NA NA all nmol/l 100 {nmol/l:100,g/l:0} nmol/l 1192 28134 [15,20,24,28,33,37,44,52,64] [17,21,25,29,33,38,44,52,65] 0.04081 1.366 PASS -0.7427 0.3393 PASS 0 33 PASS PASS PASS_at_KS_(3/3) +unambiguous u-sakka,eryt NA NA NA NA all u/field 100 {u/field:100} u/field 1161 85 [0,0,0,0,1,1,2,3,8] [0,1,1,1,1,2,2.8,4,7] 0.3415 8.008 FAIL -0.516 0.2169 PASS 0 3 PASS PASS PASS_at_T_(2/3) +unambiguous u-alb-mi NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1149 6339 [1,3,4,6,8,11,18,40,143] [3,4,5.5,7.576,11,18.48,35.4,84.52,321] 0.1507 19.01 PASS -3.853 3.919 FAIL 3 24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-haptog NA NA NA NA all g/l 100 {g/l:100} g/l 1142 10330 [0.68,0.97,1,1.064,1.345,1.65,2,2.05,2.93] [0.47,0.7,0.9,1.13,1.31,1.54,1.8,2.18,2.7] 0.1397 17.24 PASS 3.316 3.028 FAIL 0.035 1.65 PASS PASS PASS_at_KS_(2/3) +unambiguous s-alb NA NA NA NA all g/l 99.91 {g/l:99.91,%:0.05,mg/g:0.03} g/l 1141 23178 [32,35,36.4,37.5,38.6,39.6,40.9,42,44] [34,36.9,38,39,40,41,42,43,45] 0.191 34.48 PASS -9.29 19.17 FAIL 1.4 9 PASS PASS PASS_at_KS_(2/3) +unambiguous gluk-pika NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1140 727 [5.5,6.1,6.5,7.1,7.7,8.5,9.4,10.7,12.8] [5,5.5,5.9,6.2,6.6,7.2,7.9,9.08,11.4] 0.1982 15.02 PASS 5.046 6.295 FAIL 1.1 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-hco3-st NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1122 104777 [18,20,21,23,23,24,25,26,28] [20,21,22,23,24,25,25,26,28] 0.092 7.899 PASS -4.621 5.371 FAIL 1 6 PASS PASS PASS_at_KS_(2/3) +unambiguous crppika NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1122 869 [6,9,13,19.4,27,37,51,74.8,111] [6,7,10,13,18,26,39,56,88.2] 0.126 6.51 PASS 5.477 7.312 FAIL 9 36 PASS PASS PASS_at_KS_(2/3) +unambiguous s-pölyer NA NA NA NA all u/ml 99.02 {u/ml:99.02,form:0.79,estimate:0.19} u/ml 1120 7301 [0.03,0.05,0.09,0.216,0.575,1.624,3.573,8.788,22.06] [0.03,0.04,0.05,0.09,0.19,0.54,1.84,5.68,16.4] 0.1304 14.12 PASS 3.206 2.861 FAIL 0.385 0.51 PASS PASS PASS_at_KS_(2/3) +unambiguous b-gluk/pi NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1119 295 [5.3,5.8,6.3,6.7,7.4,8.1,9.2,10.4,12.84] [4.9,5.4,5.8,6.2,6.6,7.2,7.8,9.22,12.54] 0.1551 4.644 PASS 2.703 2.148 FAIL 0.8 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous s-t3-v NA NA NA NA all pmol/l 99.99 {pmol/l:99.99,pmol/:0.01} pmol/l 1116 18326 [3.5,3.8,4,4.2,4.4,4.6,4.8,5.2,5.8] [3.7,4.1,4.3,4.5,4.7,4.9,5.1,5.4,6.095] 0.1496 20.28 PASS -8.972 18.04 FAIL 0.3 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous s-mpoabg NA NA NA NA all iu/ml 98.8 {iu/ml:98.8,u/ml:1.2} iu/ml 1105 1315 [4.2,5.6,7.2,9.1,11,16,23,35,57] [3.6,4.8,6.2,7.7,9.7,13,18.8,28.2,49] 0.08196 3.236 PASS 2.755 2.228 FAIL 1.3 16.8 PASS PASS PASS_at_KS_(2/3) +unambiguous b-crp-pik NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1059 353 [7,10,14,19,25,34,46,60,97] [9,13,17,23,30,40,51.8,72,105.8] 0.08782 1.486 PASS -2.634 2.061 FAIL 5 54 PASS PASS PASS_at_KS_(2/3) +unambiguous b-pvk+tkd,leuk NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1051 3390 [4.4,5.1,5.6,6.1,6.7,7.4,8,8.7,10.2] [4.6,5.3,5.9,6.5,7.1,7.7,8.4,9.4,10.9] 0.06786 2.933 PASS -4.69 5.535 FAIL 0.4 4.8 PASS PASS PASS_at_KS_(2/3) +unambiguous s-sappih NA NA NA NA all umol/l 100 {umol/l:100} umol/l 1039 9064 [2,3,3,4,4.4,5.1,7,10,18] [2,2.9,3.5,4.4,6,7.6,10.7,17,32.07] 0.1419 16.11 PASS -3.752 3.738 FAIL 1.6 10.5 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-c-pept NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 1029 14049 [0.2316,0.4,0.543,0.66,0.778,0.9108,1.08,1.329,1.705] [0.23,0.4,0.54,0.67,0.79,0.9318,1.13,1.4,1.95] 0.04121 1.126 FAIL -4.433 4.998 FAIL 0.012 1.11 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-lzm NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1022 24683 [5.21,7.42,8.73,10,11,12,13.2,15,18.28] [1.8,8,10,11,12,13.2,14.9,16,19] 0.1322 14.68 PASS -2.802 2.287 FAIL 1 9 PASS PASS PASS_at_KS_(2/3) +unambiguous u-sakka,leuk NA NA NA NA all u/field 100 {u/field:100} u/field 1002 85 [0,0,0,0,0,1,2,5,11.9] [0,0,0,0,0,1,1,2,5] 0.1061 0.4997 FAIL 1.483 0.8506 PASS 0 0 PASS PASS PASS_at_T_(2/3) +ambiguous b-hkr split_by_score 0.8595 0.9783 0 low osuus 46.72 {%:53.16,osuus:46.72,fl:0.08} osuus 1558906 4240703 [0.32,0.35,0.37,0.386,0.4,0.41,0.42,0.44,0.46] [0.31,0.34,0.36,0.38,0.39,0.41,0.42,0.44,0.46] 0.03919 300 PASS 10.5 25.04 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +ambiguous b-hkr split_by_score 0.8595 0.9783 0 high % 53.16 {%:53.16,osuus:46.72,fl:0.08} % 191557 4824770 [32,34,37,38,39,41,42,43,45] [30,33,36,38,39,41,42,43,45] 0.05765 300 PASS 53.64 300 FAIL 0 12 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tt-inr skipped NA NA NA all inr 93.35 {inr:93.35,form:6.65,1:0.01} inr 1026823 339780 [1,1.1,1.2,1.6,2,2.2,2.5,2.7,3.1] [1,1,1.1,1.2,1.5,2,2.3,2.6,3] 0.1171 300 PASS 97.96 300 FAIL 0.5 1.5 PASS PASS PASS_at_KS_(2/3) +ambiguous s-ph skipped NA NA NA all 1 83.33 {1:83.33,ph:16.67} 1 396270 140 [7.34,7.36,7.37,7.38,7.39,7.41,7.42,7.43,7.45] [7.36,7.38,7.39,7.4,7.405,7.42,7.42,7.43,7.45] 0.1458 2.334 PASS -2.552 1.929 FAIL 0.015 0.045 PASS PASS PASS_at_KS_(2/3) +ambiguous b-eos skipped NA NA NA all e9/l 97.68 {e9/l:97.68,%:2.3,e6/l:0.02} e9/l 382440 1092967 [0.01,0.04,0.08,0.11,0.14,0.18,0.22,0.29,0.42] [0.02,0.07,0.1,0.12,0.15,0.19,0.23,0.3,0.4] 0.06737 300 PASS 2.498 1.903 FAIL 0.01 0.24 PASS PASS PASS_at_KS_(2/3) +ambiguous ab-ph skipped NA NA NA all ph 72.83 {ph:72.83,form:26.24,mmol/l:0.44} ph 380651 2975 [7.33,7.36,7.39,7.4,7.42,7.43,7.45,7.46,7.49] [7.37,7.39,7.41,7.42,7.43,7.44,7.45,7.47,7.48] 0.1419 51.61 PASS -14.52 45.54 FAIL 0.01 0.09 PASS PASS PASS_at_KS_(2/3) +ambiguous b-monos skipped NA NA NA all e9/l 97.82 {e9/l:97.82,%:2.18} e9/l 373740 965697 [0.34,0.42,0.47,0.53,0.58,0.65,0.72,0.82,0.98] [0.32,0.4,0.46,0.5,0.57,0.61,0.7,0.78,0.92] 0.05309 300 PASS 41.14 300 FAIL 0.01 0.45 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tsh skipped NA NA NA all mu/l 97.24 {mu/l:97.24,miu/l:2.41,mlu/l:0.35} mu/l 344154 1315114 [0.48,0.93,1.26,1.56,1.89,2.2,2.62,3.27,4.4] [0.53,0.92,1.21,1.5,1.8,2.1,2.51,3.1,4.2] 0.03165 237.1 PASS -24.22 128.8 FAIL 0.09 2.43 PASS PASS PASS_at_KS_(2/3) +ambiguous b-ly skipped NA NA NA all e9/l 97.41 {e9/l:97.41,%:2.59} e9/l 335323 784182 [0.8,1.07,1.28,1.48,1.67,1.89,2.13,2.44,2.97] [0.9,1.16,1.38,1.56,1.74,1.94,2.18,2.48,2.94] 0.05066 300 PASS -1.136 0.592 PASS 0.07 1.56 PASS PASS PASS_at_KS_(3/3) +ambiguous u-suhti skipped NA NA NA all kg/l 91.82 {kg/l:91.82,g/ml:6.83,ratio:1.26} kg/l 261486 41398 [1.01,1.013,1.015,1.015,1.018,1.02,1.02,1.024,1.026] [1.01,1.01,1.013,1.015,1.015,1.02,1.02,1.021,1.025] 0.1232 300 PASS -0.627 0.2752 PASS 0.003 0.015 PASS PASS PASS_at_KS_(3/3) +ambiguous u-keto-o skipped NA NA NA all estimate 94.61 {estimate:94.61,l:4.7,form:0.69} estimate 49568 133623 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.00291 0.03687 FAIL 5.854 8.315 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-ph-o skipped NA NA NA all N 52.17 {N:52.17,form:47.78,70:0.03} N 48516 2076 [5,5.5,6,6,6,6.5,7,7,7.5] [5.5,6,6,6,6.5,7,7,7,7.5] 0.151 39.36 PASS -16.11 54.73 FAIL 0.5 1.5 PASS PASS PASS_at_KS_(2/3) +ambiguous b-ghb-a1c skipped NA NA NA all % 95.93 {%:95.93,mmol/mol:4.07} % 39036 48557 [5.2,5.5,5.6,5.8,6.1,6.3,6.7,7.4,8.5] [5.2,5.4,5.5,5.7,5.8,6,6.3,6.8,7.8] 0.1436 300 PASS 28 170.3 FAIL 0.3 1.2 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tromboplastiiniaika,inr-tulostus skipped NA NA NA all inr 57.5 {inr:57.5,1:40,form:2.5} inr 38382 92 [1.1,1.4,1.9,2.1,2.3,2.5,2.7,2.9,3.3] [1.8,2.1,2.2,2.3,2.5,2.66,2.7,2.9,3.1] 0.1638 1.899 PASS -2.477 1.821 FAIL 0.2 0.9 PASS PASS PASS_at_KS_(2/3) +ambiguous mono split_by_score 2.627 0.7429 0 low e9/l 15.13 {%:84.87,e9/l:15.13} e9/l 17003 7454 [0.39,0.45,0.5,0.57,0.62,0.7,0.78,0.88,1] [0.36,0.42,0.47,0.52,0.57,0.62,0.68,0.74,0.86] 0.148 98.76 PASS 22.25 107.5 FAIL 0.05 0.39 PASS PASS PASS_at_KS_(2/3) +ambiguous mono split_by_score 2.627 0.7429 0 high % 84.87 {%:84.87,e9/l:15.13} % 13637 41798 [6,7,8,8,9,10,11,12,14] [5.1,7,7.7,8,9,10,10.4,12,13.9] 0.05219 24.05 PASS 9.37 20.1 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +ambiguous baso skipped NA NA NA all e9/l 13.73 {%:86.27,e9/l:13.73} e9/l 30199 8002 [0,0.02,0.03,0.04,0.05,0.08,1,1,1] [0.02,0.02,0.03,0.04,0.04,0.05,0.06,0.07,0.08] 0.3413 300 FAIL 103 300 FAIL 0.01 0.06 PASS PASS PASS_at_MAD_(1/3) +ambiguous lymf split_by_score 7.03 0.7018 0 low e9/l 13.98 {%:86.02,e9/l:13.98} e9/l 12928 7619 [0.95,1.16,1.35,1.54,1.75,1.96,2.19,2.51,3.04] [1.06,1.34,1.51,1.68,1.84,2.03,2.23,2.5,2.92] 0.09616 38.31 PASS -2.645 2.087 FAIL 0.09 1.35 PASS PASS PASS_at_KS_(2/3) +ambiguous lymf split_by_score 7.03 0.7018 0 high % 86.02 {%:86.02,e9/l:13.98} % 13769 46895 [14,18,22,25,28,31,34,38,45] [13,18,22,25,28,31,34,37,43] 0.03562 11.45 PASS 11.49 29.71 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) +ambiguous s-tsh skipped NA NA NA all mu/l 72.2 {mu/l:72.2,miu/l:27.73,u/l:0.04} mu/l 26229 248419 [0.41,0.863,1.17,1.42,1.7,2.04,2.46,3.1,4.41] [0.62,0.91,1.13,1.39,1.6,1.84,2.2,2.62,3.5] 0.0714 104.9 PASS 8.223 15.68 FAIL 0.1 1.92 PASS PASS PASS_at_KS_(2/3) +ambiguous b-lymfos skipped NA NA NA all e9/l 96.27 {e9/l:96.27,%:3.73} e9/l 19817 4466 [0.89,1.12,1.3,1.48,1.65,1.83,2.05,2.34,2.83] [1.02,1.29,1.46,1.63,1.81,2,2.22,2.53,3.01] 0.09359 27.51 PASS -0.4248 0.1733 PASS 0.16 1.44 PASS PASS PASS_at_KS_(3/3) +ambiguous b-neutr skipped NA NA NA all e9/l 76.51 {e9/l:76.51,%:23.49} e9/l 19426 7723 [2.07,2.6,3.02,3.43,3.85,4.32,4.9,5.73,7.24] [1.9,2.34,2.756,3.158,3.59,4.07,4.67,5.41,6.87] 0.07016 23.37 PASS 4.47 5.104 FAIL 0.26 3.57 PASS PASS PASS_at_KS_(2/3) +ambiguous b-hb-a1c skipped NA NA NA all % 85.06 {%:85.06,mmol/mol:14.85,%/mmol:0.06} % 18914 43586 [5.4,5.5,5.6,5.8,6,6.2,6.5,7.2,8.1] [5.3,5.4,5.6,5.8,5.9,6.1,6.4,6.9,7.7] 0.05016 28.55 PASS 7.633 13.63 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) +ambiguous u-suhteellinentiheys skipped NA NA NA all 1 78.44 {1:78.44,kg/l:21.56} 1 17548 262 [1.01,1.012,1.015,1.015,1.017,1.02,1.02,1.023,1.025] [1.01,1.015,1.015,1.015,1.02,1.02,1.02,1.025,1.025] 0.1136 2.631 PASS -0.06127 0.02174 PASS 0.003 0.015 PASS PASS PASS_at_KS_(3/3) +ambiguous eos skipped NA NA NA all % 91.96 {%:91.96,e9/l:8.04} % 14491 49739 [0,1,2,2,3,3,4,5,7] [0,1,2,2,3,3,4,5,6] 0.03345 10.61 PASS 5.809 8.197 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +ambiguous s-ttgaba skipped NA NA NA all u/ml 91.82 {u/ml:91.82,eliau/ml:7.73,form:0.44} u/ml 13768 32224 [0.2,0.3,0.4,0.5,0.6,0.7,0.8,1.1,1.9] [0.2,0.3,0.4,0.5,0.6,0.7,0.8,1.1,1.9] 0.01981 2.992 PASS -4.377 4.917 FAIL 0 0.9 PASS PASS PASS_at_KS_(2/3) +ambiguous neut skipped NA NA NA all % 93.42 {%:93.42,e9/l:6.58} % 12259 61798 [42,48,52,55,58,61,64,68,74] [43.1,49,52.8,56,59,62,65,69.4,75.4] 0.03737 12.12 PASS -8.523 16.78 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +ambiguous fp-pth skipped NA NA NA all ng/l 80.05 {ng/l:80.05,pmol/l:19.95} ng/l 11194 122007 [7,15,36,50,63,77,92,116,169] [35,51,66,84,106,135,179,253,408] 0.2661 300 PASS -67.71 300 FAIL 43 177 PASS PASS PASS_at_KS_(2/3) +ambiguous b-erytrosyytit,tilavuusosuus skipped NA NA NA all osuus 77.47 {osuus:77.47,%:22.53,1:0} osuus 10999 292478 [0.34,0.37,0.38,0.4,0.41,0.42,0.43,0.44,0.46] [0.31,0.34,0.37,0.38,0.4,0.41,0.42,0.44,0.46] 0.1015 94.72 PASS -0.7254 0.3295 PASS 0.01 0.12 PASS PASS PASS_at_KS_(3/3) +ambiguous p-antifxa skipped NA NA NA all iu/ml 56.03 {iu/ml:56.03,u/ml:43.91,umol/l:0.06} iu/ml 10859 13789 [0.13,0.17,0.21,0.26,0.31,0.38,0.45,0.54,0.7] [0.13,0.16,0.21,0.25,0.3,0.36,0.42,0.51,0.68] 0.04087 8.526 PASS 4.094 4.371 FAIL 0.01 0.39 PASS PASS PASS_at_KS_(2/3) +ambiguous fs-trfesat skipped NA NA NA all % 80.03 {%:80.03,osuus:18.85,1:1.13} % 10835 1915 [0.09,0.13,0.16,0.19,0.22,0.25,0.29,0.34,0.42] [7,11,14,17,20,23,27,32,39] 0.9897 300 FAIL -65.58 300 FAIL 19.78 24 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-happamuusaste bimodal_cautious 6.205 0.1646 0 low 1 91.97 {1:91.97,5170:7.63,form:0.4} 1 2901 229 [5,5.5,5.5,5.5,6,6,6,6,6] [5.5,6,6,6,6,6,6.5,6.5,7] 0.3319 20.58 FAIL -13.77 31.58 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-happamuusaste bimodal_cautious 6.205 0.1646 0 high 1 91.97 {1:91.97,5170:7.63,form:0.4} 1 7722 229 [6.5,6.5,7,7,7,7,7.5,7.5,8] [5.5,6,6,6,6,6,6.5,6.5,7] 0.6681 97.2 FAIL 24.78 67.43 FAIL 1 0 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous p-tromboplastiiniaika,inr-tulos skipped NA NA NA all inr 52.05 {inr:52.05,1:47.95} inr 8123 6341 [1.7,2,2.2,2.3,2.5,2.6,2.8,3,3.4] [1,1.1,1.1,1.3,1.9,2.2,2.4,2.7,3.1] 0.3644 300 FAIL 44.74 300 FAIL 0.6 2.4 PASS PASS PASS_at_MAD_(1/3) +ambiguous b-pvk+t skipped NA NA NA all % 43.01 {%:43.01,e9/l:23.04,g/l:13.71} % 7646 8614 [1,1,1,1,1,1,1,1,1] [6,10,12,13,14,28,39,52,62] 0.9975 300 FAIL 1.556 0.9216 PASS 13 27 PASS PASS PASS_at_T_(2/3) +ambiguous s-ccpab skipped NA NA NA all u/ml 83.24 {u/ml:83.24,eliau/ml:15.54,form:1.22} u/ml 7611 30305 [0.6,0.7,0.9,1,1.1,1.3,1.5,1.8,5] [0.6,0.8,0.9,1,1.2,1.4,1.6,2.2,21] 0.06054 19.1 PASS -8.189 15.55 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) +ambiguous l-mono skipped NA NA NA all % 97.66 {%:97.66,e9/l:2.34} % 7071 58379 [2.6,5,6.9,7.6,8.1,9,10,11.3,13] [4.6,6,7,8,9,9.3,10,11.7,14] 0.07021 26.75 PASS -8.86 18.02 FAIL 0.9 6 PASS PASS PASS_at_KS_(2/3) +ambiguous l-ly split_by_score 6.662 0.7783 0 low e9/l 2.01 {%:97.98,e9/l:2.01,osuus:0} e9/l 1408 2846 [1.097,1.38,1.59,1.76,1.93,2.1,2.31,2.59,2.98] [1.1,1.3,1.5,1.7,1.83,2,2.2,2.5,2.9] 0.07858 4.785 PASS 2.455 1.849 FAIL 0.1 1.29 PASS PASS PASS_at_KS_(2/3) +ambiguous l-ly split_by_score 6.662 0.7783 0 high % 97.98 {%:97.98,e9/l:2.01,osuus:0} % 5054 138412 [15.63,19.6,23,25.9,28.2,31,34,37.7,43.57] [13,18,22,25.1,28.1,31.2,34.9,38.9,45] 0.04859 9.719 PASS 1.478 0.8553 PASS 0.1 24.3 PASS PASS PASS_at_KS_(3/3) +ambiguous p-rf skipped NA NA NA all iu/ml 92.76 {iu/ml:92.76,u/ml:7.21,iu/l:0.03} iu/ml 6213 10583 [5,6,7,9,11,14,20,34,86] [7,10,11,12.7,15,19,27,48.3,105] 0.2662 244.7 PASS -6.241 9.351 FAIL 4 18 PASS PASS PASS_at_KS_(2/3) +ambiguous s-fsh skipped NA NA NA all iu/l 51.12 {iu/l:51.12,u/l:48.88} iu/l 6137 14866 [3.1,4.6,5.9,7.1,8.9,13,23.6,44.08,69.4] [3.3,4.7,6,7.6,10.1,17.2,33.1,51.9,72.9] 0.05693 11.95 PASS -5.692 7.89 FAIL 1.2 20.7 PASS PASS PASS_at_KS_(2/3) +ambiguous u-osmoest skipped NA NA NA all mosm/kgh2o 60.17 {mosm/kgh2o:60.17,mosm/l:34.05,e6/l:5.78} mosm/kgh2o 5941 25256 [340,440,520,550,630,700,740,850,960] [330,440,520,550,630,700,740,850,1000] 0.02943 3.326 PASS -5.525 7.464 FAIL 0 450 PASS PASS PASS_at_KS_(2/3) +ambiguous neutrofiilit bimodal 53.09 0.6531 0 low % 70.69 {%:70.69,e9/l:29.31,52%:0} % 2762 25265 [1,3,5,7,11,16,23,31,42] [43,48,52,56,59,62,65,69,75] 0.8126 300 FAIL -138.2 300 FAIL 48 24 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous neutrofiilit bimodal 53.09 0.6531 0 high % 70.69 {%:70.69,e9/l:29.31,52%:0} % 1797 25265 [60,67,73,78,82,85,89,91,94] [43,48,52,56,59,62,65,69,75] 0.5689 300 FAIL 69.36 300 FAIL 23 24 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-klotsa split_by_score 35.23 0.9066 0 low nmol/l 79.87 {nmol/l:79.87,umol/l:20.06,âumol/l:0.07} nmol/l 733 37623 [0.644,1,1.1,1.4,1.6,1.9,2,2.3,2.78] [586,870,1100,1312,1520,1740,1986,2304,2797] 0.9978 300 FAIL -340.1 300 FAIL 1518 1704 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-klotsa split_by_score 35.23 0.9066 0 high nmol/l 79.87 {nmol/l:79.87,umol/l:20.06,âumol/l:0.07} nmol/l 3675 37623 [526,787.4,1014,1237,1458,1687,1930,2238,2697] [586,870,1100,1312,1520,1740,1986,2304,2797] 0.04005 4.375 PASS -4.016 4.221 FAIL 62 1704 PASS PASS PASS_at_KS_(2/3) +ambiguous s-digoks skipped NA NA NA all nmol/l 96.59 {nmol/l:96.59,ug/l:3.41} nmol/l 3559 18447 [0.5,0.6,0.6,0.7,0.8,0.9,1,1.1,1.3] [0.4,0.5,0.6,0.7,0.8,0.9,1,1.1,1.4] 0.03224 2.401 PASS -3.499 3.327 FAIL 0 0.6 PASS PASS PASS_at_KS_(2/3) +ambiguous s-tshrab skipped NA NA NA all iu/l 84.17 {iu/l:84.17,u/l:15.54,iu/ml:0.2} iu/l 3513 6615 [1.7,2.5,3,3.5,4.1,4.9,6.3,9,16] [1.7,2,2.4,2.9,3.3,3.9,5,7.3,14] 0.1548 47.72 PASS 5.067 6.382 FAIL 0.8 4.2 PASS PASS PASS_at_KS_(2/3) +ambiguous na skipped NA NA NA all mmol/l 19.19 {mmol/l:19.19,%:15.12,e9/l:14.7} mmol/l 3419 8463 [1.7,2,2.1,2.3,2.4,2.6,2.9,3.2,4.4] [1.3,2,3.1,3.8,4.1,4.82,6,11.7,139] 0.5017 300 FAIL 1.791 1.134 PASS 1.7 6 PASS PASS PASS_at_T_(2/3) +ambiguous b-hba1cvt skipped NA NA NA all mmol/mol 58.36 {mmol/mol:58.36,%:41.64} mmol/mol 3196 10683 [46,51,55,58,61,64,68,74,82] [41,45,48,51,54,57,61,66,75] 0.2325 116.7 PASS 18.64 73.96 FAIL 7 24 PASS PASS PASS_at_KS_(2/3) +ambiguous s-prealb split_by_score 6.265 0.9397 0 low g/l 46.45 {mg/l:53.55,g/l:46.45} g/l 2235 33018 [0.1,0.13,0.16,0.18,0.2,0.22,0.24,0.26,0.3] [0.09,0.12,0.16,0.18,0.2,0.22,0.24,0.26,0.29] 0.03626 2.1 PASS -0.5916 0.2564 PASS 0 0.18 PASS PASS PASS_at_KS_(3/3) +ambiguous s-prealb split_by_score 6.265 0.9397 0 high mg/l 53.55 {mg/l:53.55,g/l:46.45} mg/l 955 38068 [98.4,139,161.2,188,207,229,247,269,294] [122,158,184,205,224,241,260,281,312] 0.09698 7.354 PASS -6.33 9.431 FAIL 17 147 PASS PASS PASS_at_KS_(2/3) +ambiguous s-rf skipped NA NA NA all iu/ml 72.43 {iu/ml:72.43,kiu/l:25.76,u/ml:1.74} iu/ml 3025 11352 [5,6,7,8,9,10,11,15,40.6] [8,9,10,11,11.1,12,14,21,52.98] 0.3576 273.2 FAIL -2.897 2.423 FAIL 2.1 6.3 PASS PASS PASS_at_MAD_(1/3) +ambiguous p-inr-pika skipped NA NA NA all % 96.06 {%:96.06,inr:3.94} % 2999 829 [1.9,2.1,2.3,2.4,2.6,2.7,2.9,3.2,3.6] [1.8,2.1,2.2,2.4,2.5,2.6,2.8,3,3.3] 0.08404 3.716 PASS 4.052 4.269 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) +ambiguous s-prl skipped NA NA NA all mu/l 94.27 {mu/l:94.27,miu/l:5.51,nmol/l:0.19} mu/l 2987 28193 [137,180,218,259,308,369,452,588.8,900.6] [115,152.1,185,220,262,314,389,522.6,840] 0.101 23.73 PASS -0.08868 0.03183 PASS 46 342 PASS PASS PASS_at_KS_(3/3) +ambiguous s-mypnabg split_by_score 26.53 0.6575 0 low eiu 82.35 {eiu:82.35,au/ml:12.74,ru/ml:4.32} eiu 1163 7323 [0.5,0.9,1.4,2,2.7,3.7,5.3,7.5,13.18] [51,65,79,95,113,135,160,200,259.8] 0.9771 300 FAIL -129.9 300 FAIL 110.3 144 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-mypnabg split_by_score 26.53 0.6575 0 high eiu 82.35 {eiu:82.35,au/ml:12.74,ru/ml:4.32} eiu 1764 7323 [51,63,77,92.68,108,131,155,191,246.4] [51,65,79,95,113,135,160,200,259.8] 0.0287 0.7263 FAIL -1.654 1.008 PASS 5 144 PASS PASS PASS_at_T_(2/3) +ambiguous u-osmol skipped NA NA NA all mosm/kgh2o 95.64 {mosm/kgh2o:95.64,mo/kgh2o:3.88,form:0.35} mosm/kgh2o 2913 7279 [175,233.4,281,323,368,412,464,534,638] [171,228,276,320,367,417,474,544,645] 0.01897 0.3605 FAIL -0.5542 0.237 PASS 1 375 PASS PASS PASS_at_T_(2/3) +ambiguous li-igg-ind skipped NA NA NA all osuus 80.28 {osuus:80.28,index:10.18,ratio:8.34} osuus 2901 741 [0.41,0.44,0.47,0.49,0.51,0.54,0.59,0.69,0.99] [0.44,0.47,0.48,0.49,0.5,0.52,0.55,0.61,0.83] 0.1172 6.8 PASS 3.409 3.18 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +ambiguous b-mono skipped NA NA NA all e9/l 93.53 {e9/l:93.53,%:6.47} e9/l 2899 66813 [0.4,0.5,0.5,0.6,0.6,0.7,0.83,0.92,1.1] [0.32,0.4,0.48,0.5,0.59,0.61,0.7,0.8,0.92] 0.1804 78.87 PASS 10.97 26.73 FAIL 0.01 0.45 PASS PASS PASS_at_KS_(2/3) +ambiguous p-cmvnh skipped NA NA NA all iu/ml 82.84 {iu/ml:82.84,u/ml:17.16} iu/ml 2630 7076 [45,64,90.7,130,180,270,530,1100,4600] [41,54,72,101,153,234,410.5,849,2735] 0.07093 8.109 PASS 3.115 2.73 FAIL 27 327 PASS PASS PASS_at_KS_(2/3) +ambiguous u-veri-o skipped NA NA NA all form 97.62 {form:97.62,u/field:2.38} form 2524 41 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01783 -0 FAIL 2.933 2.469 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-tpoab skipped NA NA NA all iu/ml 58.56 {iu/ml:58.56,u/ml:41.28,form:0.11} iu/ml 2449 7169 [0.4,6,13.74,37,70,140.9,250,418.2,695.4] [4,8,13,31,41,64,140,271.4,546] 0.1186 22.1 PASS 7.955 14.63 FAIL 29 108 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tni split_by_score 0.3025 0.3568 0 low ng/l 89.7 {ng/l:89.7,ug/l:10.3} ng/l 520 218179 [0,0.006,0.0197,0.04,0.05,0.06,0.07,0.1,0.15] [4,5,7,10,15,24,46,119,764] 1 300 FAIL -49.15 300 FAIL 14.95 33 PASS PASS PASS_at_MAD_(1/3) +ambiguous p-tni split_by_score 0.3025 0.3568 0 high ng/l 89.7 {ng/l:89.7,ug/l:10.3} ng/l 1889 218179 [3,4,6,9,13,23,36.6,73,201.4] [4,5,7,10,15,24,46,119,764] 0.09576 14.67 PASS -14.21 43.5 FAIL 2 33 PASS PASS PASS_at_KS_(2/3) +ambiguous u-prot split_by_score 11.23 0.6347 0 low mg/l 55.44 {mg/l:55.44,g/l:44.55,mg/dl:0} mg/l 2060 14966 [0,0.09,0.1,0.2,0.3,0.4,0.7,1,1.807] [65,82,99,119,144,181,241,386,961] 0.9994 300 FAIL -23.1 115.3 FAIL 143.7 207 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-prot split_by_score 11.23 0.6347 0 high mg/l 55.44 {mg/l:55.44,g/l:44.55,mg/dl:0} mg/l 259 14966 [34,50,71.4,76.2,89,101.8,131,196.2,412.4] [65,82,99,119,144,181,241,386,961] 0.292 19.04 PASS -7.437 12.28 FAIL 55 207 PASS PASS PASS_at_KS_(2/3) +ambiguous s-hcg-b-v skipped NA NA NA all ug/l 93.46 {ug/l:93.46,pmol/l:6.48,iu/l:0.02} ug/l 2184 15974 [21,30,37,45,53,63,76,95,127.4] [22.69,30.8,38,45.3,54,63.9,76,93,123] 0.01979 0.3631 FAIL 1.734 1.08 PASS 1 69 PASS PASS PASS_at_T_(2/3) +ambiguous s-mypnabm skipped NA NA NA all index 56.62 {index:56.62,s/co:42.67,form:0.63} index 2145 1445 [1,1.58,2,2.5,3,3.5,4.5,5.8,8.16] [1.5,2.2,2.8,3.4,4.2,5.2,6.6,8.4,11] 0.1865 25.99 PASS -11.33 28.4 FAIL 1.2 6.3 PASS PASS PASS_at_KS_(2/3) +ambiguous l-mon skipped NA NA NA all % 88.17 {%:88.17,e9/l:11.83} % 2104 12735 [4,8,11,12,12,13,14,15,16] [6,7,7.5,8,8.7,9,10,10.7,12] 0.5543 300 FAIL 24.12 114.2 FAIL 3.3 4.8 PASS PASS PASS_at_MAD_(1/3) +ambiguous pt-ekg-12 skipped NA NA NA all form 80.56 {form:80.56,tehtu:16.67,u:2.78} form 2052 58 [0,0,0,0,0,0,1,1,1] [0,0,0,0,0,0,48.5,1.029e+05,2.109e+05] 0.3239 5.039 FAIL -3.733 3.359 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-enaab skipped NA NA NA all u/ml 87.7 {u/ml:87.7,ratio:12.2,titre:0.1} u/ml 1973 1690 [0.1,0.1,0.16,0.2,0.2,0.2,0.3,0.4,0.7] [0.1,0.1,0.2,0.2,0.2,0.2,0.3,0.4,1.2] 0.05344 1.978 PASS -3.039 2.622 FAIL 0 0.3 PASS PASS PASS_at_KS_(2/3) +ambiguous s-dmklots split_by_score 22.05 0.9235 0 low nmol/l 61.43 {nmol/l:61.43,umol/l:38.41,âumol/l:0.14} nmol/l 516 13627 [0.4,0.5,0.69,0.8,0.9,1,1,1.2,1.4] [349,489.2,603,718,842,973,1127,1319,1617] 0.9991 300 FAIL -210 300 FAIL 841.1 981 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-dmklots split_by_score 22.05 0.9235 0 high nmol/l 61.43 {nmol/l:61.43,umol/l:38.41,âumol/l:0.14} nmol/l 1421 13627 [386,542,698,816,928,1061,1226,1420,1707] [349,489.2,603,718,842,973,1127,1319,1617] 0.0867 8.139 PASS 5.861 8.258 FAIL 86 981 PASS PASS PASS_at_KS_(2/3) +ambiguous p-pct skipped NA NA NA all ug/l 93.91 {ug/l:93.91,ng/ml:6.09} ug/l 1917 23100 [0.05,0.07,0.09,0.11,0.14,0.18,0.28,0.51,1.33] [0.07,0.1,0.14,0.2,0.28,0.42,0.72,1.5,5.461] 0.2222 76.53 PASS -1.105 0.5702 PASS 0.14 0.6 PASS PASS PASS_at_KS_(3/3) +ambiguous s-pr3ab skipped NA NA NA all iu/ml 75.45 {iu/ml:75.45,u/ml:23.28,kiu/l:1.27} iu/ml 1866 2324 [2.55,3.6,5,6.9,9.85,15,26,39,66] [2.5,4.1,6.1,8.7,13,19,27,41,73] 0.07762 5.149 PASS -2.413 1.799 FAIL 3.15 29.1 PASS PASS PASS_at_KS_(2/3) +ambiguous s-crp-o skipped NA NA NA all mg/l 88.8 {mg/l:88.8,form:10.67,u/ml:0.35} mg/l 1736 2521 [5,7,10.05,14,19,28,38,57,94] [5,5,5.6,8,10,15,22,35,64] 0.2009 36.05 PASS 10.38 24.11 FAIL 9 15 PASS PASS PASS_at_KS_(2/3) +ambiguous b-tbifng skipped NA NA NA all iu/ml 96.03 {iu/ml:96.03,iu/l:3.93,form:0.03} iu/ml 1724 2858 [0,0,0,0,0.01,0.01,0.02,0.04,0.36] [0,0,0,0,0,0.01,0.01,0.03,0.09] 0.1051 10.07 PASS 3.322 3.043 FAIL 0.01 0 FAIL PASS PASS_at_KS_(1/3) +ambiguous du-prot split_by_score 15.1 0.6975 0 low mg 65.4 {mg:65.4,g:32.31,mg/24h:1.32} mg 915 9936 [0.13,0.2,0.3,0.436,0.6,0.8,1.1,1.71,3] [98,151,250,415,666,1040,1630,2570,4429] 0.997 300 FAIL -65.65 300 FAIL 665.4 1659 PASS PASS PASS_at_MAD_(1/3) +ambiguous du-prot split_by_score 15.1 0.6975 0 high mg 65.4 {mg:65.4,g:32.31,mg/24h:1.32} mg 802 9936 [101,155.2,243.9,362,500,688.4,1027,1782,3480] [98,151,250,415,666,1040,1630,2570,4429] 0.1102 7.577 PASS -5.619 7.608 FAIL 166 1659 PASS PASS PASS_at_KS_(2/3) +ambiguous s-chpnabm bimodal 0.9363 0.6431 0 low index 96.11 {index:96.11,u/ml:2.63,titre:0.69} index 682 841 [0.08,0.102,0.13,0.144,0.17,0.2,0.25,0.298,0.37] [0.05,0.07,0.08,0.1,0.12,0.14,0.17,0.21,0.29] 0.2482 20.15 PASS -0.676 0.3017 PASS 0.05 0.15 PASS PASS PASS_at_KS_(3/3) +ambiguous s-chpnabm bimodal 0.9363 0.6431 0 high index 96.11 {index:96.11,u/ml:2.63,titre:0.69} index 672 841 [2.3,3,3.5,4,4.5,5.2,6.2,7.5,9.99] [0.05,0.07,0.08,0.1,0.12,0.14,0.17,0.21,0.29] 0.9869 300 FAIL 19.23 65.74 FAIL 4.38 0.15 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous b-b-cd19 skipped NA NA NA all e9/l 66.67 {e9/l:66.67,e6/l:33.33} e9/l 1316 1826 [0,0,0,0.02,0.065,0.13,0.2,0.31,0.46] [0,0,0,0.01,0.06,0.13,0.2,0.29,0.47] 0.02213 0.07716 FAIL -2.042 1.384 FAIL 0.005 0.18 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-hepyabg skipped NA NA NA all u/ml 81.11 {u/ml:81.11,index:11,eiu:4.08} u/ml 1308 4091 [0.927,2.812,10,14,30,76.2,166.5,410,1600] [0.1,0.1,0.4,10,10.7,11.6,13.8,22.9,83] 0.3368 99.57 FAIL 12.38 32.66 FAIL 19.3 30.9 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-chpnabg skipped NA NA NA all eiu 42.53 {eiu:42.53,u/ml:35.3,bu/ml:10.86} eiu 1294 1829 [4.2,7.8,10.2,12.5,15.8,32,64,81.8,128] [45,52,60,70,82,95,114,141,184] 0.5852 240.5 FAIL -23.19 108.3 FAIL 66.2 90 PASS PASS PASS_at_MAD_(1/3) +ambiguous i-stathct bimodal 0.8089 0.9655 0 low %pcv 60.91 {%pcv:60.91,%:35.45,mmol/l:1.82} %pcv 1018 67 [0.33,0.36,0.39,0.4,0.41,0.43,0.44,0.46,0.49] [34.6,37,38,40,41,42,44,46,46.4] 1 107.6 FAIL -53.01 55.1 FAIL 40.59 12 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous i-stathct bimodal 0.8089 0.9655 0 high %pcv 60.91 {%pcv:60.91,%:35.45,mmol/l:1.82} %pcv 222 67 [32,35.2,38,40,41,42,44,46,47] [34.6,37,38,40,41,42,44,46,46.4] 0.0712 0.0288 FAIL -0.7825 0.3611 PASS 0 12 PASS PASS PASS_at_T_(2/3) +ambiguous u-epitel bimodal 1.004 0.7048 0 low /sunf 95.22 {/sunf:95.22,sunf:4.78} /sunf 902 1316 [0,0,0,0,0,1,1,1,1] [0,0,0,0,0,0,0,1,2] 0.2103 20.48 PASS -1.413 0.8017 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +ambiguous u-epitel bimodal 1.004 0.7048 0 high /sunf 95.22 {/sunf:95.22,sunf:4.78} /sunf 218 1316 [2,2,2,2,2,3,3,4,5] [0,0,0,0,0,0,0,1,2] 0.8685 154 FAIL 19.8 52.93 FAIL 2 0 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous c-reaktiivinenproteiini,vieritutkimus,plasmasta skipped NA NA NA all mg/l 95 {mg/l:95,1:5} mg/l 1118 38 [3.2,6,9.01,14,20,29,41,62,95] [5.85,6.64,8.47,11,15,22.8,56.2,59.6,94.4] 0.1044 0.1088 FAIL 0.1372 0.04983 PASS 5 27.75 PASS PASS PASS_at_T_(2/3) +ambiguous s-gadab skipped NA NA NA all iu/ml 77.97 {iu/ml:77.97,ru:20.5,u/ml:1.16} iu/ml 1035 1685 [0.1,0.1,1,1,1,1,3.8,22.2,136] [1,1,1,1,1,2,11.8,55,207.6] 0.2763 42.88 PASS -1.673 1.025 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +ambiguous s-hbsab skipped NA NA NA all miu/ml 70.21 {miu/ml:70.21,iu/l:16.15,u/l:12.92} miu/ml 1022 6885 [15.87,27,43,69.72,100.1,153.2,230,330.8,560] [19,32,50,77,122,186,280,418,638.6] 0.05887 2.398 PASS -3.896 3.99 FAIL 21.9 294 PASS PASS PASS_at_KS_(2/3) diff --git a/scripts/injection/data/plot_name_level.tsv b/scripts/injection/data/plot_name_level.tsv deleted file mode 100644 index bf062cc..0000000 --- a/scripts/injection/data/plot_name_level.tsv +++ /dev/null @@ -1,1026 +0,0 @@ -TEST_NAME total_count top_prevalence --cd4-solujensuhdecd8-soluihin 665 0.0 --cdt 239 100.0 --crppikatesti 196 0.0 --cyp4f2 1093 0.0 --glutamyylitransferaasi-desialotransferriini-indeksi 720 0.0 --h-ind 39809 0.0 --i-ind 9849 0.0 --kt/v,daugirdaksenkaava 176 0.0 --l-ind 15069 0.0 --nt 5011 100.0 --ph 903 0.0 --s.yht. 844 0.0 --slco1b1 869 0.0 --transf 269 100.0 --trfesat 5306 100.0 -120mp-glu 228 100.0 -14272 5212 0.0 -14593 144 0.0 -5400 373 0.0 -6820 170 0.0 -:glutamyylitransferaasi-desialotransferriini-indeksi 268 0.0 -ab-ahco3vt 157 100.0 -ab-be 52398 99.98203824573457 -ab-be-vt 210 0.0 -ab-caionvt 122 100.0 -ab-emäsylimäärä 3580 100.0 -ab-hco3-st 2478 100.0 -ab-pco2 3058 99.99767495094834 -ab-pco2-vt 170 0.0 -ab-ph 380522 98.68999999999998 -ab-ph(t) 4545 0.0 -ab-ph-vt 168 0.0 -ab-po2 3071 99.99763920547053 -ab-po2-vt 179 0.0 -as-eryt 767 100.0 -as-leuk 773 100.0 -astmatesti 136 0.0 -b-6-me-mp 488 0.0 -b-6-tgn 482 0.0 -b-angap 138 100.0 -b-b-cd19 1310 100.0 -b-ba/abs 1306 100.0 -b-baso 357874 99.8588409835393 -b-basof 19444 100.0 -b-be 15770 100.0 -b-co 483 100.0 -b-cr 456 100.0 -b-crp 3350 100.0 -b-crp-o 3079 100.0 -b-crp-os 462 0.0 -b-crp-ospkl 477 0.0 -b-crp-pik 1042 0.0 -b-crp-pika 798 0.0 -b-crp-v 202 100.0 -b-crp-vt 3956 100.0 -b-cya 116 100.0 -b-eos 381192 99.82971040616191 -b-eosin 19436 100.0 -b-eosinofiilit 250 100.0 -b-erblast 314346 100.0 -b-erybla 169159 100.0 -b-eryt 2702180 100.0 -b-erytroblastit 10379 100.0 -b-erytrosyytit 105 100.0 -b-erytrosyytit,tilavuusosuus 10924 77.48 -b-erytrosyytit,tilavuusosuus,pikahoitoyksiköt 196 0.0 -b-fidd-o 102 100.0 -b-fidd-vt 150 0.0 -b-fosfatidyylietanoli 344 0.0 -b-ghb-a1c 38232 100.0 -b-ghb-a1c,tk 5295 0.0 -b-ghba1c/p 183 0.0 -b-ghba1cp 3927 100.0 -b-gluk 295 0.0 -b-gluk-vt 154 0.0 -b-glukoosi,hoitoyksikönvieritesti,kokoveri 521 0.0 -b-hb 895386 100.0 -b-hb,tk 528 0.0 -b-hb-a1c 18829 99.88999628233044 -b-hb-co 125 100.0 -b-hb-hoi 136 0.0 -b-hb-met 133 100.0 -b-hb-pika 281 0.0 -b-hb-vt 1252 100.0 -b-hba1c 355680 100.0 -b-hba1c,t 4683 0.0 -b-hba1c,tk 6492 0.0 -b-hba1c-om 123 0.0 -b-hba1c-oma 239 0.0 -b-hba1c/pi 961 0.0 -b-hba1c/pika 867 0.0 -b-hba1cvt 3104 83.51364179104479 -b-hkr 1750455 66.66232347980981 -b-hkrhoi 155 0.0 -b-inr-pik 5420 100.0 -b-inr-vt 283 0.0 -b-inrpika 1503 100.0 -b-inrvieri 218 0.0 -b-k 420 0.0 -b-keto/pik 358 0.0 -b-konedif,baso 395 0.0 -b-konedif,eos 395 0.0 -b-konedif,lymf 395 0.0 -b-konedif,monos 395 0.0 -b-konedif,neutro 395 0.0 -b-krea 421 0.0 -b-la 156187 100.0 -b-laktevt 563 100.0 -b-leuc-v 538 0.0 -b-leuk 2609979 100.0 -b-leuk-hoi 105 0.0 -b-leuk-vt 806 100.0 -b-leuk/pi 367 0.0 -b-leukosyytit 5619 100.0 -b-ly 334997 99.39827286689368 -b-ly/abs 1306 100.0 -b-lymf 9905 100.0 -b-lymfos 19817 95.72 -b-mono 2791 99.98405458089668 -b-monos 373170 99.61871550051363 -b-multiplateadp 150 0.0 -b-na 418 0.0 -b-neut 678675 99.57806235359783 -b-neutr 19414 97.48 -b-neutrofiilit 257 100.0 -b-pco2 559 100.0 -b-peth 1406 100.0 -b-ph 3521 100.0 -b-po2 558 100.0 -b-pvk+t 7644 0.0 -b-pvk+tkd 782 0.0 -b-pvk+tkd,leuk 1051 100.0 -b-qr-crp 392 100.0 -b-retik 25381 100.0 -b-retind 1699 100.0 -b-t-cd4 128 100.0 -b-tacro 1877 100.0 -b-tbifng 1582 98.5439570164349 -b-ti 295 100.0 -b-tnt-o 237 99.91 -b-trom 2413261 100.0 -b-tromb 74939 100.0 -baso 25346 100.0 -bla 1034 0.0 -c-reaktiivinenproteiini,tk:ntekemä 201 0.0 -c6-indeksi 333 0.0 -ca++/7.40 27372 100.0 -ca++/ph7.4 343 100.0 -ca-ion 27146 100.0 -cb-ahco3 177 100.0 -cb-be 36509 100.0 -cb-bepika 634 0.0 -cb-crp 3380 0.0 -cb-emäsylimäärä 421 100.0 -cb-gluk-v 105 0.0 -cb-gluk-vt 243 100.0 -cb-hb 340 100.0 -cb-hbo2sat 246 100.0 -cb-hco3-st 7826 100.0 -cb-inr,pikamääritys 193 0.0 -cb-inr-oma 284 0.0 -cb-inrc-c 4271 0.0 -cb-inrpika 463 0.0 -cb-leuk-hy 187 100.0 -cb-pco2 8978 100.0 -cb-ph 104777 100.0 -cb-phpika 1696 0.0 -cb-po2 1218 100.0 -cb-tt-inr 112 100.0 -cb-tt-inrp 5576 0.0 -cb-tt-inrpika 4841 0.0 -cd4/cd8 3896 0.0 -cp-c-reaktiivinenproteiini,ihopiston,hoitoyksikössä 261 0.0 -cp-crp-hy 942 100.0 -cp-gluk 2125 100.0 -cp-gluk-hy 9537 100.0 -cp-gluk-po 1736 0.0 -cp-glukoosi,ihopistosn,vieritestihoitoyksikössä 3716 0.0 -cp-inr-hy 181 0.0 -cp-inr-vt 369 0.0 -crp 7205 0.0 -crp(päiv.hoitaja) 2927 100.0 -crp(vo:nyhteydessäotettu),tth 1267 100.0 -crp,tk 8883 0.0 -crp-pika 5345 100.0 -crppika 470 100.0 -crpvieri 571 100.0 -crpvieritesti 116 0.0 -cu-alb 1604 100.0 -cu-alb-mi 1340 100.0 -cu-kesto 767 100.0 -cu-tilav 770 100.0 -cu-vm 706 100.0 -cyp4f2-geeninnukleotidivariaatiot,dna-tutkimus 424 0.0 -du-ca 1118 99.2278175313059 -du-iglck 269 0.0 -du-iglcl 170 0.0 -du-krea 263 100.0 -du-metnef 235 100.0 -du-normet 235 100.0 -du-prot 1593 91.78401757689893 -du-tilav 338 100.0 -e-erytrosyytit,kokojakauma 1709 100.0 -e-mch 859143 99.9348185692021 -e-mchc 305071 100.0 -e-mcv 862958 100.0 -e-punasolujenkokojakauma 870 100.0 -e-rdw 444914 100.0 -e-retik 11832 100.0 -emäsylimäärä,kapillaariveri 991 0.0 -emäsylimäärä,koneveri 281 0.0 -emäsylimäärä,laskimoverestä,pikatesti 273 0.0 -emäsylimäärä,laskimoveri 1291 0.0 -emäsylimäärä,valtimoveri 346 100.0 -eos 14128 100.0 -eosin 441 100.0 -eosinofiil. 3566 0.0 -epit.solut 291 0.0 -epiteelit 152 100.0 -erblast 744 0.0 -erytroblastit 2654 100.0 -f-calpro 12541 100.0 -f-elast1 1570 100.0 -fb-folaat 251 100.0 -fb-gluk 302 100.0 -fb-leuk 78137 100.0 -fe-folaat 26985 100.0 -fibrosis-4-indeksi 458 0.0 -fibrosis-4indeksi 162 0.0 -fluor,nat,fl-clue 105 0.0 -fluor,nat,fl-hiiva 105 0.0 -fluor,nat,fl-leuk 102 0.0 -fluor,nat,muuta 104 0.0 -fosfatidyylietanoli 121 0.0 -fp-b6-vit 411 100.0 -fp-c-pept 477 100.0 -fp-ca 8237 100.0 -fp-ctx 253 0.0 -fp-fe 11013 100.0 -fp-gluk 377752 99.98829160401532 -fp-gluk,t 708 0.0 -fp-gluk/pi 108 0.0 -fp-gluk0 105 100.0 -fp-glukoosi 1341 99.93 -fp-kol 245681 100.0 -fp-kol-hdl 235216 100.0 -fp-kol-ind 5066 0.0 -fp-kol-ldl 300072 100.0 -fp-kolesteroli 562 100.0 -fp-krea 6187 100.0 -fp-laktaat 2177 100.0 -fp-nh4-ion 774 100.0 -fp-pi 8730 100.0 -fp-pth 9057 91.41072871811858 -fp-renin 101 100.0 -fp-renin-p 134 100.0 -fp-transf 12440 100.0 -fp-trfesat 2145 100.0 -fp-trigly 239085 100.0 -fp-urea 5197 100.0 -fs-a-vit 227 100.0 -fs-ace 202 100.0 -fs-c-pept 942 100.0 -fs-ca++/7.40 10495 0.0 -fs-ca-ion 10496 100.0 -fs-ca-ion/ph7.40 122 100.0 -fs-ca-iona 134 100.0 -fs-cga 167 99.82 -fs-e-vit 127 100.0 -fs-fe 483 100.0 -fs-folaat 26281 100.0 -fs-kol 3794 100.0 -fs-kol-hdl 3005 100.0 -fs-kol-ldl 3772 100.0 -fs-ph 30288 0.0 -fs-pi 803 100.0 -fs-pth 450 0.0 -fs-rf 293 100.0 -fs-sappih 1213 100.0 -fs-transf 231 100.0 -fs-transferiininrautakyllästeisyys 275 0.0 -fs-trfesat 10694 100.0 -fs-trigly 3024 100.0 -gluk-pika 1002 100.0 -glukoosi(päiv.hoitaja) 611 0.0 -glukoosi,pikatesti,veri 214 0.0 -glukoosi,vieritutkimus 140 0.0 -glukvieri 188 0.0 -gt-cdt-ind 2058 0.0 -happamuusaste 377 0.0 -happamuusaste,virtsasta 1393 0.0 -happamuusaste,virtsasta,vieritesti 122 0.0 -hb(päiv.hoitaja) 816 0.0 -hb-pika 345 100.0 -hba1c-pika 1437 0.0 -hcgbvkmom 20354 0.0 -hdl/kol 88970 100.0 -hdl/kol. 11548 100.0 -hemolyysi-indeksi 1344 0.0 -hoiglukstx 185 0.0 -i-statcl 574 0.0 -i-statcrea 1228 0.0 -i-statglu 573 0.0 -i-stathb 437 0.0 -i-stathct 1240 0.0 -i-statk 1230 0.0 -i-statna 1231 100.0 -i-staturea 522 0.0 -iga/prealb 1082 0.0 -ihopisto 206 0.0 -inr,tk 115 0.0 -inr-pika 4278 0.0 -inr-vieri 8630 0.0 -inr/hoito 1127 0.0 -inrpika 166 0.0 -kalium,hoitoyksikönvieritesti,veri 191 0.0 -koivu 123 100.0 -kol/hdl 397 0.0 -kol/hdl-su 945 0.0 -kol/hdlsuh 66868 0.0 -kolesteroli/hdl-suhde 33783 0.0 -kolesterolinjahdl-kolest.suhde 268 0.0 -kolesterolinjahdl-kolesterolinsuhde 549 0.0 -kt/v 168 0.0 -l-baso 16704 99.99862029831388 -l-baso(a) 48061 100.0 -l-basof 19090 100.0 -l-bla 1576 100.0 -l-blastit 295 100.0 -l-eos 20712 100.0 -l-eos(a) 49313 100.0 -l-eosin 19408 100.0 -l-liusk 110 100.0 -l-ly 5324 94.98890676296783 -l-lymf 17718 100.0 -l-lymf(a) 50542 100.0 -l-lymfos 19480 100.0 -l-lymfosyytit 258 100.0 -l-metam 1599 100.0 -l-metamye 292 100.0 -l-mon 1466 100.0 -l-mono 6751 100.0 -l-mono(a) 49676 100.0 -l-monos 31160 99.95724605172809 -l-monosyytit 227 100.0 -l-myel 1572 100.0 -l-myelos 286 100.0 -l-neut 16030 100.0 -l-neut(a) 48854 100.0 -l-neutr 20755 100.0 -l-neutrofiilit 258 100.0 -l-nlt 1564 100.0 -l-nst 1514 100.0 -l-prom 1494 100.0 -l-promyel 272 100.0 -leuk-pika 491 100.0 -leukosyytit 246 100.0 -leukpika 127 0.0 -li-alb 229 99.06 -li-eryt 3048 100.0 -li-gluk 458 100.0 -li-igg 427 99.03 -li-igg-ind 2821 100.0 -li-igg/alb 517 100.0 -li-laktaat 128 100.0 -li-leuk 3052 100.0 -li-prot 137 100.0 -lieriöt 2909 100.0 -lipemia-indeksi 987 0.0 -ly-cd4-t 128 100.0 -ly-cd4/cd8 2599 0.0 -ly-t-cd4/cd8,t-auttaja/estäjäsolujensuhde 109 0.0 -ly-tcd4/8. 1005 0.0 -lymf 26250 99.4563027875808 -lymfos 168 100.0 -marevan-hoidonseur.tatesti,hoitoyksikkötekeesormenpäänäyte 168 0.0 -mb-be 691 100.0 -mb-ph 612 0.0 -metam 1140 100.0 -mittaustulos(mg/l) 390 0.0 -mittaustulos(mmol/l) 552 0.0 -mono 25867 99.56393849126479 -mononukleaariset 4588 0.0 -monos 118 100.0 -myel 1135 100.0 -neut 12043 100.0 -neutrofiilit 4535 0.0 -nlt 1167 0.0 -non-hdl 65979 0.0 -non-hdl(paasto) 6004 0.0 -nst 1024 0.0 -nt- 631 0.0 -ntkmom 20440 0.0 -nu-alb 1492 100.0 -nu-albkre 761 100.0 -nu-albkrea 9486 100.0 -näköseula 151 0.0 -o2-virt 155 0.0 -oma-b-fid 109 0.0 -oma-b-hb 267 100.0 -oma-cp-glu 169 0.0 -oma-crp 21620 100.0 -oma-crp-pi 1174 0.0 -oma-crp-pika 1056 0.0 -oma-fp-glu 431 0.0 -oma-ghb-a1 851 0.0 -oma-ghb-a1c 646 0.0 -oma-gluk 18422 0.0 -oma-hb 1113 0.0 -oma-hba1c 1339 0.0 -oma-inr 3911 0.0 -oma-inr-pi 928 0.0 -oma-kol 199 0.0 -oma-p-crp 9028 100.0 -oma-p-gluk 1556 0.0 -oma-p-tnt 139 0.0 -oma-pt-ekg 372 0.0 -oma-u-tutk,u-alb-o 539 0.0 -oma-u-tutk,u-eryt-o 537 0.0 -oma-u-tutk,u-gluk-o 640 0.0 -oma-u-tutk,u-keto-o 622 0.0 -oma-u-tutk,u-leuk-o 574 0.0 -oma-u-tutk,u-nitr-o 612 0.0 -oma-u-tutk,u-ph 2210 0.0 -omaastmat 133 0.0 -omaastmatesti 127 0.0 -p-acth 133 99.93 -p-afos 179381 100.0 -p-alaniiniaminotransferaasi 550 100.0 -p-alat 483676 100.0 -p-alb 50728 100.0 -p-amyl 25628 100.0 -p-amylp 5116 100.0 -p-antifxa 10759 58.64722279022214 -p-apcres. 659 0.0 -p-aptt 1747 100.0 -p-asat 20668 100.0 -p-at3 164 100.0 -p-at3-spr 109 100.0 -p-at3. 171 100.0 -p-b12-vit 9335 100.0 -p-bil 45509 100.0 -p-bil-kj 5695 100.0 -p-bkvnh 607 63.26 -p-bnp 3561 99.98301158301157 -p-c-pept 377 100.0 -p-c-reaktiivinenproteiinipikahoitoyksiköt 389 100.0 -p-c3 510 100.0 -p-c4 369 100.0 -p-ca 24687 100.0 -p-ca++hoi 155 0.0 -p-ca-albk 18639 100.0 -p-ca-ion. 4176 100.0 -p-ca-iona 4341 100.0 -p-ca12-5 282 100.0 -p-cea 2741 100.0 -p-ck 17771 100.0 -p-ck-mb 114 100.0 -p-ck-mbm 7109 100.0 -p-cl 306 100.0 -p-cmvnh 2592 82.64 -p-crp 329221 100.0 -p-crp-hy 2326 100.0 -p-crp-o 8842 100.0 -p-crp-vt 3133 100.0 -p-d-25 37842 100.0 -p-digoks 126 0.0 -p-fe 476 100.0 -p-ferrit 65015 100.0 -p-fibr 1155 100.0 -p-fidd 11726 100.0 -p-fidd-o 543 100.0 -p-fsh 1798 100.0 -p-fviii 108 100.0 -p-fviii. 399 100.0 -p-gfreepi 1212 100.0 -p-gfrtest 1165 0.0 -p-gluk 34338 100.0 -p-gluk,tk 7190 0.0 -p-gluk-a2 167 100.0 -p-gluk-o 113 100.0 -p-gluk-vt 3258 100.0 -p-glukhoi 380 100.0 -p-glukoosipikahoitoyksiköt 373 100.0 -p-glukpoc 1562 100.0 -p-gt 103034 100.0 -p-happamuusaste(ionis.ca) 22410 0.0 -p-haptog 1631 100.0 -p-hcg 603 96.38199999999999 -p-hcg-tot 906 0.0 -p-hco3 558 100.0 -p-hcyst 106 100.0 -p-iga 9051 100.0 -p-ige 139 100.0 -p-igg 3539 100.0 -p-igm 2247 100.0 -p-il6 110 100.0 -p-inr 1094127 100.0 -p-inr(pikamittari) 479 100.0 -p-inr-hy 20228 0.0 -p-inr-o 525 0.0 -p-inr-oma 192 0.0 -p-inr-pi 2836 0.0 -p-inr-pik 1713 0.0 -p-inr-pika 2945 0.0 -p-inr-poc 191 0.0 -p-inr-vt 8458 100.0 -p-inrosoitus 120 0.0 -p-k 700837 100.0 -p-k-vt 1215 100.0 -p-kalium 363 100.0 -p-kaliumpikahoitoyksiköt 230 100.0 -p-kalsium,ionisoitunutpika,hoitoyksiköt 210 100.0 -p-khoi 242 100.0 -p-kol 63495 100.0 -p-kol-hdl 61069 100.0 -p-kol-ldl 76288 100.0 -p-korsol 2426 100.0 -p-krea 596970 100.0 -p-krea-vt 322 100.0 -p-kreatiniini 1159 100.0 -p-kysc 2515 100.0 -p-laktaattipikahoitoyksiköt 222 0.0 -p-lakthoi 228 100.0 -p-ld 5665 100.0 -p-lh 873 100.0 -p-lh/fsh 274 0.0 -p-luakptt 1658 100.0 -p-luakrvv 304 0.0 -p-mb/ck 114 0.0 -p-mg 11929 100.0 -p-myogl 666 100.0 -p-na 615154 100.0 -p-na-vt 473 100.0 -p-nh4-ion 136 100.0 -p-non-hdl 326 0.0 -p-omagluk 1161 0.0 -p-osmol 456 100.0 -p-pc 466 100.0 -p-pct 1810 88.72616862326575 -p-ph 7625 0.0 -p-pi 6523 100.0 -p-posturea 144 100.0 -p-prealb 1737 99.72802533103051 -p-preurea 326 100.0 -p-prl 1891 100.0 -p-probnp 41340 100.0 -p-ps 129 100.0 -p-ps-agv 188 100.0 -p-psa 85173 100.0 -p-psa,sädehoidettupotilas 893 0.0 -p-psa-suh 20275 99.91832351848905 -p-psa-v 38742 100.0 -p-psagen 935 100.0 -p-reninm 448 100.0 -p-rf 6126 98.30889537307212 -p-se 151 100.0 -p-shbg 668 100.0 -p-t3-v 7512 100.0 -p-t4-v 203141 100.0 -p-t4v 20603 100.0 -p-tfr 35584 100.0 -p-tkfiddo 152 100.0 -p-tni 2297 95.15649402390437 -p-tnt 32745 99.99244509249978 -p-tnt-o 168 100.0 -p-tpoab 541 0.0 -p-trigly 60045 100.0 -p-tromboplastiiniaika,inr,tt 9455 0.0 -p-tromboplastiiniaika,inr-tulos 8123 100.0 -p-tromboplastiiniaika,inr-tulostus 38382 100.0 -p-tromboplastiiniaika-pika,inrpika-tulos 331 0.0 -p-tsh 343875 99.25123681311499 -p-tt 5888 100.0 -p-tt-inr 1026698 93.64176207941482 -p-tt-inrp 162 0.0 -p-tt-inrqc 156 0.0 -p-tt. 179 100.0 -p-tyreotropiini 361 98.97999999999999 -p-uraat 37253 99.53553951485485 -p-urea 5524 100.0 -p-viskos 158 100.0 -p-zn 186 100.0 -p.-trombai 180 100.0 -paastoseeruminph 1457 0.0 -pappakmom 20435 0.0 -pd-leuk 745 100.0 -pf-ada/s-ada 121 0.0 -pf-eryt 2022 99.97 -pf-happamuusaste 119 0.0 -pf-leuk 2053 99.08 -pf-ph 2075 100.0 -pf-prot 103 100.0 -ph 164235 0.0 -ph,seerumista 198 0.0 -ph,seerumista,osatutk 1224 0.0 -phadiatop 331 100.0 -pika-crp 871 100.0 -pika-inr 2713 0.0 -pika-virtsaliuska,u-ph 108 0.0 -pika-virtsaliuska,u-suhti-o 108 0.0 -pikahb 419 0.0 -pikainr 973 0.0 -pikau-sti,u-eryt-o 359 0.0 -pikau-sti,u-gluk-o 358 0.0 -pikau-sti,u-keto-o 359 0.0 -pikau-sti,u-leuk-o 359 0.0 -pikau-sti,u-nitr-o 359 0.0 -pikau-sti,u-ph 358 0.0 -pikau-sti,u-prot-o 359 0.0 -pikau-stix,u-ph 1330 0.0 -pituus(cm) 4130 0.0 -plasmaninr(k) 299 0.0 -prom 1016 0.0 -ps-crp 462 0.0 -ps-gluk 166 0.0 -ps-inr 300 0.0 -psa-v/psa 12988 100.0 -pt-apri 190 0.0 -pt-audio/i 410 0.0 -pt-ekg-12 2051 0.0 -pt-fib-4 4395 0.0 -pt-fvspido 288 0.0 -pt-fvspiro 287 0.0 -pt-gfre 216653 100.0 -pt-gfre-3 188 100.0 -pt-gfre-cg 839 0.0 -pt-gfre-md 1584 100.0 -pt-gfreep 770 0.0 -pt-gfreepi 752135 99.11941275911894 -pt-gfreepinosatutkimus 649 0.0 -pt-gfreepio1 434 100.0 -pt-gfrekys 561 100.0 -pt-glomerulussuodatusnopeus 154 0.0 -pt-glomerulussuodosnopeus 201 0.0 -pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava 5151 100.0 -pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava(p-kreaosatutkimus) 171 100.0 -pt-glomerulussuodosnopeus,estimoituckd-epikaavallakystatiinic:stä 147 100.0 -pt-glomerulustensuodatusnopeus,estimoitu,mdrd-kaava 246 100.0 -pt-kt/v1 2648 0.0 -pt-lämpöt 104 100.0 -pt-paino 145 0.0 -pulssi 133 0.0 -punasolujenerittelylaskenta 404 0.0 -raskauksienmäärä,g 6870 0.0 -s-ace 484 100.0 -s-achr-ab 143 100.0 -s-adali 491 100.0 -s-afluust 125 100.0 -s-afmakro 125 100.0 -s-afmaksa 125 100.0 -s-afos 436 99.81743119266054 -s-afp 729 90.58901234567901 -s-afsuol1 125 100.0 -s-afsuol2 125 0.0 -s-afsuol3 125 100.0 -s-alat 158 99.92 -s-alb 996 100.0 -s-album 2535 100.0 -s-aldos 254 100.0 -s-aldos-p 137 100.0 -s-alfa-1 2517 100.0 -s-alfa-2 2509 100.0 -s-alfgale 102 100.0 -s-ana 1150 100.0 -s-anaab 204 100.0 -s-antitry 539 100.0 -s-apob/a1 2604 0.0 -s-apob/a1-suhde 793 0.0 -s-apob/apoa1-suhde 16804 0.0 -s-b12-tc2 45678 100.0 -s-b12-vit 20181 100.0 -s-b2miglo 118 100.0 -s-beta-1 2512 100.0 -s-beta-2 2528 100.0 -s-bil 466 100.0 -s-bopeaba 105 100.0 -s-bopeabg 104 100.0 -s-borabgv 140 100.0 -s-borabmv 215 100.0 -s-borrabg 351 100.0 -s-borrabm 663 100.0 -s-c-pep-a 195 100.0 -s-c1inh 390 100.0 -s-c3 273 100.0 -s-c4 261 100.0 -s-ca(7.4) 16088 100.0 -s-ca(akt) 11963 100.0 -s-ca++/7.40 5861 0.0 -s-ca-i7.4 1160 100.0 -s-ca-ion 24947 100.0 -s-ca-iona 11860 100.0 -s-ca12-5 291 100.0 -s-ca19-9 321 100.0 -s-ccpab 7235 87.07004239533651 -s-cdt 12144 100.0 -s-cea 2187 100.0 -s-chpnabg 384 100.0 -s-chpnabm 1348 88.46 -s-clahere 118 100.0 -s-clteab 202 100.0 -s-cmvabg 159 100.0 -s-cmvabm 150 100.0 -s-cmvavi 722 0.0 -s-codiab 165 100.0 -s-crp 592 100.0 -s-crp-o 1730 100.0 -s-d-1,25 514 0.0 -s-d-25 15247 100.0 -s-dgpabg 316 0.0 -s-dheas 265 100.0 -s-diabetesresistenssi 265 0.0 -s-digoks 3544 98.53846501128669 -s-dmklots 1763 89.65036921151437 -s-dnaab 605 100.0 -s-dnanab 526 77.26661596958175 -s-dnanab. 1881 100.0 -s-dpteroe 228 100.0 -s-e2 521 100.0 -s-ebvabg 291 100.0 -s-enaab 1784 100.0 -s-epo 924 77.30874458874459 -s-etoh 701 94.19 -s-ferrit 606 100.0 -s-fsh 6089 56.431021514205945 -s-gadab 972 98.8196639784946 -s-gamma 2599 100.0 -s-gliadie 106 0.0 -s-gt 211 99.88 -s-haptog 994 100.0 -s-hbsab 889 74.14331090174966 -s-hcg 575 65.87422608695653 -s-hcg-b-v 1852 100.0 -s-hcgbv 643 100.0 -s-hcgbv/d 4859 100.0 -s-healthindex(nhi) 265 0.0 -s-hepyaba 485 100.0 -s-hepyabg 1175 95.6719829787234 -s-hevohie 169 100.0 -s-hivab 186 0.0 -s-hs-crp 107 100.0 -s-iga 2318 100.0 -s-ige 1378 99.99547169811322 -s-igf1 101 0.0 -s-igf1sds 704 100.0 -s-igg 1486 100.0 -s-igg-sum 1410 100.0 -s-igg1 1897 100.0 -s-igg2 1893 100.0 -s-igg3 1853 100.0 -s-igg4 2367 100.0 -s-iglck-v 7808 100.0 -s-iglcl-v 7599 100.0 -s-igm 811 100.0 -s-immunoglobuliini,kevyetketjut,vapaat,kappa-lambda-suhde 2512 0.0 -s-infli 991 100.0 -s-infliks 137 100.0 -s-k 1963 100.0 -s-k/l-ex 163 0.0 -s-k/l-s-v 37594 100.0 -s-kalsium,ionisoitunut 297 100.0 -s-kalsium,ionisoitunut,aktuaali 202 100.0 -s-kalsium,ionisoitunutph7.4korjattu 208 0.0 -s-kap-ex 166 0.0 -s-karba 355 100.0 -s-kerulo 197 100.0 -s-ketiap 150 0.0 -s-kissae 112 0.0 -s-kisshie 265 100.0 -s-klotsa 4148 96.54409799554566 -s-koirae 115 0.0 -s-koirhie 266 100.0 -s-koivue 437 0.0 -s-kol-hdl 1972 100.0 -s-kol-ldl 1796 100.0 -s-kolesterolitasapaino 265 0.0 -s-korsol 1484 100.0 -s-kysc 752 100.0 -s-lam-ex 168 0.0 -s-lamotri 111 100.0 -s-lh 670 72.24720895522388 -s-li 4574 100.0 -s-lzm 987 100.0 -s-mg 373 100.0 -s-mg-ion 161 100.0 -s-mkomp-1 4740 100.0 -s-mkomp-2 1456 100.0 -s-mkomp-3 1434 100.0 -s-mkomp-4 1286 100.0 -s-monityydyttymättömienrasvahappojensuhdekerta 254 0.0 -s-mpoab 105 65.9 -s-mpoabg 1044 98.78 -s-mtx 124 100.0 -s-mypnabg 2836 99.91000000000001 -s-mypnabm 2032 0.0 -s-norklot 2537 100.0 -s-norklots 154 0.0 -s-normet 114 99.87 -s-ohkarba 268 100.0 -s-olants 301 100.0 -s-om5glie 181 0.0 -s-omega-6-rasvahappojensuhdenomega-3-rasvahappo 258 0.0 -s-osmol 727 100.0 -s-papp-a 274 0.0 -s-pappa 7766 100.0 -s-pct 117 100.0 -s-ph 395899 0.0 -s-ph(akt) 15874 100.0 -s-piiinp 113 98.49 -s-pr3ab 1796 76.40000000000002 -s-prealb 3043 85.0436345711469 -s-prl 2923 98.6285733835101 -s-prostataspesifinenantigeeni 165 100.0 -s-prot 5018 100.0 -s-psa 2720 100.0 -s-psa-suh 543 99.51591160220994 -s-psa-t 106 100.0 -s-psa-v 107 100.0 -s-psa-v/t 525 100.0 -s-pujoe 344 100.0 -s-puumabm 352 0.0 -s-pölyer 688 0.0 -s-p�lyer 220 0.0 -s-rasvahappotasapaino 265 0.0 -s-rf 2992 88.75204545454545 -s-risper 104 0.0 -s-rnpab 806 100.0 -s-ruokaer 144 0.0 -s-sappih 946 100.0 -s-scl70ab 353 100.0 -s-sentab 134 100.0 -s-shbg 1008 100.0 -s-smab 507 100.0 -s-ssaab 236 100.0 -s-ssbab 230 100.0 -s-sydämenikä 265 0.0 -s-sydäntautiriskinpisteytys 265 0.0 -s-t3-v 1034 100.0 -s-t4-v 9377 100.0 -s-t4-vdi 124 100.0 -s-testo 6705 99.98681431767339 -s-testovl 237 100.0 -s-tfr 1918 100.0 -s-timotee 321 100.0 -s-toxoabg 333 100.0 -s-tpoab 2300 67.94864756446991 -s-trigly 1983 100.0 -s-trypt 107 100.0 -s-tsh 25833 91.66959238183719 -s-tsh-peg 177 100.0 -s-tshrab 3358 83.10698029891304 -s-ttgaba 13655 95.54335554741853 -s-tulehdus 265 0.0 -s-tygl 129 100.0 -s-tyypin2diabetesriskinpisteytys 265 0.0 -s-ucrp 210 100.0 -s-valpr 4190 100.0 -s-van 2314 100.0 -s-vedol 151 100.0 -s-verensokeri 265 0.0 -s-viseabg 114 0.0 -s-viseabm 130 0.0 -s-vlseabg 138 0.0 -s-vlseabm 284 0.0 -s-vzvabg 116 0.0 -s-vzvabm 105 0.0 -sao2 2020 0.0 -seeruminhappamuusaste 2429 0.0 -snabb-inr 6267 0.0 -suhteellinentiheys 139 0.0 -suhteellinentiheys(kval) 256 0.0 -sy-eryt 129 100.0 -sy-gran 116 100.0 -sy-leuk 3825 99.77037647058823 -sy-lymf 116 100.0 -sy-muutsol 116 100.0 -sy-solut 410 0.0 -synnytystenmäärä,p 5868 0.0 -testo/shbg 109 0.0 -tffesat 2720 100.0 -timotei 118 100.0 -tromboplastiiniaika,inr-tulostus,kapillaariverestä 111 0.0 -tromboplastiiniaika,inr-tulostus,plasmasta 1310 100.0 -u-a1miglo 1280 0.0 -u-alb 54229 100.0 -u-alb-mi 403 100.0 -u-alb-o 41403 100.0 -u-alb/kre,u-alb 148 0.0 -u-alb/kre,u-krea 241 0.0 -u-albkre 50990 100.0 -u-albkrea 4066 100.0 -u-albumiini-kreatiniini-suhde,osatutk. 208 0.0 -u-bact 3529 0.0 -u-bakt 788 0.0 -u-bakt-vi 125 0.0 -u-baktb 201 0.0 -u-baktvi 346 0.0 -u-epilevy 1298 100.0 -u-epipien 1465 100.0 -u-epit 17406 100.0 -u-epitel 1120 0.0 -u-eryt 156911 99.47324090454053 -u-eryt-o 40413 100.0 -u-eryt. 292 100.0 -u-gluk 241 0.0 -u-gluk-0 4154 0.0 -u-gluk-o 49917 100.0 -u-gran 175 0.0 -u-happamuusaste 5304 0.0 -u-hb-o 584 0.0 -u-huum-10,ominaispaino 113 0.0 -u-huum-10,ph 146 0.0 -u-huum-7,ominaispaino 257 0.0 -u-huum-7,ph 315 0.0 -u-hyalier 537 100.0 -u-k 143 100.0 -u-kemseu,op 224 0.0 -u-kemseu,ph 239 0.0 -u-kemseul 699 0.0 -u-kemseul,omin.p 3444 0.0 -u-kemseul,op 254 0.0 -u-kemseul,ph 8222 0.0 -u-kemseul,u-ph 1683 0.0 -u-kemseul,u-sg 162 0.0 -u-kemseul,u-suhti 1362 0.0 -u-kemvt,sg 189 0.0 -u-keto-de 153 0.0 -u-keto-o 49520 98.0415909370767 -u-krea 102262 97.82576153767351 -u-leuk 156199 99.78119826278059 -u-leuk-bv 1442 100.0 -u-leuk-o 38972 100.0 -u-leuk. 292 100.0 -u-leukb 201 0.0 -u-levyep 135440 100.0 -u-lier 155241 100.0 -u-lieriö 2104 100.0 -u-lieriöt 2067 100.0 -u-muulier 537 100.0 -u-na 572 100.0 -u-nitr 182 0.0 -u-nitr-o 48433 100.0 -u-omin.p- 358 0.0 -u-omin.p-pika 214 0.0 -u-ominaisp 300 0.0 -u-ominaispaino 5398 0.0 -u-ominp-h 12360 0.0 -u-osmest 6300 100.0 -u-osmoest 5188 87.05 -u-osmoie 191 0.0 -u-osmol 2342 100.0 -u-osmolaliteetti,estimoitu 119 100.0 -u-osmole 13102 100.0 -u-ph 613611 98.78 -u-ph-0 1707 0.0 -u-ph-huu 12605 0.0 -u-ph-hy 2439 0.0 -u-ph-o 48346 0.0 -u-ph-pika 647 0.0 -u-ph. 23976 0.0 -u-phstix 1275 0.0 -u-phv 275 0.0 -u-pienep 135145 100.0 -u-prot 2170 80.93954799390553 -u-prot-o 9755 0.0 -u-sakka,epit 311 0.0 -u-sakka,eryt 1160 0.0 -u-sakka,leuk 1002 0.0 -u-sakka,lier 302 0.0 -u-sakka,makrof 305 0.0 -u-sakka,muuta 267 0.0 -u-seulont,ph 423 0.0 -u-seulonta,ph 786 0.0 -u-sg 1159 0.0 -u-suht-hy 453 0.0 -u-suhteellinentiheys 17548 100.0 -u-suhteellinentiheys,osatutkimus 145 0.0 -u-suhteellinentiheysstix 564 0.0 -u-suhti 261295 92.57617934696285 -u-suhti-o 45940 0.0 -u-suhti. 23488 0.0 -u-suhtih 41902 100.0 -u-suhtih-o 133 0.0 -u-tutk-1 358 0.0 -u-tutk-1,ph 2454 0.0 -u-tutk-1-,ph 1640 0.0 -u-tutk-1-,sg 1332 0.0 -u-tutk-1-oma,ph 2466 0.0 -u-tutk-1-oma,sg 2058 0.0 -u-tutkimus1,seulonta,osavastaussg 165 0.0 -u-veri-o 2498 0.0 -ua-be 261 100.0 -ua-ph 118 0.0 -vb-ahco3vt 386 100.0 -vb-be 46078 100.0 -vb-be-vt 629 100.0 -vb-bepika 324 100.0 -vb-caionvt 420 100.0 -vb-emäsylimäärä 3475 100.0 -vb-happamuusaste 2150 0.0 -vb-hb-vt 222 0.0 -vb-hco3-st 1064 100.0 -vb-hco3-vt 159 0.0 -vb-he-tase,vb-be.b 123 0.0 -vb-he-tase,vb-pco2 152 0.0 -vb-k-vt 226 0.0 -vb-na-vt 227 0.0 -vb-o2sat 767 100.0 -vb-pco2 3339 100.0 -vb-pco2-vt 682 0.0 -vb-ph 174556 100.0 -vb-ph-vt 542 0.0 -vb-po2 3333 100.0 -verensokeri,tk:ntekemä 154 0.0 -vieri-crp 477 0.0 -virtsam. 247 0.0 -virtsansolujenhl7-siirtoon 262 0.0 -vp-gluk-0h 371 0.0 -vp-gluk-1h 131 0.0 -vp-gluk-2h 366 0.0 -vp-happamuusaste 2193 0.0 -vp-ph 5059 0.0 -zb-be 2350 0.0 -zb-emäsylimäärä 208 0.0 -zb-ph 4383 0.0 diff --git a/scripts/injection/data/summary_table.md b/scripts/injection/data/summary_table.md index 4c30f25..06622f2 100644 --- a/scripts/injection/data/summary_table.md +++ b/scripts/injection/data/summary_table.md @@ -1,9 +1,9 @@ -*Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements* +*Active threshold: 98% — min count: 1,000 — 542 TEST_NAMEs, 31,839,159 measurements* | Threshold | UNAMBIGUOUS test names | UNAMBIGUOUS measurements | AMBIGUOUS test names | AMBIGUOUS measurements | NO_DATA test names | NO_DATA measurements | | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| 95% | 434 (60.7%) | 26,508,342 (82.9%) | 79 (11.0%) | 4,345,264 (13.6%) | 202 (28.3%) | 1,108,898 (3.5%) | -| 98% \* | 413 (57.8%) | 24,979,594 (78.2%) | 100 (14.0%) | 5,874,012 (18.4%) | 202 (28.3%) | 1,108,898 (3.5%) | -| 99% | 392 (54.8%) | 22,954,996 (71.8%) | 121 (16.9%) | 7,898,610 (24.7%) | 202 (28.3%) | 1,108,898 (3.5%) | -| 100% | 275 (38.5%) | 12,745,902 (39.9%) | 238 (33.3%) | 18,107,704 (56.7%) | 202 (28.3%) | 1,108,898 (3.5%) | -| **TOTAL** | **715** | | | || | +| 95% | 342 (63.1%) | 26,444,780 (83.1%) | 60 (11.1%) | 4,332,188 (13.6%) | 140 (25.8%) | 1,062,191 (3.3%) | +| 98% \* | 326 (60.1%) | 24,919,426 (78.3%) | 76 (14.0%) | 5,857,542 (18.4%) | 140 (25.8%) | 1,062,191 (3.3%) | +| 99% | 309 (57.0%) | 22,898,275 (71.9%) | 93 (17.2%) | 7,878,693 (24.7%) | 140 (25.8%) | 1,062,191 (3.3%) | +| 100% | 220 (40.6%) | 12,707,871 (39.9%) | 182 (33.6%) | 18,069,097 (56.8%) | 140 (25.8%) | 1,062,191 (3.3%) | +| **TOTAL** | **542** | | | || | diff --git a/scripts/injection/data/test_names_exploration_scatter.png b/scripts/injection/data/test_names_exploration_scatter.png index 6f866423f6d6be813007113cac9156fe70ae3a45..8ebcd127083d6c86446cf3040cf84d4ad41f093f 100644 GIT binary patch literal 111788 zcmce;WmHw`_XdihqNEszq@pM#NT(oDf`ouHh;(;LDJV#*bc1vYNOyO)bW3i!OxM~@!%_!LLc`kJ*v#74K=Yohj-{1>nJF_pCp{D0J$-9yb1NSq_H<0fOda=DSXcy4XLtz+TTSlW}+6E#nwmkLJQg|9M=kldV^#z`LAF4->*kF&PEE) z|L>y{s4q-!|L=p3?n*aex!t?^-(R&4AGF&4?-4KYhiMDmW%!?`!Ak;tsb(+#pJ!@( z$JZ(U-vhec6KDG2d*}b0A6;Sf?8jecdc3MhZIl78^Af z2?j)W)U103vs*ufwI6jwao&{ZD_%;DWOJMd^x_kab=qplQoH@J=UD4-YrZCbzAe1IaZ8u`P#{Lc>`H>a6R4x^!LQdW~(`JA^MuNW%o{n#g(mGq)-Q*9Fy6SwH*KiKNh 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+261,7 @@ def print_summary(plot_name, threshold): print(f"\n * = active threshold ({threshold}%)\n") -def print_assignment_summary(udf, adf, no_data, plot_name): +def print_assignment_summary(udf, adf, no_data, plot_name, out_doc=None, out_tsv=None): """Fraction of TEST_NAMEs/measurements successfully assigned a unit.""" count_map = plot_name.set_index("TEST_NAME")["COUNT"].to_dict() omop_names = set(plot_name[plot_name["OMOP_CONCEPT_ID"].notna()]["TEST_NAME"]) @@ -311,18 +311,37 @@ def _build_row(name_filter=None): cw = nw + 2 + mw cols = ["UNAMBIGUOUS", "AMBIGUOUS", "NO_DATA", "TOTAL"] - print("\nAssignment summary (successfully assigned)\n") - print(f"{'':>{lw}}" + "".join(f" {c:^{cw}}" for c in cols)) - print(f"{'':>{lw}}" + "".join(f" {'names':>{nw}} {'meas':>{mw}}" for _ in cols)) + text_lines = [ + "\nAssignment summary (successfully assigned)\n", + f"{'':>{lw}}" + "".join(f" {c:^{cw}}" for c in cols), + f"{'':>{lw}}" + "".join(f" {'names':>{nw}} {'meas':>{mw}}" for _ in cols), + ] div = f"{'':>{lw}}" + "".join(f" {'-'*nw} {'-'*mw}" for _ in cols) - print(div) + text_lines.append(div) for label, cells in rows: - line = f"{label:<{lw}}" + "".join(f" {ns:>{nw}} {ms:>{mw}}" for ns, ms in cells) + text_lines.append(f"{label:<{lw}}" + "".join(f" {ns:>{nw}} {ms:>{mw}}" for ns, ms in cells)) + text_lines.append(div) + + for line in text_lines: print(line) - print(div) + + if out_doc: + Path(out_doc).write_text("```\n" + "\n".join(text_lines) + "\n```\n") + print(f"Wrote {out_doc}") + + if out_tsv: + tsv_rows = [] + for label, cells in rows: + row = {"subset": label} + for col, (ns, ms) in zip(cols, cells): + row[f"{col}_names"] = ns + row[f"{col}_meas"] = ms + tsv_rows.append(row) + pd.DataFrame(tsv_rows).to_csv(out_tsv, sep="\t", index=False) + print(f"Wrote {out_tsv}") -def dump_summary_md(plot_name, threshold, min_count, out="summary_table.md"): +def dump_summary_md(plot_name, threshold, min_count, out="summary_table.md", out_tsv=None): total = len(plot_name) total_n = int(plot_name["COUNT"].sum()) cats = ["UNAMBIGUOUS", "AMBIGUOUS", "NO_DATA"] @@ -338,21 +357,30 @@ def dump_summary_md(plot_name, threshold, min_count, out="summary_table.md"): lines.append(header) lines.append(sep) + tsv_rows = [] for t in _SUMMARY_THRESHOLDS: marker = " \\*" if t == threshold else "" row = f"| {t}%{marker} |" + tsv_row = {"threshold": f"{t}%"} for cat in cats: sub = plot_name[plot_name[f"CATEGORY_{t}"] == cat] n = len(sub) m = int(sub["COUNT"].sum()) row += f" {n:,} ({100*n/total:.1f}%) | {m:,} ({100*m/total_n:.1f}%) |" + tsv_row[f"{cat}_names"] = n + tsv_row[f"{cat}_meas"] = m lines.append(row) + tsv_rows.append(tsv_row) lines.append(f"| **TOTAL** | **{total:,}** | | " + "| |" * (len(cats) - 1)) Path(out).write_text("\n".join(lines) + "\n") print(f"Wrote {out}") + if out_tsv: + pd.DataFrame(tsv_rows).to_csv(out_tsv, sep="\t", index=False) + print(f"Wrote {out_tsv}") + # --------------------------------------------------------------------------- # Injection engine @@ -406,7 +434,7 @@ def _fmt_deciles(arr): return "[" + ",".join(f"{v:.4g}" for v in vals) + "]" -def _run_engine(c_vals, t_vals, name, dump_dir, prevalence=None, tag_override=None): +def _run_engine(c_vals, t_vals, name, dump_dir, plots_dir=None, prevalence=None, tag_override=None): """Run KS / T / MAD pipeline, save diagnostic plot, return (updates, ks, t, mad).""" ks_step = injection_engine._ks(c_vals, t_vals, ks_threshold=0.3, sig_level=0.05) t_step = injection_engine._t(c_vals, t_vals, sig_level=0.05) @@ -425,7 +453,7 @@ def _run_engine(c_vals, t_vals, name, dump_dir, prevalence=None, tag_override=No result = injection_engine.PipelineResult(outcome, decided_by, [ks_step, t_step, mad_step]) - injection_engine.plot_result(c_vals, t_vals, result, name, dump_dir, + injection_engine.plot_result(c_vals, t_vals, result, name, plots_dir or dump_dir, prevalence=prevalence, tag_override=tag_override) n_passed = sum(s.passed for s in [ks_step, t_step, mad_step]) @@ -445,7 +473,8 @@ def _run_engine(c_vals, t_vals, name, dump_dir, prevalence=None, tag_override=No return updates, ks_step, t_step, mad_step -def run_unambiguous(parquet, plot_name, details, dump_dir, test_mode=False): +def run_unambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, test_mode=False, + out="unambiguous_results.tsv"): os.makedirs(dump_dir, exist_ok=True) unambig = plot_name[plot_name["CATEGORY"] == "UNAMBIGUOUS"].sort_values("COUNT", ascending=False) @@ -498,7 +527,7 @@ def run_unambiguous(parquet, plot_name, details, dump_dir, test_mode=False): if len(c_vals) >= 2 and len(t_vals) >= 2: print("engine...", end=" ", flush=True) updates, ks, t, mad = _run_engine(c_vals, t_vals, name, dump_dir, - prevalence=prev) + plots_dir=plots_dir, prevalence=prev) row.update(updates) print( f"KS={'P' if ks.passed else 'F'}" @@ -526,9 +555,8 @@ def run_unambiguous(parquet, plot_name, details, dump_dir, test_mode=False): results = pd.DataFrame(rows, columns=cols) for col in ("TEST_NAME", "UNIT", "OUTCOME", "NOTES"): results[col] = results[col].str.replace(" ", "_", regex=False) - results.to_csv("unambiguous_results.tsv", sep="\t", index=False, - float_format="%.4g", na_rep="NA") - print(f"\nWrote unambiguous_results.tsv ({len(results)} rows)") + results.to_csv(out, sep="\t", index=False, float_format="%.4g", na_rep="NA") + print(f"\nWrote {out} ({len(results)} rows)") return results @@ -550,9 +578,9 @@ def _unit_tag(unit): return unit.replace("/", "_").replace(" ", "_").replace("%", "pct") -def run_ambiguous(parquet, plot_name, details, dump_dir, +def run_ambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, dip_threshold=0.05, min_target_n=30, test_mode=False, - split_threshold=0.15): + split_threshold=0.15, out="ambiguous_results.tsv"): os.makedirs(dump_dir, exist_ok=True) ambig = plot_name[plot_name["CATEGORY"] == "AMBIGUOUS"].sort_values("COUNT", ascending=False) @@ -617,7 +645,7 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, t_vals_u = unit_data[unit] upd, ks, t, mad = _run_engine( c_vals, t_vals_u, - f"{name} [all] [{unit}]", dump_dir, + f"{name} [all] [{unit}]", dump_dir, plots_dir=plots_dir, prevalence=f"{upct:.1f}%", tag_override=f"{tag}_all_{_unit_tag(unit)}", ) @@ -633,7 +661,7 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, # Bimodal check always runs — needed for split score even when pre-check passed bim = injection_engine.bimodal_check(c_vals, dip_threshold=dip_threshold) - injection_engine.plot_bimodal_check(bim, name, dump_dir) + injection_engine.plot_bimodal_check(bim, name, plots_dir or dump_dir) print(f" bimodal={bim.status} sep={bim.separator:.4g}" f" BC={bim.bc:.3f} dip_p={bim.dip_p:.3g}") @@ -666,7 +694,7 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, g_score=global_ranks[0][2] if global_ranks else np.nan, s_score=si.get("split_score", np.nan), improvement=si.get("improvement", 0.0), - out_path=os.path.join(dump_dir, f"split_eval_{tag}.png"), + out_path=os.path.join(plots_dir or dump_dir, f"split_eval_{tag}.png"), ) if any_precheck_pass and not prefer_split: @@ -723,7 +751,7 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, t_vals_u = unit_data[unit] upd, ks, t, mad = _run_engine( c_sub, t_vals_u, - f"{name} [{sub_name}] [{unit}]", dump_dir, + f"{name} [{sub_name}] [{unit}]", dump_dir, plots_dir=plots_dir, prevalence=f"{upct:.1f}%", tag_override=f"{tag}_{sub_name}_{_unit_tag(unit)}", ) @@ -762,16 +790,16 @@ def _outcome_rank(o): .sort_values(["_rank", "UNIT_PREVALENCE"], ascending=[True, False]) .groupby(["TEST_NAME", "SUB_DIST"])["UNIT"] .first() - .reset_index() - .rename(columns={"UNIT": "BEST_UNIT"})) - results = results.merge(best, on=["TEST_NAME", "SUB_DIST"], how="left") - results = results[results["UNIT"] == results["BEST_UNIT"]].drop(columns=["_rank"]) + .reset_index()) + results = results.merge(best.rename(columns={"UNIT": "_best_unit"}), + on=["TEST_NAME", "SUB_DIST"], how="left") + results = results[results["UNIT"] == results["_best_unit"]].drop(columns=["_rank", "_best_unit"]) col_order = [ "TEST_NAME", "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", "SCORE_GLOBAL", "SCORE_SPLIT", "SCORE_IMPROVEMENT", "SUB_DIST", - "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "BEST_UNIT", + "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "N_CANDIDATE", "N_TARGET", "CAND_DECILES", "TARG_DECILES", "KS_STAT", "KS_MLOGP", "KS_PASS", @@ -780,14 +808,13 @@ def _outcome_rank(o): "OUTCOME", "NOTES", ] results = results[col_order] - results.to_csv("ambiguous_results.tsv", sep="\t", index=False, - float_format="%.4g", na_rep="NA") + results.to_csv(out, sep="\t", index=False, float_format="%.4g", na_rep="NA") - _print_ambig_summary(results) + _print_ambig_summary(results, out) return results -def _print_ambig_summary(results): +def _print_ambig_summary(results, out="ambiguous_results.tsv"): n_tot = results["TEST_NAME"].nunique() tested = results[results["OUTCOME"] != "SKIP"] @@ -805,13 +832,13 @@ def _print_ambig_summary(results): print() w = 40 - print(f" {'TEST_NAME':<{w}} {'BIMODAL':<18} {'SUB':<5} {'BEST_UNIT':<14} OUTCOME") + print(f" {'TEST_NAME':<{w}} {'BIMODAL':<18} {'SUB':<5} {'UNIT':<14} OUTCOME") print(f" {'-'*w} {'-'*18} {'-'*5} {'-'*14} -------") for _, r in best_rows.iterrows(): print(f" {r['TEST_NAME']:<{w}} {r['BIMODAL_STATUS']:<18} {r['SUB_DIST']:<5}" - f" {r['BEST_UNIT']:<14} {r['OUTCOME']}") + f" {r['UNIT']:<14} {r['OUTCOME']}") - print(f"\nWrote ambiguous_results.tsv ({len(results)} rows, {n_tot} TEST_NAMEs)") + print(f"\nWrote {out} ({len(results)} rows, {n_tot} TEST_NAMEs)") # --------------------------------------------------------------------------- @@ -821,7 +848,7 @@ def _print_ambig_summary(results): _UNIFIED_COLS = [ "TYPE", "TEST_NAME", "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", - "SUB_DIST", "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "BEST_UNIT", + "SUB_DIST", "CUTOFF", "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "N_CANDIDATE", "N_TARGET", "CAND_DECILES", "TARG_DECILES", "KS_STAT", "KS_MLOGP", "KS_PASS", @@ -831,14 +858,13 @@ def _print_ambig_summary(results): ] -def _write_unified(udf, adf): +def _write_unified(udf, adf, out="injection_results.tsv"): parts = [] if udf is not None and len(udf): u = udf.copy() u["TYPE"] = "unambiguous" u["SUB_DIST"] = "all" - u["BEST_UNIT"] = u["UNIT"] # Derive UNIT_PREVALENCE from the dominant unit in PREVALENCE_DICT def _top_pct(row): pairs = parse_top_units(row["PREVALENCE_DICT"], n=10) @@ -857,11 +883,15 @@ def _top_pct(row): if not parts: return - combined = (pd.concat(parts, ignore_index=True) - .reindex(columns=_UNIFIED_COLS)) - combined.to_csv("injection_results.tsv", sep="\t", index=False, - float_format="%.4g", na_rep="NA") - print(f"\nWrote injection_results.tsv ({len(combined)} rows)") + combined = pd.concat(parts, ignore_index=True) + combined["CUTOFF"] = np.where( + combined["SUB_DIST"] == "low", + combined["BIMODAL_SEP"], + np.inf, + ) + combined = combined.reindex(columns=_UNIFIED_COLS) + combined.to_csv(out, sep="\t", index=False, float_format="%.4g", na_rep="NA") + print(f"\nWrote {out} ({len(combined)} rows)") # --------------------------------------------------------------------------- @@ -919,50 +949,68 @@ def build_parser(): help="Hartigan dip test p-value threshold for bimodality detection") p.add_argument("--split-threshold", type=float, default=0.15, metavar="FLOAT", help="Minimum relative KS improvement to prefer a split over the global fit") - p.add_argument("--omop-unit-table", default="omop_unit_table.tsv", metavar="PATH", - help="Cache path for the OMOP unit table (built automatically if missing)") + p.add_argument("--omop-unit-table", default=None, metavar="PATH", + help="Override path for the OMOP unit table cache (default: data/omop_unit_table.tsv under --out-dir)") p.add_argument("--min-target-n", type=int, default=30, metavar="INT", help="Minimum reference records a unit must have to be tested (ambiguous pass)") p.add_argument("--test", action="store_true", help="Limit to a small sample: one per COUNT decile (unambiguous) " "and top 10 by volume (ambiguous)") + p.add_argument("--out-dir", default=".", metavar="PATH", + help="Root output directory; doc/, plots/, data/ subdirs are created here") return p def main(): args = build_parser().parse_args() - counts = query_counts(args.parquet) + data_dir = Path(args.out_dir) + doc_dir = data_dir / "doc" + plots_dir = data_dir / "plots" + for d in (data_dir, doc_dir, plots_dir): + d.mkdir(parents=True, exist_ok=True) + + counts = query_counts(args.parquet, out=str(data_dir / "test_name_counts.tsv")) counts = counts[counts["COUNT"] > args.min_count].reset_index(drop=True) - details = query_details(args.parquet) + details = query_details(args.parquet, + counts_file=str(data_dir / "test_name_counts.tsv"), + out=str(data_dir / "test_name_details.tsv")) plot_name = build_plot_table(counts, details) plot_name = _add_category(plot_name, args.prevalence_threshold, args.min_target_n) - plot_name.to_csv("plot_name_level.tsv", sep="\t", index=False) - print(f"Built plot_name_level.tsv ({len(plot_name)} rows, " + plot_name.to_csv(data_dir / "plot_name_level.tsv", sep="\t", index=False) + print(f"Built {data_dir}/plot_name_level.tsv ({len(plot_name)} rows, " f"min_count={args.min_count}, threshold={args.prevalence_threshold}%)") - omop_tbl = load_omop_unit_table(args.parquet, args.omop_unit_table) + omop_tbl = load_omop_unit_table(args.parquet, + out=args.omop_unit_table or str(data_dir / "omop_unit_table.tsv")) omop_cat = omop_tbl.set_index("OMOP_CONCEPT_ID")["CATEGORY"] - make_scatter_plot(plot_name) + make_scatter_plot(plot_name, output=str(plots_dir / "test_names_exploration_scatter.png")) print_summary(plot_name, args.prevalence_threshold) - dump_summary_md(plot_name, args.prevalence_threshold, args.min_count) + dump_summary_md(plot_name, args.prevalence_threshold, args.min_count, + out=str(doc_dir / "summary_table.md"), + out_tsv=str(data_dir / "summary_table.tsv")) omop_sub = plot_name[plot_name["OMOP_CONCEPT_ID"].notna()].copy() print(f"\n── OMOP-mapped subset ({len(omop_sub):,} TEST_NAMEs) ──") print_summary(omop_sub, args.prevalence_threshold) dump_summary_md(omop_sub, args.prevalence_threshold, args.min_count, - out="omop_summary_table.md") + out=str(doc_dir / "omop_summary_table.md"), + out_tsv=str(data_dir / "omop_summary_table.tsv")) if args.inject: udf = run_unambiguous(args.parquet, plot_name, details, args.dump_dir, - test_mode=args.test) + plots_dir=str(plots_dir), + test_mode=args.test, + out=str(data_dir / "unambiguous_results.tsv")) adf = run_ambiguous(args.parquet, plot_name, details, args.dump_dir, + plots_dir=str(plots_dir), dip_threshold=args.dip_threshold, min_target_n=args.min_target_n, test_mode=args.test, - split_threshold=args.split_threshold) - _write_unified(udf, adf) + split_threshold=args.split_threshold, + out=str(data_dir / "ambiguous_results.tsv")) + _write_unified(udf, adf, out=str(data_dir / "injection_results.tsv")) no_data = plot_name[plot_name["CATEGORY"] == "NO_DATA"][["TEST_NAME", "COUNT", "OMOP_CONCEPT_ID"]].copy() @@ -979,9 +1027,9 @@ def main(): no_data["PREVALENCE"] = (no_data["COUNT"] / no_data["OMOP_TOTAL_N"]).round(4) no_data = no_data.drop(columns=["CANONICAL_UNIT"]) - no_data.to_csv("no_data_results.tsv", sep="\t", index=False, na_rep="NA") + no_data.to_csv(data_dir / "no_data_results.tsv", sep="\t", index=False, na_rep="NA") n_injected = no_data["UNIT"].notna().sum() - print(f"Wrote no_data_results.tsv ({len(no_data)} rows, {n_injected} units injected via OMOP)") + print(f"Wrote {data_dir}/no_data_results.tsv ({len(no_data)} rows, {n_injected} units injected via OMOP)") has_omop = no_data["OMOP_CONCEPT_ID"].notna() has_unit = no_data["UNIT"].notna() @@ -1006,7 +1054,9 @@ def main(): if not args.test: _check_coverage(plot_name, udf, adf, no_data) - print_assignment_summary(udf, adf, no_data, plot_name) + print_assignment_summary(udf, adf, no_data, plot_name, + out_doc=str(doc_dir / "assignment_summary.md"), + out_tsv=str(data_dir / "assignment_summary.tsv")) if __name__ == "__main__": diff --git a/scripts/injection/html/doc.html b/scripts/injection/html/doc.html new file mode 100644 index 0000000..dae5028 --- /dev/null +++ b/scripts/injection/html/doc.html @@ -0,0 +1,268 @@ + + + + + + Documentation — unit injection + + + + +

+
+

Unit injection exploration

+

The goal is to identify lab measurements that have a numeric value but are missing a unit, and to characterise the unit distribution of the matching records that do have a unit — so that a unit can be confidently assigned to the missing ones.

+

Summary

+

scatter

+

Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ThresholdUNAMBIGUOUS test namesUNAMBIGUOUS measurementsAMBIGUOUS test namesAMBIGUOUS measurementsNO_DATA test namesNO_DATA measurements
95%434 (60.7%)26,508,342 (82.9%)79 (11.0%)4,345,264 (13.6%)202 (28.3%)1,108,898 (3.5%)
98% *413 (57.8%)24,979,594 (78.2%)100 (14.0%)5,874,012 (18.4%)202 (28.3%)1,108,898 (3.5%)
99%392 (54.8%)22,954,996 (71.8%)121 (16.9%)7,898,610 (24.7%)202 (28.3%)1,108,898 (3.5%)
100%275 (38.5%)12,745,902 (39.9%)238 (33.3%)18,107,704 (56.7%)202 (28.3%)1,108,898 (3.5%)
TOTAL715
+
+

Usage

+
python3 explore_test_name.py <parquet_file> [options]
+
+
    +
  • <parquet_file>: path to the input parquet file (INJECT.parquet)
    • +
  • --min-count INT: minimum no-unit records a TEST_NAME must have to be included in plots and injection (default: 1000)
    • +
  • --prevalence-threshold FLOAT: min dominant-unit prevalence (%) to classify a TEST_NAME as UNAMBIGUOUS (default: 98)
    • +
  • --min-target-n INT: minimum reference records a unit must have; tests below this are classified NO_DATA (default: 30)
    • +
  • --dump-dir PATH: cache directory for per-test .npy arrays (default: /mnt/disks/data/kanta/inject/tmp/)
    • +
  • --omop-unit-table PATH: cache path for the OMOP unit table; built automatically on first run (default: omop_unit_table.tsv)
    • +
  • --inject: run the injection engine (unambiguous + ambiguous + no_data passes)
    • +
  • --dip-threshold FLOAT: Hartigan dip test p-value threshold for bimodality (default: 0.05)
    • +
  • --split-threshold FLOAT: minimum relative KS improvement required to prefer a score-based split over the global fit (default: 0.15)
    • +
  • --test: small-sample mode — one test per COUNT decile (unambiguous) and top 10 by volume (ambiguous)
    • +
+

Caching behaviour

+

test_name_counts.tsv and test_name_details.tsv are cached after the first ClickHouse query and reused on subsequent runs — delete them to force a re-query. They are always queried with a fixed baseline of COUNT > 50; --min-count is applied as a post-load filter in Python, so changing it never requires a re-query.

+

plot_name_level.tsv, test_names_exploration_scatter.png, and summary_table.md are always recomputed from the filtered data.

+

Per-test .npy arrays are always cached in --dump-dir and reused across runs.

+
+

Step 1 — Injection targets (test_name_counts.tsv)

+

Counts records where at least one value is present (MEASUREMENT_VALUE_EXTRACTED IS NOT NULL OR MEASUREMENT_VALUE_SOURCE IS NOT NULL) but the unit prefix is absent (MEASUREMENT_UNIT_PRE_FIX IS NULL), grouped by TEST_NAME. Cached with COUNT > 50; further filtered to --min-count at runtime.

+

Columns: TEST_NAME, COUNT

+
+

Step 2 — Reference population (test_name_details.tsv)

+

For every TEST_NAME in Step 1, describes the unit distribution of the records that already have both a value and a unit (MEASUREMENT_VALUE_SOURCE IS NOT NULL AND MEASUREMENT_UNIT_PRE_FIX IS NOT NULL).

+

Columns: TEST_NAME, COUNT, UNIT, PREVALENCE_DICT

+
    +
  • COUNT: total reference records for this TEST_NAME (across all units)
    • +
  • UNIT: the most frequent unit
    • +
  • PREVALENCE_DICT: top-3 units and their percentage share, e.g. {mmol/l:98.5,umol/l:1.5}
    • +
+
+

Step 3 — Plotting table, scatter plot, and classification

+

Steps 1 and 2 are merged in Python to produce plot_name_level.tsv, a scatter plot, and a summary table. Each TEST_NAME is assigned a CATEGORY that drives which injection pass it enters.

+

plot_name_level.tsv

+

One row per TEST_NAME. Columns include COUNT, N_WITH_UNIT, top_prevalence, CATEGORY, and exploratory CATEGORY_{95,98,99,100} columns.

+
    +
  • COUNT: no-unit record count
    • +
  • N_WITH_UNIT: total reference records with any unit
    • +
  • top_prevalence: prevalence (%) of the dominant unit; 0 if no reference records exist
    • +
+

Classification (CATEGORY)

+ + + + + + + + + + + + + + + + + + + + + +
CategoryCondition
NO_DATAN_WITH_UNIT < --min-target-n OR top_prevalence == 0
UNAMBIGUOUStop_prevalence >= --prevalence-threshold
AMBIGUOUS0 < top_prevalence < --prevalence-threshold
+

The injection engine only runs tests classified as UNAMBIGUOUS or AMBIGUOUS. NO_DATA tests are written directly to no_data_results.tsv.

+

OMOP unit table (omop_unit_table.tsv)

+

Built once from the OMOP LAB mapping files and enriched with per-concept record counts queried from the parquet file. Cached at --omop-unit-table. Each OMOP concept is assigned a CATEGORY:

+
    +
  • SINGLE — only one unit observed in the OMOP data
    • +
  • EQUIVALENT — multiple units present but all mutually convertible; a CANONICAL_UNIT is available
    • +
  • MULTIPLE — multiple non-equivalent units; no single canonical unit can be assigned
    • +
+

This table is used to enrich no_data_results.tsv with canonical units.

+

Two summary tables are written: +- summary_table.md — all TEST_NAMEs +- omop_summary_table.md — OMOP-mapped subset only

+
+

Step 4 — Injection engine (--inject)

+

With --inject, three passes are run and a coverage check validates that every TEST_NAME in plot_name_level.tsv appears in exactly one output file.

+

Unambiguous pass → unambiguous_results.tsv

+

TEST_NAMEs with CATEGORY == UNAMBIGUOUS. The candidate distribution (no-unit records) is compared against the reference distribution for the dominant unit.

+

One row per TEST_NAME. Columns: TEST_NAME, UNIT, PREVALENCE_DICT, N_CANDIDATE, N_TARGET, CAND_DECILES, TARG_DECILES, KS_STAT, KS_MLOGP, KS_PASS, T_STAT, T_MLOGP, T_PASS, MAD_DIST, MAD_THRESHOLD, MAD_PASS, OUTCOME, NOTES.

+

Ambiguous pass → ambiguous_results.tsv

+

TEST_NAMEs with CATEGORY == AMBIGUOUS. Only units with prevalence > 1% and at least --min-target-n reference records are considered.

+

Pipeline per TEST_NAME:

+
    +
  1. Pre-check: run the full (unsplit) candidate distribution against each qualifying unit.
    2. +
  2. Bimodality check (always runs, even if pre-check passed): test the candidate distribution for bimodality and compute split_improvement — the relative KS gain when the candidate is split at the GMM separator vs. treated globally.
    3. +
  3. Split decision: a split is preferred if split_improvement > --split-threshold AND the two halves favour different best units (same_best_unit == False). If splitting is not preferred and any pre-check passed, the global result is kept.
    4. +
  4. Sub-distribution engine (only if splitting is preferred): the candidate is split into low/high halves at the GMM separator and the engine is re-run on each half × unit.
    5. +
+

One row per (TEST_NAME, SUB_DIST) — the best unit only. Best unit selection: PASS > FAIL > SKIP, then highest UNIT_PREVALENCE as tiebreaker — we prefer the dominant clinical unit when two units both pass.

+

A split_eval_{tag}.png decision-tree figure is saved to --dump-dir for every TEST_NAME.

+

Columns: TEST_NAME, BIMODAL_STATUS, BIMODAL_SEP, BIMODAL_BC, BIMODAL_DIP_P, SCORE_GLOBAL, SCORE_SPLIT, SCORE_IMPROVEMENT, SUB_DIST, UNIT, UNIT_PREVALENCE, PREVALENCE_DICT, BEST_UNIT, N_CANDIDATE, N_TARGET, CAND_DECILES, TARG_DECILES, KS_STAT, KS_MLOGP, KS_PASS, T_STAT, T_MLOGP, T_PASS, MAD_DIST, MAD_THRESHOLD, MAD_PASS, OUTCOME, NOTES.

+
    +
  • SCORE_GLOBAL: best KS statistic achieved across all units on the full candidate distribution (lower = better fit)
    • +
  • SCORE_SPLIT: mean of the best KS statistics for the low and high sub-distributions
    • +
  • SCORE_IMPROVEMENT: (SCORE_GLOBAL − SCORE_SPLIT) / SCORE_GLOBAL — relative improvement from splitting
    • +
+

No-data pass → no_data_results.tsv

+

TEST_NAMEs with CATEGORY == NO_DATA. No engine is run. The result is enriched with OMOP unit table information; a canonical unit is injected where the OMOP concept has category SINGLE or EQUIVALENT.

+

Columns: TEST_NAME, COUNT, OMOP_CONCEPT_ID, OMOP_QUANTITY, CATEGORY, N_UNITS, UNITS, CONVERSIONS, OMOP_TOTAL_N, UNIT, PREVALENCE.

+
    +
  • CATEGORY: OMOP unit category (SINGLE, EQUIVALENT, MULTIPLE, or NA)
    • +
  • UNIT: canonical unit from the OMOP table if available, otherwise blank
    • +
  • PREVALENCE: fraction of OMOP concept records that are no-unit (COUNT / OMOP_TOTAL_N)
    • +
+

After writing, a breakdown is printed: +- no OMOP — TEST_NAMEs with no concept ID +- OMOP, unit injected — concept has SINGLE/EQUIVALENT category +- OMOP, no unit — concept mapped but MULTIPLE or unknown unit

+

Unified output → injection_results.tsv

+

Merge of the unambiguous and ambiguous results with a TYPE column (unambiguous / ambiguous). Does not include no_data rows.

+

Coverage check

+

After all three passes, a checksum validates that the union of the three output files equals the full set of TEST_NAMEs in plot_name_level.tsv, with no overlaps and no missing entries. Skipped in --test mode.

+

Assignment summary

+

Printed at the end of --inject. Shows, for each category (UNAMBIGUOUS, AMBIGUOUS, NO_DATA) and in total, how many TEST_NAMEs and measurements received a unit (PASS rows), broken out for all TEST_NAMEs and the OMOP-mapped subset.

+
+

Injection engine pipeline

+

Each comparison runs three tests in order. All three always run; the first to decide the outcome wins.

+
    +
  1. KS test — two-sample Kolmogorov–Smirnov. PASS = stat < 0.3 AND p < 0.05. Uses a fast binned approximation (100k bins, Hodges-corrected asymptotic p) above 500k samples; exact scipy otherwise.
    2. +
  2. Welch t-test — fallback if KS fails. PASS = p ≥ 0.05 (means not significantly different).
    3. +
  3. MAD test — last resort. PASS = |median(candidate) − median(target)| ≤ 3 × MAD(target).
    4. +
+

Decision rule: KS PASS → PASS. KS FAIL, T PASS → PASS. Both fail → MAD decides. NOTES records the deciding test and how many of the three passed, e.g. PASS_at_T_(2/3).

+

P-values are stored as −log10(p) throughout (KS_MLOGP, T_MLOGP).

+

Each comparison produces a 3-panel diagnostic plot saved to --dump-dir: +- Panel 1: ECDFs + KS distance marked in red + KS annotation +- Panel 2: KDE (linear scale) + dotted mean lines + t-test annotation +- Panel 3: KDE (log scale) + MAD band (green = PASS, salmon = FAIL) + median lines + distance arrow

+

KDE/ECDF rendering downsamples to 50k points. All statistics use the full arrays.

+
+

Bimodal check

+

Before the ambiguous sub-distribution pass, the candidate distribution is tested for bimodality using two statistics:

+

The candidate array is subsampled to 50,000 points before the dip test and GMM fitting (the dip test is unreliable above ~72k samples and GMM fitting is also faster at this size). All statistics and the separator are computed on this subsample.

+

Hartigan's dip test (primary gate): p-value < --dip-threshold (default 0.05) declares non-unimodal.

+

Bimodality coefficient (BC): (skew² + 1) / (excess_kurtosis + 3(n−1)²/((n−2)(n−3))). Values above ~0.555 suggest bimodality.

+

Both are computed in the space (linear or log) where a 2-component GMM achieves lower BIC. The GMM separator is used to split the candidate distribution.

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
dip pBCStatus
≥ threshold—unimodal
< threshold≥ 0.555bimodal — split into low/high
< threshold< 0.555bimodal_cautious — split, modes overlap
——skipped — pre-check passed and split not preferred
+

split_by_score is a separate label (not dip-test-derived) assigned when the split is triggered by score improvement (SCORE_IMPROVEMENT > --split-threshold and the two halves favour different units), regardless of dip test outcome.

+

A diagnostic plot (bimodal_{tag}.png) is saved to --dump-dir.

+ + diff --git a/scripts/injection/html/index.html b/scripts/injection/html/index.html new file mode 100644 index 0000000..f6671f1 --- /dev/null +++ b/scripts/injection/html/index.html @@ -0,0 +1,203 @@ + + + + + + Unit injection results + + + + + + +
+

Unit injection results

+ +
Scatter: TEST_NAMEs by count and prevalence
+ +

Category summary

Active threshold: 98% — min count: 1,000 — 542 TEST_NAMEs, 31,839,159 measurements

+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
ThresholdUNAMBIGUOUS test namesUNAMBIGUOUS measurementsAMBIGUOUS test namesAMBIGUOUS measurementsNO_DATA test namesNO_DATA measurements
95%342 (63.1%)26,444,780 (83.1%)60 (11.1%)4,332,188 (13.6%)140 (25.8%)1,062,191 (3.3%)
98% *326 (60.1%)24,919,426 (78.3%)76 (14.0%)5,857,542 (18.4%)140 (25.8%)1,062,191 (3.3%)
99%309 (57.0%)22,898,275 (71.9%)93 (17.2%)7,878,693 (24.7%)140 (25.8%)1,062,191 (3.3%)
100%220 (40.6%)12,707,871 (39.9%)182 (33.6%)18,069,097 (56.8%)140 (25.8%)1,062,191 (3.3%)
TOTAL542

Assignment summary


+Assignment summary (successfully assigned)
+
+                      UNAMBIGUOUS                   AMBIGUOUS                     NO_DATA                       TOTAL           
+               names                 meas   names                 meas   names                 meas   names                 meas
+              ------  -------------------  ------  -------------------  ------  -------------------  ------  -------------------
+All            10/10  2,874,565/2,874,565   10/10  5,300,918/5,300,918  26/140    284,033/1,062,191  46/160  8,459,516/9,237,674
+OMOP-mapped    10/10  2,874,565/2,874,565   10/10  5,300,918/5,300,918   26/61      284,033/797,892   46/81  8,459,516/8,973,375
+              ------  -------------------  ------  -------------------  ------  -------------------  ------  -------------------
+
+ +

Per-column search: text columns support regex (e.g. ^PASS$, + mmol). Numeric columns support comparisons: <3, + >=20, !=0. The global box top-right searches all columns with regex.

+ +
+ + + + + + +
Test nameTypeOutcomeUnitUnit prev (%)N candN targetKS statKS −log10pKS passT statT −log10pT passMAD distMAD thrMAD passNotesBEST_UNIT
+
+ + + + + + + diff --git a/scripts/injection/injection_engine.py b/scripts/injection/injection_engine.py index f36847d..ab7c65a 100644 --- a/scripts/injection/injection_engine.py +++ b/scripts/injection/injection_engine.py @@ -167,7 +167,8 @@ class BimodalResult: bc: float dip_p: float lognormal: bool # which space had lower BIC - fit: dict # raw GMM output (empty dict if unavailable) + fit: dict # raw GMM output for the winning fit (empty dict if unavailable) + fit_alt: dict # raw GMM output for the losing fit (empty dict if unavailable) def __str__(self): return (f"[BIMODAL] {self.status} sep={self.separator:.4g}" @@ -256,7 +257,7 @@ def bimodal_check(arr, dip_threshold=0.05, bc_threshold=0.555): fits = [f for f in (fit_norm, fit_log) if f is not None] if not fits: - return BimodalResult("unimodal", np.nan, np.nan, np.nan, False, {}) + return BimodalResult("unimodal", np.nan, np.nan, np.nan, False, {}, {}) best = min(fits, key=lambda f: f["bic"]) @@ -279,13 +280,53 @@ def bimodal_check(arr, dip_threshold=0.05, bc_threshold=0.555): else: status = "bimodal" if bc >= bc_threshold else "unimodal" - return BimodalResult(status, sep, bc, dip_p, best["lognormal"], best) + alt = next((f for f in fits if f is not best), {}) + return BimodalResult(status, sep, bc, dip_p, best["lognormal"], best, alt) + + +def _plot_bimodal_panel(ax, fit, is_winner, result_separator): + """Draw one GMM panel (linear or log space) onto ax.""" + if not fit: + ax.text(0.5, 0.5, "fit unavailable", ha="center", va="center", + transform=ax.transAxes, color="grey") + return + + x_fit = fit["x_fit"] + x_orig = fit["x_orig"] + means = fit["means_native"] + sigmas = fit["sigmas_native"] + weights = fit["weights"] + lognormal = fit["lognormal"] + + lo, hi = np.percentile(x_fit, [0.5, 99.5]) + ax.hist(x_fit, bins=60, density=True, alpha=0.45, color="steelblue", range=(lo, hi)) + xf = np.linspace(lo, hi, 400) + for m, s, w in zip(means, sigmas, weights): + ax.plot(xf, w * stats.norm.pdf(xf, m, s), alpha=0.8) + if not np.isnan(fit["sep_native"]): + ax.axvline(fit["sep_native"], color="red", ls="--", + label=f"sep={fit['sep_native']:.3g}") + + space = "log" if lognormal else "linear" + ax.set_xlabel("log(value)" if lognormal else "value") + title = f"{space} space BIC={fit['bic']:.1f}" + ax.set_title(title, fontweight="bold" if is_winner else "normal", + color="black" if is_winner else "grey") + ax.legend(fontsize=8) + + if is_winner: + ax.spines[["top", "right", "bottom", "left"]].set_linewidth(2.5) + for spine in ax.spines.values(): + spine.set_edgecolor("#2ca02c") + ax.text(0.98, 0.97, "✓ winner", ha="right", va="top", + transform=ax.transAxes, fontsize=9, color="#2ca02c", fontweight="bold") def plot_bimodal_check(result, name, dump_dir): """ Save bimodal diagnostic to dump_dir/bimodal_{tag}.png. - Uses the subsampled arrays stored in result.fit; no-op only if GMM failed. + Always shows both linear and log panels; winner is highlighted in green. + No-op if GMM failed entirely. """ if not result.fit: return @@ -294,49 +335,25 @@ def plot_bimodal_check(result, name, dump_dir): if os.path.exists(out_path): return - fit = result.fit - means_n, sigmas_n, weights_n = fit["means_native"], fit["sigmas_native"], fit["weights"] - x_orig = fit["x_orig"] # positive values in original space - x_fit = fit["x_fit"] # values in fitted space (log or linear) + fit_win = result.fit + fit_alt = result.fit_alt + + # Assign panels: left=linear, right=log + fit_linear = fit_win if not fit_win["lognormal"] else fit_alt + fit_log = fit_win if fit_win["lognormal"] else fit_alt fig, axes = plt.subplots(1, 2, figsize=(12, 4)) fig.suptitle( f"{name} — {result.status} sep={result.separator:.4g}" f" BC={result.bc:.3f} dip_p={result.dip_p:.3g}" - f" space={'log' if result.lognormal else 'linear'}", + f" winner={'log' if result.lognormal else 'linear'}", fontsize=10, fontweight="bold", ) - # Panel 1: original space - ax = axes[0] - lo, hi = np.percentile(x_orig, [0.5, 99.5]) - ax.hist(x_orig, bins=60, density=True, alpha=0.45, color="steelblue", range=(lo, hi)) - xlin = np.linspace(lo, hi, 400) - for m, s, w in zip(means_n, sigmas_n, weights_n): - if fit["lognormal"]: - safe = np.clip(xlin, 1e-10, None) - ax.plot(xlin, w * stats.norm.pdf(np.log(safe), m, s) / safe, alpha=0.8) - else: - ax.plot(xlin, w * stats.norm.pdf(xlin, m, s), alpha=0.8) - if not np.isnan(result.separator): - ax.axvline(result.separator, color="red", ls="--", - label=f"sep={result.separator:.3g}") - ax.set_xlabel("value"); ax.set_title("Original space"); ax.legend(fontsize=8) - - # Panel 2: fitted space (log or linear) - ax = axes[1] - lo_f, hi_f = np.percentile(x_fit, [0.5, 99.5]) - ax.hist(x_fit, bins=60, density=True, alpha=0.45, color="steelblue", range=(lo_f, hi_f)) - xf = np.linspace(lo_f, hi_f, 400) - for m, s, w in zip(means_n, sigmas_n, weights_n): - ax.plot(xf, w * stats.norm.pdf(xf, m, s), alpha=0.8) - if not np.isnan(fit["sep_native"]): - ax.axvline(fit["sep_native"], color="red", ls="--", - label=f"sep={fit['sep_native']:.3g}") - space_label = "log(value)" if fit["lognormal"] else "value" - ax.set_xlabel(space_label) - ax.set_title(f"Fitted space ({'log' if fit['lognormal'] else 'linear'})") - ax.legend(fontsize=8) + _plot_bimodal_panel(axes[0], fit_linear, is_winner=not result.lognormal, + result_separator=result.separator) + _plot_bimodal_panel(axes[1], fit_log, is_winner=result.lognormal, + result_separator=result.separator) plt.tight_layout() plt.savefig(out_path, dpi=120, bbox_inches="tight") diff --git a/scripts/injection/parquet/build.sh b/scripts/injection/parquet/build.sh new file mode 100644 index 0000000..6e08ef9 --- /dev/null +++ b/scripts/injection/parquet/build.sh @@ -0,0 +1,35 @@ +#!/usr/bin/env bash +# build.sh +# Runs the two-step pipeline: +# 1. munged TSV.gz → clean TSV.gz (make_tsv_gzipped.sql) +# 2. clean TSV.gz → INJECT.parquet (make_parquet.sql) +# Outputs are written next to the input file. + +set -euo pipefail + +DEFAULT_INPUT=~/fg-3/kanta_v3/core/kanta_dev_2026_03_09.txt.gz + +if [[ $# -gt 1 ]]; then + echo "Usage: $0 [input.tsv.gz]" >&2 + exit 1 +fi + +INPUT="$(realpath "${1:-$DEFAULT_INPUT}")" +CLEAN_TSV="$PWD/clean.tsv.gz" +PARQUET="$PWD/INJECT.parquet" + +SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)" + +echo "==> Step 1: $INPUT → $CLEAN_TSV" +clickhouse local \ + --query "$(cat "$SCRIPT_DIR/make_tsv_gzipped.sql")" \ + --param_filePathMungedTxtGz="$INPUT" \ + | gzip > "$CLEAN_TSV" + +echo "==> Step 2: $CLEAN_TSV → $PARQUET" +clickhouse local \ + --query "$(cat "$SCRIPT_DIR/make_parquet.sql")" \ + --param_filePathCleanTxtGz="$CLEAN_TSV" \ + > "$PARQUET" + +echo "Done. Output: $PARQUET" diff --git a/scripts/injection/plot_exploration.py b/scripts/injection/plot_exploration.py index a1c1d14..eb60384 100644 --- a/scripts/injection/plot_exploration.py +++ b/scripts/injection/plot_exploration.py @@ -44,7 +44,8 @@ def make_scatter_plot(plot_name, output=DEFAULT_OUTPUT): ax_scatter.scatter(sub["COUNT"], sub["top_prevalence"], alpha=0.5, s=20, color=_COLORS[label], label=f"{label} (n={len(sub)})") - ax_scatter.legend(fontsize=8, markerscale=1.5, loc="upper right") + handles, labels = ax_scatter.get_legend_handles_labels() + ax_kde.legend(handles, labels, fontsize=8, markerscale=1.5, loc="center right") ax_scatter.set_xlabel("Count (value, no unit)") ax_scatter.set_ylabel("Top unit prevalence (%)") ax_scatter.set_title("TEST_NAME level — injection candidates") From 5f45f0dd89024ab799d599cd5671643966c34943 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 21:29:36 +0000 Subject: [PATCH 10/20] add HTML site generation with per-test Plotly plots and plot data extraction - injection_engine.py: add compute_plot_data() and compute_bimodal_plot_data() to extract compact JSON-serialisable plot data (ECDF, KDE, MAD band) alongside existing PNG generation - explore_test_name.py: accumulate plot data in run_unambiguous/run_ambiguous, write plot_data.json; add SCORE_* cols to _UNIFIED_COLS; add CUTOFF column - build_site.py: per-test HTML pages with Plotly 3-panel engine charts and bimodal check charts for ambiguous tests; --data-dir / --out-dir separation; per-column numeric filtering; clickable TEST_NAME links Co-Authored-By: Claude Sonnet 4.6 --- scripts/injection/build_site.py | 561 ++++++++++++++++++++++++- scripts/injection/explore_test_name.py | 55 ++- scripts/injection/injection_engine.py | 135 ++++++ 3 files changed, 732 insertions(+), 19 deletions(-) diff --git a/scripts/injection/build_site.py b/scripts/injection/build_site.py index d682991..5ce4b59 100644 --- a/scripts/injection/build_site.py +++ b/scripts/injection/build_site.py @@ -12,6 +12,8 @@ """ import argparse +import os +import re import json from pathlib import Path @@ -250,6 +252,212 @@ """ +_AMBIG_PAGE = """ + + + + + __TEST_NAME__ + + + + + +
+ +
+

__TEST_NAME__

+ ambiguous +
+ +
+
Bimodal status
+
__BIMODAL_STATUS__
+
Split improvement
+
__SCORE_IMPROVEMENT__
+
+ +

__EXPLANATION__

+ + +
+
Bimodal check + + winner: __BIM_WINNER__  |  sep=__BIM_SEP__  |  + BC=__BIM_BC__  |  dip_p=__BIM_DIP_P__ + +
+
+
+ + + __ENGINE_SECTIONS__ + + + + + +""" + + # --------------------------------------------------------------------------- # Helpers # --------------------------------------------------------------------------- @@ -257,7 +465,7 @@ def _find_scatter(data_dir: Path, out_dir: Path) -> str: p = data_dir / "test_names_exploration_scatter.png" if p.exists(): - return str(p.resolve().relative_to(out_dir.resolve())) + return os.path.relpath(p.resolve(), out_dir.resolve()) return "" @@ -323,6 +531,8 @@ def _col_def(k, l): d["width"] = f"{COL_WIDTHS[k]}px" if k in wide_cols: d["className"] = "col-wide" + if k == "TEST_NAME": + d["render"] = "__TEST_NAME_RENDER__" return d headers = "".join(f"{label}" for _, label in cols) @@ -334,6 +544,11 @@ def _col_def(k, l): outcome_idx = next((i for i, (k, _) in enumerate(cols) if k == "OUTCOME"), 3) scatter_path = scatter_override if scatter_override is not None else _find_scatter(data_dir, out_dir) + # TEST_NAME render function: link to per-test page + test_name_render = ("function(data,type){if(type!=='display')return data;" + "var slug=data.replace(/[^a-zA-Z0-9_-]/g,'_');" + "return ''+data+'';}") + html = (_INDEX .replace("__SCATTER_BLOCK__", _scatter_block(scatter_path)) .replace("__SUMMARY_SECTION__", _summary_section(data_dir)) @@ -342,13 +557,354 @@ def _col_def(k, l): .replace("__DATA_JSON__", data_json) .replace("__COLUMNS_JSON__", columns_json) .replace("__NUMERIC_COLS_JSON__", numeric_cols_json) - .replace("__OUTCOME_COL_IDX__", str(outcome_idx))) + .replace("__OUTCOME_COL_IDX__", str(outcome_idx)) + .replace('"__TEST_NAME_RENDER__"', test_name_render)) out = out_dir / "index.html" out.write_text(html, encoding="utf-8") print(f"Wrote {out} ({len(rows)} rows)") +def _slugify(name: str) -> str: + return re.sub(r"[^a-zA-Z0-9_-]", "_", name) + + +_TEST_PAGE = """ + + + + + __TEST_NAME__ + + + + + +
+ +
+

__TEST_NAME__

+ __OUTCOME__ + __TYPE__ +
+ +
+
Unit
__UNIT__
+
Unit prevalence
__UNIT_PREV__%
+
N candidate
__N_CAND__
+
N target
__N_TARGET__
+
Decided by
__DECIDED_BY__
+
+ +

__EXPLANATION__

+ +
+ + + + + +""" + + +def _explanation(row, pd) -> str: + outcome = row.get("OUTCOME", "") + decided_by = pd.get("decided_by", "") + unit = row.get("UNIT", "") + prev = row.get("UNIT_PREVALENCE", "") + + if outcome == "PASS": + by_map = { + "KS": f"The KS test confirmed the distributions match (stat={row.get('KS_STAT',''):.3g}, −log10p={row.get('KS_MLOGP',''):.1f}).", + "T": f"The KS test was inconclusive but the Welch t-test confirmed similar means (−log10p={row.get('T_MLOGP',''):.1f}).", + "MAD": f"KS and t-tests were inconclusive, but the MAD test confirmed medians are within the threshold (dist={row.get('MAD_DIST',''):.3g}).", + } + desc = by_map.get(decided_by, "") + return (f"{prev:.1f}% of reference records use unit {unit}. " + f"{desc} Unit {unit} assigned.") + else: + return (f"No unit could be confidently assigned. " + f"The candidate distribution did not match any reference unit " + f"(KS stat={row.get('KS_STAT',''):.3g}, MAD dist={row.get('MAD_DIST',''):.3g}).") + + +def _ambig_explanation(rows, bim_data: dict) -> str: + status = str(rows.iloc[0].get("BIMODAL_STATUS", "")) + sep = rows.iloc[0].get("BIMODAL_SEP") + bc = rows.iloc[0].get("BIMODAL_BC") + dip_p = rows.iloc[0].get("BIMODAL_DIP_P") + impr = rows.iloc[0].get("SCORE_IMPROVEMENT") + + # Bimodal sentence + if status == "skipped": + bim_sentence = "No split was performed — the pre-check passed globally without needing to split the distribution." + elif status == "split_by_score": + impr_str = f"{impr:+.1%}" if pd.notna(impr) else "?" + sep_str = f"{sep:.4g}" if pd.notna(sep) else "?" + bim_sentence = (f"The distribution was split by score improvement ({impr_str}) at cutoff {sep_str}, " + f"even though the dip test did not flag bimodality.") + elif status in ("bimodal", "bimodal_cautious"): + dip_str = f"{dip_p:.3g}" if pd.notna(dip_p) else "?" + bc_str = f"{bc:.3f}" if pd.notna(bc) else "?" + sep_str = f"{sep:.4g}" if pd.notna(sep) else "?" + cautious = " (modes overlap)" if status == "bimodal_cautious" else "" + bim_sentence = (f"Hartigan's dip test detected bimodality{cautious} " + f"(dip p={dip_str}, BC={bc_str}). Distribution split at {sep_str}.") + else: + bim_sentence = "" + + # Per sub-dist sentences + sub_sentences = [] + for _, row in rows.iterrows(): + sub = str(row.get("SUB_DIST", "all")) + unit = str(row.get("UNIT", "")) + outcome = str(row.get("OUTCOME", "")) + decided = str(row.get("NOTES", "")).split("_at_")[1].split("_")[0] if "_at_" in str(row.get("NOTES","")) else "" + prev = row.get("UNIT_PREVALENCE") + prev_str = f"{prev:.1f}%" if pd.notna(prev) else "?" + if sub == "all": + label = "The full candidate distribution" + else: + label = f"The {sub} sub-distribution" + if outcome == "PASS": + sub_sentences.append(f"{label} matched unit {unit} ({prev_str} prevalence, decided by {decided}).") + else: + sub_sentences.append(f"{label} did not match any unit confidently (outcome: {outcome}).") + + return " ".join(filter(None, [bim_sentence] + sub_sentences)) + + +def build_test_pages(out_dir: Path, data_dir: Path) -> None: + plot_data_path = data_dir / "plot_data.json" + inj_path = data_dir / "injection_results.tsv" + + if not plot_data_path.exists(): + print(f"Skipping test pages: {plot_data_path} not found") + return + if not inj_path.exists(): + print(f"Skipping test pages: {inj_path} not found") + return + + plot_data = json.loads(plot_data_path.read_text()) + df = pd.read_csv(inj_path, sep="\t", na_values=["NA"]) + + # Only unambiguous rows have the ecdf key directly + unamb = df[df["TYPE"] == "unambiguous"].copy() + + tests_dir = out_dir / "tests" + tests_dir.mkdir(exist_ok=True) + + written = 0 + for _, row in unamb.iterrows(): + name = row["TEST_NAME"] + pd_ = plot_data.get(name) + if pd_ is None or "ecdf" not in pd_: + continue + + slug = _slugify(name) + outcome = str(row.get("OUTCOME", "")) + html = (_TEST_PAGE + .replace("__TEST_NAME__", name) + .replace("__OUTCOME_CLASS__", "badge-pass" if outcome == "PASS" else "badge-fail") + .replace("__OUTCOME__", outcome) + .replace("__TYPE__", str(row.get("TYPE", ""))) + .replace("__UNIT__", str(row.get("UNIT", ""))) + .replace("__UNIT_PREV__", f"{row.get('UNIT_PREVALENCE', 0):.1f}") + .replace("__N_CAND__", f"{int(row.get('N_CANDIDATE', 0)):,}") + .replace("__N_TARGET__", f"{int(row.get('N_TARGET', 0)):,}") + .replace("__DECIDED_BY__", str(pd_.get("decided_by", ""))) + .replace("__EXPLANATION__", _explanation(row, pd_)) + .replace("__PLOT_DATA_JSON__", json.dumps(pd_))) + (tests_dir / f"{slug}.html").write_text(html, encoding="utf-8") + written += 1 + + # Ambiguous pages + ambig_names = df[df["TYPE"] == "ambiguous"]["TEST_NAME"].unique() + for name in ambig_names: + pd_ = plot_data.get(name) + if pd_ is None or "engine" not in pd_: + continue + + rows = df[df["TEST_NAME"] == name] + bim = pd_.get("bimodal") or {} + first = rows.iloc[0] + + # Build one engine section per winning row + engine_sections_html = "" + sections_data = [] + for _, row in rows.iterrows(): + sub = str(row.get("SUB_DIST", "all")) + unit = str(row.get("UNIT", "")) + key = f"{sub}_{unit}" + epd = pd_["engine"].get(key) + outcome = str(row.get("OUTCOME", "")) + badge = "badge-pass" if outcome == "PASS" else ("badge-fail" if outcome == "FAIL" else "badge-skip") + chart_id = _slugify(key) + label = f"{sub} — {unit}" + engine_sections_html += ( + f'
' + f'
{label} {outcome}' + f'' + f'N cand={int(row.get("N_CANDIDATE",0)):,}   N target={int(row.get("N_TARGET",0)):,}  ' + f'unit prev={row.get("UNIT_PREVALENCE",0):.1f}%
' + f'
' + f'
' + ) + sections_data.append({"chart_id": chart_id, "plot_data": epd}) + + bim_sep = f"{bim.get('separator'):.4g}" if bim.get('separator') is not None else "NA" + bim_bc = f"{bim.get('bc'):.3f}" if bim.get('bc') is not None else "NA" + bim_dip = f"{bim.get('dip_p'):.3g}" if bim.get('dip_p') is not None else "NA" + score_impr = first.get("SCORE_IMPROVEMENT") + score_str = f"{score_impr:+.1%}" if pd.notna(score_impr) else "NA" + + page_data = {"bimodal": bim, "sections": sections_data} + html = (_AMBIG_PAGE + .replace("__TEST_NAME__", name) + .replace("__EXPLANATION__", _ambig_explanation(rows, bim)) + .replace("__BIMODAL_STATUS__", str(first.get("BIMODAL_STATUS", "NA"))) + .replace("__SCORE_IMPROVEMENT__", score_str) + .replace("__BIM_WINNER__", bim.get("winner", "NA")) + .replace("__BIM_SEP__", bim_sep) + .replace("__BIM_BC__", bim_bc) + .replace("__BIM_DIP_P__", bim_dip) + .replace("__ENGINE_SECTIONS__", engine_sections_html) + .replace("__PAGE_DATA_JSON__", json.dumps(page_data))) + slug = _slugify(name) + (tests_dir / f"{slug}.html").write_text(html, encoding="utf-8") + written += 1 + + print(f"Wrote {written} test pages → {tests_dir}") + + def build_doc(out_dir: Path, readme_path: Path) -> None: text = readme_path.read_text() readme_html = markdown.markdown(text, extensions=["tables", "fenced_code"]) @@ -388,6 +944,7 @@ def main(): build_index(out_dir, data_dir, inj_path=inj, scatter_override=scatter) build_doc(out_dir, readme) + build_test_pages(out_dir, data_dir) if __name__ == "__main__": diff --git a/scripts/injection/explore_test_name.py b/scripts/injection/explore_test_name.py index 659cda7..796b74c 100644 --- a/scripts/injection/explore_test_name.py +++ b/scripts/injection/explore_test_name.py @@ -12,6 +12,7 @@ """ import argparse +import json import os import re import subprocess @@ -455,6 +456,8 @@ def _run_engine(c_vals, t_vals, name, dump_dir, plots_dir=None, prevalence=None, [ks_step, t_step, mad_step]) injection_engine.plot_result(c_vals, t_vals, result, name, plots_dir or dump_dir, prevalence=prevalence, tag_override=tag_override) + plot_data = injection_engine.compute_plot_data(c_vals, t_vals, result, + prevalence=prevalence) n_passed = sum(s.passed for s in [ks_step, t_step, mad_step]) updates = dict( @@ -470,11 +473,12 @@ def _run_engine(c_vals, t_vals, name, dump_dir, plots_dir=None, prevalence=None, CAND_DECILES=_fmt_deciles(c_vals), TARG_DECILES=_fmt_deciles(t_vals), ) - return updates, ks_step, t_step, mad_step + return updates, ks_step, t_step, mad_step, plot_data def run_unambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, test_mode=False, out="unambiguous_results.tsv"): + plot_data = {} os.makedirs(dump_dir, exist_ok=True) unambig = plot_name[plot_name["CATEGORY"] == "UNAMBIGUOUS"].sort_values("COUNT", ascending=False) @@ -526,9 +530,10 @@ def run_unambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, test_ if len(c_vals) >= 2 and len(t_vals) >= 2: print("engine...", end=" ", flush=True) - updates, ks, t, mad = _run_engine(c_vals, t_vals, name, dump_dir, - plots_dir=plots_dir, prevalence=prev) + updates, ks, t, mad, pd_ = _run_engine(c_vals, t_vals, name, dump_dir, + plots_dir=plots_dir, prevalence=prev) row.update(updates) + plot_data[name] = pd_ print( f"KS={'P' if ks.passed else 'F'}" f"(stat={ks.details['stat']:.3g},mlogp={updates['KS_MLOGP']:.1f},{ks.details['method']})" @@ -557,7 +562,7 @@ def run_unambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, test_ results[col] = results[col].str.replace(" ", "_", regex=False) results.to_csv(out, sep="\t", index=False, float_format="%.4g", na_rep="NA") print(f"\nWrote {out} ({len(results)} rows)") - return results + return results, plot_data # --------------------------------------------------------------------------- @@ -582,6 +587,7 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, dip_threshold=0.05, min_target_n=30, test_mode=False, split_threshold=0.15, out="ambiguous_results.tsv"): os.makedirs(dump_dir, exist_ok=True) + plot_data = {} ambig = plot_name[plot_name["CATEGORY"] == "AMBIGUOUS"].sort_values("COUNT", ascending=False) if test_mode: @@ -643,12 +649,13 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, precheck = [] # (unit, upct, t_vals, updates, ks_step, t_step, mad_step) for unit, upct in [(u, p) for u, p in top_units if u in unit_data]: t_vals_u = unit_data[unit] - upd, ks, t, mad = _run_engine( + upd, ks, t, mad, pd_ = _run_engine( c_vals, t_vals_u, f"{name} [all] [{unit}]", dump_dir, plots_dir=plots_dir, prevalence=f"{upct:.1f}%", tag_override=f"{tag}_all_{_unit_tag(unit)}", ) + plot_data.setdefault(name, {}).setdefault("engine", {})[f"all_{unit}"] = pd_ precheck.append((unit, upct, t_vals_u, upd, ks, t, mad)) print(f" [all][{unit}({upct:.1f}%)]" f" N={len(c_vals):,}/{len(t_vals_u):,}" @@ -662,6 +669,7 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, # Bimodal check always runs — needed for split score even when pre-check passed bim = injection_engine.bimodal_check(c_vals, dip_threshold=dip_threshold) injection_engine.plot_bimodal_check(bim, name, plots_dir or dump_dir) + plot_data.setdefault(name, {})["bimodal"] = injection_engine.compute_bimodal_plot_data(bim) print(f" bimodal={bim.status} sep={bim.separator:.4g}" f" BC={bim.bc:.3f} dip_p={bim.dip_p:.3g}") @@ -749,12 +757,13 @@ def run_ambiguous(parquet, plot_name, details, dump_dir, plots_dir=None, for sub_name, c_sub in sub_dists: for unit, upct in [(u, p) for u, p in top_units if u in unit_data]: t_vals_u = unit_data[unit] - upd, ks, t, mad = _run_engine( + upd, ks, t, mad, pd_ = _run_engine( c_sub, t_vals_u, f"{name} [{sub_name}] [{unit}]", dump_dir, plots_dir=plots_dir, prevalence=f"{upct:.1f}%", tag_override=f"{tag}_{sub_name}_{_unit_tag(unit)}", ) + plot_data.setdefault(name, {}).setdefault("engine", {})[f"{sub_name}_{unit}"] = pd_ rows.append(dict( TEST_NAME=name, BIMODAL_STATUS=bimodal_label, @@ -811,7 +820,7 @@ def _outcome_rank(o): results.to_csv(out, sep="\t", index=False, float_format="%.4g", na_rep="NA") _print_ambig_summary(results, out) - return results + return results, plot_data def _print_ambig_summary(results, out="ambiguous_results.tsv"): @@ -848,6 +857,7 @@ def _print_ambig_summary(results, out="ambiguous_results.tsv"): _UNIFIED_COLS = [ "TYPE", "TEST_NAME", "BIMODAL_STATUS", "BIMODAL_SEP", "BIMODAL_BC", "BIMODAL_DIP_P", + "SCORE_GLOBAL", "SCORE_SPLIT", "SCORE_IMPROVEMENT", "SUB_DIST", "CUTOFF", "UNIT", "UNIT_PREVALENCE", "PREVALENCE_DICT", "N_CANDIDATE", "N_TARGET", "CAND_DECILES", "TARG_DECILES", @@ -1000,18 +1010,29 @@ def main(): out_tsv=str(data_dir / "omop_summary_table.tsv")) if args.inject: - udf = run_unambiguous(args.parquet, plot_name, details, args.dump_dir, - plots_dir=str(plots_dir), - test_mode=args.test, - out=str(data_dir / "unambiguous_results.tsv")) - adf = run_ambiguous(args.parquet, plot_name, details, args.dump_dir, - plots_dir=str(plots_dir), - dip_threshold=args.dip_threshold, - min_target_n=args.min_target_n, test_mode=args.test, - split_threshold=args.split_threshold, - out=str(data_dir / "ambiguous_results.tsv")) + udf, udf_plots = run_unambiguous(args.parquet, plot_name, details, args.dump_dir, + plots_dir=str(plots_dir), + test_mode=args.test, + out=str(data_dir / "unambiguous_results.tsv")) + adf, adf_plots = run_ambiguous(args.parquet, plot_name, details, args.dump_dir, + plots_dir=str(plots_dir), + dip_threshold=args.dip_threshold, + min_target_n=args.min_target_n, test_mode=args.test, + split_threshold=args.split_threshold, + out=str(data_dir / "ambiguous_results.tsv")) _write_unified(udf, adf, out=str(data_dir / "injection_results.tsv")) + all_plot_data = {**udf_plots, **adf_plots} + plot_data_path = data_dir / "plot_data.json" + class _Enc(json.JSONEncoder): + def default(self, o): + if isinstance(o, (np.bool_,)): return bool(o) + if isinstance(o, np.integer): return int(o) + if isinstance(o, np.floating): return float(o) + return super().default(o) + plot_data_path.write_text(json.dumps(all_plot_data, cls=_Enc), encoding="utf-8") + print(f"Wrote {plot_data_path} ({len(all_plot_data)} TEST_NAMEs)") + no_data = plot_name[plot_name["CATEGORY"] == "NO_DATA"][["TEST_NAME", "COUNT", "OMOP_CONCEPT_ID"]].copy() no_data = no_data.merge( diff --git a/scripts/injection/injection_engine.py b/scripts/injection/injection_engine.py index ab7c65a..b359877 100644 --- a/scripts/injection/injection_engine.py +++ b/scripts/injection/injection_engine.py @@ -284,6 +284,45 @@ def bimodal_check(arr, dip_threshold=0.05, bc_threshold=0.555): return BimodalResult(status, sep, bc, dip_p, best["lognormal"], best, alt) +def compute_bimodal_plot_data(result): + """Extract compact data for the bimodal diagnostic plot.""" + if not result.fit: + return None + + def _fit_data(fit): + if not fit: + return None + x = fit["x_fit"] + lo, hi = float(np.percentile(x, 0.5)), float(np.percentile(x, 99.5)) + xs = np.linspace(lo, hi, _KDE_PTS) + curves = [] + for m, s, w in zip(fit["means_native"], fit["sigmas_native"], fit["weights"]): + from scipy import stats as _stats + curves.append({"y": (w * _stats.norm.pdf(xs, m, s)).tolist(), + "mean": float(m), "sigma": float(s), "weight": float(w)}) + # histogram + counts, edges = np.histogram(x, bins=40, range=(lo, hi), density=True) + return { + "lognormal": fit["lognormal"], + "bic": float(fit["bic"]), + "sep_native": float(fit["sep_native"]) if not np.isnan(fit["sep_native"]) else None, + "x": xs.tolist(), + "hist_counts": counts.tolist(), + "hist_edges": edges.tolist(), + "curves": curves, + } + + return { + "status": result.status, + "separator": float(result.separator) if not np.isnan(result.separator) else None, + "bc": float(result.bc), + "dip_p": float(result.dip_p) if not np.isnan(result.dip_p) else None, + "winner": "log" if result.lognormal else "linear", + "linear": _fit_data(result.fit if not result.fit.get("lognormal") else result.fit_alt), + "log": _fit_data(result.fit if result.fit.get("lognormal") else result.fit_alt), + } + + def _plot_bimodal_panel(ax, fit, is_winner, result_separator): """Draw one GMM panel (linear or log space) onto ax.""" if not fit: @@ -501,6 +540,102 @@ def _load_values(path): # Diagnostics plot # --------------------------------------------------------------------------- +_KDE_PTS = 80 # points per KDE curve for HTML rendering +_ECDF_PTS = 100 # points sampled from each ECDF for HTML rendering + + +def compute_plot_data(candidate, target, result, prevalence=None): + """ + Extract the minimal numeric data needed to reproduce the 3-panel diagnostic + plot in a browser. Returns a plain dict suitable for JSON serialisation. + """ + rng = np.random.default_rng(42) + c_plot = _plot_sample(candidate, rng) + t_plot = _plot_sample(target, rng) + + ks_step = next((s for s in result.steps if s.name == "KS"), None) + t_step = next((s for s in result.steps if s.name == "T"), None) + mad_step = next((s for s in result.steps if s.name == "MAD"), None) + + # --- Panel 1: ECDF (subsample to _ECDF_PTS evenly-spaced quantiles) --- + def _ecdf_compact(arr): + x, y = _ecdf(arr) + idx = np.unique(np.linspace(0, len(x) - 1, _ECDF_PTS, dtype=int)) + return x[idx].tolist(), y[idx].tolist() + + cx, cy = _ecdf_compact(c_plot) + tx, ty = _ecdf_compact(t_plot) + + ks_marker = None + if ks_step: + all_x = np.sort(np.unique(np.concatenate([np.array(cx), np.array(tx)]))) + c_full = np.searchsorted(np.array(cx), all_x, side="right") / len(cx) + t_full = np.searchsorted(np.array(tx), all_x, side="right") / len(tx) + i_max = int(np.argmax(np.abs(c_full - t_full))) + ks_marker = {"x": float(all_x[i_max]), + "y_lo": float(min(c_full[i_max], t_full[i_max])), + "y_hi": float(max(c_full[i_max], t_full[i_max]))} + + # --- Panel 2: KDE linear --- + def _kde_compact(arr, n=_KDE_PTS): + if len(arr) < 2 or np.std(arr) == 0: + return [], [] + kde = stats.gaussian_kde(arr) + xs = np.linspace(arr.min(), arr.max(), n) + return xs.tolist(), kde(xs).tolist() + + c_kde_x, c_kde_y = _kde_compact(c_plot) + t_kde_x, t_kde_y = _kde_compact(t_plot) + + # --- Panel 3: KDE log --- + c_pos = c_plot[c_plot > 0] + t_pos = t_plot[t_plot > 0] + c_log_x, c_log_y = _kde_compact(np.log(c_pos)) if len(c_pos) > 1 else ([], []) + t_log_x, t_log_y = _kde_compact(np.log(t_pos)) if len(t_pos) > 1 else ([], []) + + mad_info = None + if mad_step: + d = mad_step.details + mad_info = { + "c_median": float(d["cand_median"]), + "t_median": float(d["target_median"]), + "threshold": float(d["threshold"]), + "distance": float(d["distance"]), + "MAD": float(d["MAD"]), + "n_mad": float(d["n_mad"]), + "passed": mad_step.passed, + } + + return { + "outcome": result.outcome, + "decided_by": result.decided_by, + "prevalence": str(prevalence) if prevalence else None, + "n_candidate": len(candidate), + "n_target": len(target), + "ecdf": { + "c_x": cx, "c_y": cy, + "t_x": tx, "t_y": ty, + "ks_marker": ks_marker, + "ks": {"stat": float(ks_step.details["stat"]), + "mlogp": float(-np.log10(np.clip(ks_step.details["pval"], 1e-300, 1.0))), + "passed": ks_step.passed} if ks_step else None, + }, + "kde_linear": { + "c_x": c_kde_x, "c_y": c_kde_y, + "t_x": t_kde_x, "t_y": t_kde_y, + "c_mean": float(np.mean(c_plot)), + "t_mean": float(np.mean(t_plot)), + "t": {"stat": float(t_step.details["stat"]), + "mlogp": float(-np.log10(np.clip(t_step.details["pval"], 1e-300, 1.0))), + "passed": t_step.passed} if t_step else None, + }, + "kde_log": { + "c_x": c_log_x, "c_y": c_log_y, + "t_x": t_log_x, "t_y": t_log_y, + "mad": mad_info, + }, + } + def _ecdf(arr): x = np.sort(arr) y = np.arange(1, len(x) + 1) / len(x) From c45801e271b311c2f64a2b37ed17e3ef31218ee5 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 21:37:28 +0000 Subject: [PATCH 11/20] add GitHub Pages deployment and track site data files - .github/workflows/deploy_site.yml: build site with build_site.py on push to master, deploy to GitHub Pages via actions/deploy-pages - .gitignore: exclude generated html/ and intermediate pipeline cache TSVs - data/: track site-facing files (injection_results, plot_data, summaries, scatter) Co-Authored-By: Claude Sonnet 4.6 --- .github/workflows/deploy_site.yml | 49 ++ .gitignore | 10 + scripts/injection/data/assignment_summary.md | 4 +- scripts/injection/data/injection_results.tsv | 441 +----------------- scripts/injection/data/plot_data.json | 1 + scripts/injection/data/summary_table.md | 12 +- .../data/test_names_exploration_scatter.png | Bin 111788 -> 118922 bytes 7 files changed, 90 insertions(+), 427 deletions(-) create mode 100644 .github/workflows/deploy_site.yml create mode 100644 scripts/injection/data/plot_data.json diff --git a/.github/workflows/deploy_site.yml b/.github/workflows/deploy_site.yml new file mode 100644 index 0000000..8b930f3 --- /dev/null +++ b/.github/workflows/deploy_site.yml @@ -0,0 +1,49 @@ +name: Deploy injection site + +on: + push: + branches: [master] + paths: + - scripts/injection/data/** + - scripts/injection/build_site.py + - scripts/injection/README.md + +permissions: + contents: read + pages: write + id-token: write + +concurrency: + group: pages + cancel-in-progress: false + +jobs: + build-and-deploy: + runs-on: ubuntu-latest + environment: + name: github-pages + url: ${{ steps.deployment.outputs.page_url }} + steps: + - uses: actions/checkout@v4 + + - uses: actions/setup-python@v5 + with: + python-version: "3.11" + + - name: Install dependencies + run: pip install pandas markdown + + - name: Build site + run: | + python3 scripts/injection/build_site.py \ + --data-dir scripts/injection/data \ + --out-dir _site + + - uses: actions/configure-pages@v4 + + - uses: actions/upload-pages-artifact@v3 + with: + path: _site + + - id: deployment + uses: actions/deploy-pages@v4 diff --git a/.gitignore b/.gitignore index 353d9e0..78fb261 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,16 @@ finngen_qc/test/ /scripts/test/ +# injection site — generated HTML (rebuilt by CI) +scripts/injection/html/ +# injection intermediate pipeline cache files (not needed for site) +scripts/injection/data/test_name_counts.tsv +scripts/injection/data/test_name_details.tsv +scripts/injection/data/omop_unit_table.tsv +scripts/injection/data/unambiguous_results.tsv +scripts/injection/data/ambiguous_results.tsv +scripts/injection/data/plot_name_level.tsv + #EMACS FILES \#*\# .\#* diff --git a/scripts/injection/data/assignment_summary.md b/scripts/injection/data/assignment_summary.md index d82bd36..fe2ad54 100644 --- a/scripts/injection/data/assignment_summary.md +++ b/scripts/injection/data/assignment_summary.md @@ -5,7 +5,7 @@ Assignment summary (successfully assigned) UNAMBIGUOUS AMBIGUOUS NO_DATA TOTAL names meas names meas names meas names meas ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- -All 10/10 2,874,565/2,874,565 10/10 5,300,918/5,300,918 26/140 284,033/1,062,191 46/160 8,459,516/9,237,674 -OMOP-mapped 10/10 2,874,565/2,874,565 10/10 5,300,918/5,300,918 26/61 284,033/797,892 46/81 8,459,516/8,973,375 +All 10/10 2,800,937/2,800,937 10/10 5,300,918/5,300,918 28/202 285,698/1,108,898 48/222 8,387,553/9,210,753 +OMOP-mapped 9/9 2,800,434/2,800,434 10/10 5,300,918/5,300,918 28/66 285,698/802,091 47/85 8,387,050/8,903,443 ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- ``` diff --git a/scripts/injection/data/injection_results.tsv b/scripts/injection/data/injection_results.tsv index 7a02839..f5132f5 100644 --- a/scripts/injection/data/injection_results.tsv +++ b/scripts/injection/data/injection_results.tsv @@ -1,419 +1,22 @@ -TYPE TEST_NAME BIMODAL_STATUS BIMODAL_SEP BIMODAL_BC BIMODAL_DIP_P SUB_DIST UNIT UNIT_PREVALENCE PREVALENCE_DICT BEST_UNIT N_CANDIDATE N_TARGET CAND_DECILES TARG_DECILES KS_STAT KS_MLOGP KS_PASS T_STAT T_MLOGP T_PASS MAD_DIST MAD_THRESHOLD MAD_PASS OUTCOME NOTES -unambiguous b-eryt NA NA NA NA all e12/l 99.99 {e12/l:99.99,%:0.01,e9/l:0} e12/l 2702234 8026175 [3.25,3.63,3.9,4.1,4.28,4.44,4.6,4.79,5.04] [3.3,3.7,3.99,4.2,4.35,4.5,4.67,4.83,5.1] 0.05101 300 PASS -81.68 300 FAIL 0.07 1.35 PASS PASS PASS_at_KS_(2/3) -unambiguous b-leuk NA NA NA NA all e9/l 100 {e9/l:100,g/l:0,form:0} e9/l 2610059 7601140 [4.4,5.2,5.8,6.4,7,7.7,8.6,9.7,11.7] [4.3,5.1,5.7,6.3,6.9,7.5,8.3,9.5,11.5] 0.03003 300 PASS 40.72 300 FAIL 0.1 4.8 PASS PASS PASS_at_KS_(2/3) -unambiguous b-trom NA NA NA NA all e9/l 100 {e9/l:100,%:0,form:0} e9/l 2413303 7894206 [150,183,207,227,246,267,291,324,381] [154,187,209,229,247,267,291,321,374] 0.01194 228.8 PASS 15.29 52.07 FAIL 1 156 PASS PASS PASS_at_KS_(2/3) -unambiguous p-inr NA NA NA NA all inr 99.17 {inr:99.17,ng:0.52,form:0.31} inr 1094306 73174 [1.5,1.9,2.1,2.3,2.4,2.6,2.7,3,3.3] [1,1.3,1.9,2.1,2.3,2.4,2.6,2.8,3.2] 0.1414 300 PASS 69.28 300 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) -unambiguous b-hb NA NA NA NA all g/l 99.99 {g/l:99.99,e9/l:0.01,form:0} g/l 895512 10047206 [106,116,124,129,133,137,142,147,154] [99,110,119,125,130,135,140,145,152] 0.07401 300 PASS 177.8 300 FAIL 3 39 PASS PASS PASS_at_KS_(2/3) -unambiguous e-mcv NA NA NA NA all fl 99.96 {fl:99.96,%:0.03,pg:0} fl 863209 10019368 [84.6,87,89,90,91,93,94,96,99] [85,87,89,90,91,93,94,96,99] 0.009422 61 PASS -18.11 72.59 FAIL 0 9 PASS PASS PASS_at_KS_(2/3) -unambiguous e-mch NA NA NA NA all pg 99.78 {pg:99.78,pg/cell:0.21,fl:0} pg 859269 10022306 [27,29,29,30,30,31,31,32,33] [28,29,29,30,30,31,31,32,33] 0.01713 201.5 PASS -5.64 7.768 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) -unambiguous pt-gfreepi NA NA NA NA all ml/min/173m2 99.11 {ml/min/173m2:99.11,form:0.89} ml/min/173m2 752397 1889100 [39,51,59,67,74,80,86,92,101] [38,54,65,73,80,86,91,97,106] 0.09026 300 PASS 0.6265 0.2749 PASS 6 48 PASS PASS PASS_at_KS_(3/3) -unambiguous p-k NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/mol:0,nmol/l:0} mmol/l 701228 6736993 [3.5,3.7,3.8,3.9,4,4.1,4.2,4.3,4.5] [3.5,3.7,3.8,3.9,4,4.1,4.2,4.3,4.6] 0.04774 300 PASS 8.691 17.45 FAIL 0 0.9 PASS PASS PASS_at_KS_(2/3) -unambiguous b-neut NA NA NA NA all e9/l 98.61 {e9/l:98.61,%:1.39} e9/l 678979 1796762 [1.7,2.32,2.81,3.27,3.74,4.29,4.97,5.95,7.77] [1.68,2.28,2.73,3.19,3.63,4.17,4.8,5.74,7.5] 0.02295 225.1 PASS 26.64 155.6 FAIL 0.11 3.87 PASS PASS PASS_at_KS_(2/3) -unambiguous p-na NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0,1:0} mmol/l 615417 6700235 [134,137,138,139,140,141,142,142,144] [134,136,138,139,140,140,141,142,143] 0.08943 300 PASS 110.5 300 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) -unambiguous u-ph NA NA NA NA all form 98.78 {form:98.78,ph:1.22} form 614126 18003 [5.5,5.5,6,6,6.5,7,7,7,7.5] [5,5,5,5.5,6,6,6.5,7,7] 0.2368 300 PASS 78.83 300 FAIL 0.5 3 PASS PASS PASS_at_KS_(2/3) -unambiguous p-krea NA NA NA NA all umol/l 99.98 {umol/l:99.98,umol:0.02,ml/min/173m2:0} umol/l 597169 7087388 [56,63,68,73,79,86,94,106,128] [53,60,65,70,76,82,90,104,135] 0.05594 300 PASS -81.6 300 FAIL 3 45 PASS PASS PASS_at_KS_(2/3) -unambiguous p-alat NA NA NA NA all u/l 100 {u/l:100,umol/l:0,mmol/l:0} u/l 484108 4339404 [13,16,18,21,24,27,32,40,56] [13,16,18,21,24,28,33,42,61] 0.01793 121.3 PASS -61.36 300 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) -unambiguous e-rdw NA NA NA NA all % 100 {%:100} % 445075 5838138 [13,13,13,14,14,14,15,15,17] [12.6,13,13,13.5,14,14,15,16,17] 0.04145 300 PASS -18.65 76.9 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-gluk NA NA NA NA all mmol/l 99.96 {mmol/l:99.96,nmol/l:0.04,mmol/:0} mmol/l 377861 1527267 [5.2,5.5,5.7,5.9,6.1,6.4,6.7,7.2,8.2] [5,5.3,5.5,5.7,5.8,6.1,6.4,6.9,7.8] 5.211e-06 -0 FAIL -0.9174 0.445 PASS 0.3 1.5 PASS PASS PASS_at_T_(2/3) -unambiguous b-baso NA NA NA NA all e9/l 98.99 {e9/l:98.99,%:1.01} e9/l 358577 1025695 [0.01,0.02,0.03,0.03,0.04,0.04,0.05,0.06,0.08] [0,0.02,0.02,0.03,0.04,0.04,0.05,0.07,0.1] 0.06985 300 PASS 17 64.07 FAIL 0 0.06 PASS PASS PASS_at_KS_(2/3) -unambiguous b-hba1c NA NA NA NA all mmol/mol 99.68 {mmol/mol:99.68,mmol/m:0.17,mmol:0.07} mmol/mol 356117 1619587 [34,37,38,40,42,44,47,52,62] [33,35,37,38,40,42,44.8,50,60] 0.1172 300 PASS 68.38 300 FAIL 2 15 PASS PASS PASS_at_KS_(2/3) -unambiguous p-crp NA NA NA NA all mg/l 100 {mg/l:100,mg/ml:0,alle:0} mg/l 329485 3909221 [2,4,6,10,15,23,37,58,99] [3,5,8,13,21,34,52,81,133] 0.08114 300 PASS -122 300 FAIL 6 54 PASS PASS PASS_at_KS_(2/3) -unambiguous b-erblast NA NA NA NA all e9/l 100 {e9/l:100} e9/l 314346 313463 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.003567 1.435 PASS 8.538 16.86 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous e-mchc NA NA NA NA all g/l 100 {g/l:100,e9/l:0,form:0} g/l 306131 6813807 [314,320,326,330,333,336,339,343,348] [315,321,325,328,331,333,337,340,346] 0.07143 300 PASS 35.87 280.8 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-kol-ldl NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0,mmoil/l:0} mmol/l 300160 1258918 [1.6,2,2.2,2.5,2.8,3.1,3.4,3.78,4.2] [1.5,1.8,2.1,2.38,2.6,2.9,3.2,3.6,4.1] 0.07917 300 PASS 78.61 300 FAIL 0.2 2.1 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-kol NA NA NA NA all mmol/l 100 {mmol/l:100,mmol:0,mmol/:0} mmol/l 246075 1160366 [3.4,3.8,4.1,4.5,4.8,5.1,5.4,5.8,6.3] [3.2,3.6,4,4.3,4.6,4.9,5.2,5.6,6.2] 0.08252 300 PASS 72.12 300 FAIL 0.2 2.4 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-trigly NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0} mmol/l 239400 1104071 [0.7,0.85,1,1.1,1.25,1.41,1.67,1.99,2.55] [0.7,0.82,0.96,1.1,1.21,1.4,1.6,1.89,2.4] 0.03363 193.1 PASS 21.77 104.2 FAIL 0.04 1.17 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-kol-hdl NA NA NA NA all mmol/l 100 {mmol/l:100,mml/l:0,mmol:0} mmol/l 235506 1110652 [0.96,1.1,1.2,1.31,1.42,1.54,1.68,1.85,2.11] [0.95,1.09,1.2,1.3,1.4,1.5,1.63,1.8,2.03] 0.03251 178.1 PASS 30.77 206.9 FAIL 0.02 0.84 PASS PASS PASS_at_KS_(2/3) -unambiguous pt-gfre NA NA NA NA all ml/min/173m2 99.63 {ml/min/173m2:99.63,form:0.37,mi/min/173m2:0} ml/min/173m2 216785 1096392 [42,54,63,71,77,83,88,93,102] [41,57,67,75,82,87,92,98,106.1] 0.08308 300 PASS -56.47 300 FAIL 5 45 PASS PASS PASS_at_KS_(2/3) -unambiguous p-t4-v NA NA NA NA all pmol/l 100 {pmol/l:100,nmol/l:0,pmo/l:0} pmol/l 203419 904186 [12,13,14,14.9,15.5,16.2,17,18.1,19.9] [12,13,14,14.7,15.2,16,17,18,19.5] 0.0401 231.7 PASS 21.9 105.5 FAIL 0.3 5.7 PASS PASS PASS_at_KS_(2/3) -unambiguous p-afos NA NA NA NA all u/l 100 {u/l:100,umol/l:0} u/l 179506 2452551 [47,55,61,67,74,81,91,106,134] [49,57,64,70,77,85,95,111,151] 0.04779 300 PASS -42.81 300 FAIL 3 57 PASS PASS PASS_at_KS_(2/3) -unambiguous vb-ph NA NA NA NA all ph 99.15 {ph:99.15,form:0.64,1:0.21} ph 174741 931 [7.3,7.33,7.35,7.37,7.38,7.39,7.41,7.42,7.45] [7.31,7.34,7.36,7.37,7.38,7.39,7.4,7.42,7.44] 0.06548 3.169 PASS -1.378 0.7736 PASS 0 0.09 PASS PASS PASS_at_KS_(3/3) -unambiguous b-erybla NA NA NA NA all e9/l 100 {e9/l:100} e9/l 169159 1041960 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.02442 75.13 PASS 19.22 81.51 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous u-eryt NA NA NA NA all e6/l 98.22 {e6/l:98.22,u/field:0.92,form:0.43} e6/l 157713 273727 [1,2,4,5,8,13,23,52,193] [2.2,4,6,7.8,10,13,19,30.9,86.7] 0.1553 300 PASS -5.124 6.523 FAIL 2 19.5 PASS PASS PASS_at_KS_(2/3) -unambiguous u-leuk NA NA NA NA all e6/l 99.11 {e6/l:99.11,u/field:0.6,/sunf:0.27} e6/l 156801 294204 [1,1,2,4,7,13,29,88,402] [0.8,1,2,3,5,8,16.8,46,216] 0.07322 300 PASS -3.965 4.134 FAIL 2 12 PASS PASS PASS_at_KS_(2/3) -unambiguous b-la NA NA NA NA all mm/h 99.95 {mm/h:99.95,mmol:0.03,form:0.01} mm/h 156217 1232795 [2,5,6,8,10,15,21,28,41] [2,4,5,7,9,12,16,25,38] 0.06215 300 PASS 1.287 0.7029 PASS 1 18 PASS PASS PASS_at_KS_(3/3) -unambiguous u-lier NA NA NA NA all e6/l 100 {e6/l:100,u/field:0} e6/l 155357 195506 [0,0,0,0,0,0,0,1,3] [0,0,0,0,0,0,0.13,0.81,1.22] 0.09197 300 PASS 48.69 300 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous u-levyep NA NA NA NA all e6/l 99.53 {e6/l:99.53,u/field:0.47} e6/l 135481 81771 [0,0,0,0,0,1,2,4,11] [0,0,0,0,1,1,2,4,9] 0.09894 300 PASS 5.548 7.539 FAIL 1 3 PASS PASS PASS_at_KS_(2/3) -unambiguous u-pienep NA NA NA NA all e6/l 100 {e6/l:100} e6/l 135163 65516 [0,0,0,0,0,1,1,2,4] [0,0,0,0,0,0.9,1,2,4] 0.05883 132.5 PASS -1.225 0.6567 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -unambiguous cb-ph NA NA NA NA all ph 100 {ph:100} ph 104918 9565 [7.35,7.38,7.39,7.41,7.42,7.43,7.44,7.45,7.47] [7.35,7.37,7.39,7.41,7.42,7.43,7.44,7.46,7.48] 0.02779 5.587 PASS -0.9305 0.4533 PASS 0 0.09 PASS PASS PASS_at_KS_(3/3) -unambiguous p-gt NA NA NA NA all u/l 100 {u/l:100,mg/ml:0,mg/l:0} u/l 103122 716550 [15,20,26,33,44,58,78,114,200] [15,19,23,29,36,47,65,100,195] 0.07536 300 PASS 5.969 8.621 FAIL 8 57 PASS PASS PASS_at_KS_(2/3) -unambiguous u-krea NA NA NA NA all mmol/l 98.91 {mmol/l:98.91,umol/l:1.09,g/l:0} mmol/l 102588 389195 [3.3,4.4,5.3,6.3,7.4,8.7,10.3,12.8,18.2] [3.1,4.1,4.9,5.8,6.8,7.9,9.3,11.1,14.2] 0.06325 282.1 PASS 71.26 300 FAIL 0.6 7.8 PASS PASS PASS_at_KS_(2/3) -unambiguous hdl/kol NA NA NA NA all % 100 {%:100} % 89962 130585 [21,25,28,30,33,36,39,42,47] [21,24,27,30,32,35,38,41,46] 0.033 50.09 PASS 15.48 53.27 FAIL 1 21 PASS PASS PASS_at_KS_(2/3) -unambiguous p-psa NA NA NA NA all ug/l 100 {ug/l:100,µh/l:0} ug/l 85734 353554 [0.36,0.61,0.89,1.2,1.62,2.2,3.02,4.4,6.9] [0.25,0.52,0.82,1.2,1.74,2.54,3.8,5.9,10.6] 0.06999 293.6 PASS -32.53 231.1 FAIL 0.12 4.08 PASS PASS PASS_at_KS_(2/3) -unambiguous fb-leuk NA NA NA NA all e9/l 100 {e9/l:100} e9/l 78470 326274 [4.5,5.2,5.7,6.2,6.7,7.3,8,8.9,10.4] [4.5,5.1,5.6,6.1,6.6,7.2,7.9,8.8,10.4] 0.01482 11.77 PASS 0.9066 0.4382 PASS 0.1 4.2 PASS PASS PASS_at_KS_(3/3) -unambiguous p-kol-ldl NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 76361 340811 [1.3,1.5,1.7,2,2.2,2.5,2.9,3.3,3.8] [1.3,1.5,1.8,2,2.3,2.6,2.9,3.3,3.8] 0.01497 11.84 PASS -8.846 18.04 FAIL 0.1 2.1 PASS PASS PASS_at_KS_(2/3) -unambiguous b-tromb NA NA NA NA all e9/l 100 {e9/l:100} e9/l 75012 323035 [168,193,212,229,246,264,286,314,359] [163,190,210,228,245,263,284,313,361] 0.01738 15.68 PASS 4.206 4.584 FAIL 1 144 PASS PASS PASS_at_KS_(2/3) -unambiguous p-ferrit NA NA NA NA all ug/l 100 {ug/l:100} ug/l 65282 414832 [12,19,28,39,54,77,111,168,282] [14,23,34,48,67,96,142,224,419] 0.06433 202.6 PASS -32.04 224.1 FAIL 13 147 PASS PASS PASS_at_KS_(2/3) -unambiguous p-kol NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 63596 235312 [3,3.4,3.7,4,4.3,4.6,4.9,5.3,5.9] [3,3.4,3.7,4,4.3,4.6,5,5.4,5.9] 0.02577 28.58 PASS -10.74 26.15 FAIL 0 2.4 PASS PASS PASS_at_KS_(2/3) -unambiguous p-kol-hdl NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 61142 221234 [0.97,1.09,1.2,1.3,1.4,1.51,1.64,1.8,2.03] [0.96,1.09,1.2,1.3,1.4,1.51,1.63,1.79,2.02] 0.006651 1.542 PASS 3.266 2.963 FAIL 0 0.84 PASS PASS PASS_at_KS_(2/3) -unambiguous p-trigly NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 60090 219531 [0.72,0.88,1,1.12,1.28,1.44,1.66,1.97,2.51] [0.7,0.84,0.97,1.1,1.24,1.4,1.62,1.92,2.49] 0.02559 26.55 PASS 3.328 3.058 FAIL 0.04 1.17 PASS PASS PASS_at_KS_(2/3) -unambiguous u-alb NA NA NA NA all mg/l 100 {mg/l:100,mg/ml:0,mg/mmol:0} mg/l 54491 245848 [3,4,5,7,9.4,14,24.3,45.9,123] [3.7,5,6,9,13,21.5,42,102,337] 0.09064 300 PASS -43.91 300 FAIL 3.6 27 PASS PASS PASS_at_KS_(2/3) -unambiguous ab-be NA NA NA NA all mmol/l 99.98 {mmol/l:99.98,ml:0.01,%:0} mmol/l 52627 328149 [-7.2,-4.9,-3.7,-2.8,-2.2,-1.6,-1.1,-0.7,-0.3] [-4.6,-2.4,-0.8,0.2,1,1.9,2.9,4.2,6.3] 0.5981 300 FAIL -216.4 300 FAIL 3.2 7.5 PASS PASS PASS_at_MAD_(1/3) -unambiguous p-alb NA NA NA NA all g/l 100 {g/l:100,%:0} g/l 51547 870387 [26,30,33,34.4,36,37,38,39.2,41] [25,29,32,34,35.6,37,38,39.4,41] 0.04602 89.32 PASS 17.96 71.18 FAIL 0.4 10.8 PASS PASS PASS_at_KS_(2/3) -unambiguous u-albkre NA NA NA NA all mg/mmol 100 {mg/mmol:100,g/mol:0} mg/mmol 51403 242629 [0.3,0.4,0.6,0.8,1.2,1.9,3.4,7,20.5] [0.3,0.5,0.7,1,1.6,2.9,6.2,16.1,60.6] 0.08722 280.5 PASS -1.503 0.8765 PASS 0.4 3.9 PASS PASS PASS_at_KS_(3/3) -unambiguous l-lymf(a) NA NA NA NA all % 100 {%:100} % 50542 588720 [14,19,22,26,28,31,34,38,44] [12,17,21,24,27,30,34,38,44] 0.04828 94.06 PASS 21.39 100.4 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) -unambiguous u-gluk-o NA NA NA NA all estimate 99.32 {estimate:99.32,form:0.67,A:0.01} estimate 50039 123942 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01171 3.946 PASS 4.074 4.334 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous l-mono(a) NA NA NA NA all % 100 {%:100} % 49676 588958 [6,7,8,8,9,10,11,12,13] [6,7,8,8,9,10,11,12,13] 0.01509 8.768 PASS -0.3816 0.1532 PASS 0 6 PASS PASS PASS_at_KS_(3/3) -unambiguous l-eos(a) NA NA NA NA all % 100 {%:100} % 49313 92061 [0,1,2,2,2,3,4,5,6] [0,1,2,2,2,3,4,4,6] 0.0186 9.351 PASS 7.754 14.05 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) -unambiguous l-neut(a) NA NA NA NA all % 100 {%:100} % 48854 590444 [41,47,51,54,58,61,64,68,74] [41,48,52,55,59,62,66,70,77] 0.0498 96.99 PASS -20.59 93.1 FAIL 1 27 PASS PASS PASS_at_KS_(2/3) -unambiguous u-nitr-o NA NA NA NA all estimate 99.34 {estimate:99.34,form:0.66,A:0} estimate 48542 124895 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.0008223 -0 FAIL 3.955 4.116 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -unambiguous l-baso(a) NA NA NA NA all % 100 {%:100} % 48061 93247 [0,0,0,1,1,1,1,1,1] [0,0,1,1,1,1,1,1,1] 0.1053 300 PASS -33.15 238.8 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous vb-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 46427 126442 [-7.4,-5.3,-4,-3.1,-2.4,-1.8,-1.2,-0.7,-0.3] [-3.4,-0.8,0.3,1,1.7,2.4,3.2,4.2,5.9] 0.7185 300 FAIL -239 300 FAIL 4.1 5.4 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-b12-tc2 NA NA NA NA all pmol/l 100 {pmol/l:100,>35:0} pmol/l 46070 176282 [51,65,76,87,97,107,117,130,160] [52,66,76.7,86,95.1,105,114,124,138] 0.07646 185.4 PASS 24.8 134.4 FAIL 1.9 71.7 PASS PASS PASS_at_KS_(2/3) -unambiguous p-bil NA NA NA NA all umol/l 100 {umol/l:100} umol/l 45706 1372979 [5,6,7,8,9,11,13,17,26] [5,6,7,8,9,11,13,16.4,25] 0.03003 34.39 PASS -1.03 0.5186 PASS 0 9 PASS PASS PASS_at_KS_(3/3) -unambiguous u-suhtih NA NA NA NA all kg/l 99.91 {kg/l:99.91,ratio:0.09} kg/l 41978 4621 [1.009,1.011,1.013,1.015,1.016,1.018,1.02,1.022,1.025] [1.01,1.01,1.01,1.01,1.015,1.015,1.015,1.02,1.02] 0.2869 300 PASS 19.31 81.92 FAIL 0.001 0.015 PASS PASS PASS_at_KS_(2/3) -unambiguous p-probnp NA NA NA NA all ng/l 100 {ng/l:100} ng/l 41763 317468 [81,133,211,338,555,907,1400,2220,4148] [81,146,246,412,695,1144,1849,3080,6216] 0.06289 126.6 PASS -36.62 290.5 FAIL 140 1800 PASS PASS PASS_at_KS_(2/3) -unambiguous u-alb-o NA NA NA NA all estimate 99.75 {estimate:99.75,form:0.25,A:0} estimate 41443 115398 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.0002578 -0 FAIL 0.961 0.4729 PASS 0 0 PASS PASS PASS_at_T_(2/3) -unambiguous u-eryt-o NA NA NA NA all estimate 99.32 {estimate:99.32,form:0.68,eru/ul:0} estimate 40464 103663 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01896 8.797 PASS 7.44 12.99 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous u-leuk-o NA NA NA NA all estimate 99.05 {estimate:99.05,form:0.86,u/field:0.05} estimate 39068 102815 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.04043 39.92 PASS 8.452 16.53 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous p-psa-v NA NA NA NA all ug/l 99.99 {ug/l:99.99,form:0.01,%:0} ug/l 38748 112760 [0.22,0.34,0.44,0.54,0.65,0.78,0.92,1.11,1.54] [0.23,0.34,0.45,0.56,0.69,0.8,1,1.24,1.7] 0.03829 36.44 PASS -14.73 48.34 FAIL 0.04 0.96 PASS PASS PASS_at_KS_(2/3) -unambiguous p-d-25 NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 38104 55698 [47,58,66,74,80,88,96,107,124] [47,57,64,71,77,84,93,103,120] 0.04497 39.47 PASS 12.91 37.36 FAIL 3 54 PASS PASS PASS_at_KS_(2/3) -unambiguous s-k/l-s-v NA NA NA NA all ratio 99.15 {ratio:99.15,1:0.69,mg/l:0.16} ratio 37831 2440 [0.17,0.77,1.02,1.21,1.4,1.63,2.01,3.43,14.3] [0.12,0.79,0.987,1.19,1.445,1.76,3.09,10,30.9] 0.09989 19.63 PASS 1.874 1.215 PASS 0.045 2.445 PASS PASS PASS_at_KS_(3/3) -unambiguous p-uraat NA NA NA NA all umol/l 98.74 {umol/l:98.74,mmol/l:1.26} umol/l 37337 226132 [246,288,322,353,383,416,450,492,549] [225,266,298,327,355,385,420,463,526] 0.09345 243.3 PASS 37.11 296.8 FAIL 28 234 PASS PASS PASS_at_KS_(2/3) -unambiguous cb-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 36614 63821 [-6.7,-4.6,-3.3,-2.4,-1.6,-1,-0.6,-0.2,2] [-2.8,0,0.7,1.3,2,2.8,3.8,5.2,7.7] 0.6474 300 FAIL -155.1 300 FAIL 3.6 5.7 PASS PASS PASS_at_MAD_(1/3) -unambiguous p-tfr NA NA NA NA all mg/l 100 {mg/l:100} mg/l 35728 152596 [2.1,2.5,2.9,3.2,3.6,4.1,4.8,5.8,7.5] [0.8,1.3,2.1,2.5,2.9,3.3,3.8,4.6,6.2] 0.2209 300 PASS 57.88 300 FAIL 0.7 3.9 PASS PASS PASS_at_KS_(2/3) -unambiguous p-gluk NA NA NA NA all mmol/l 99.96 {mmol/l:99.96,mmol:0.04,%:0} mmol/l 34995 1187642 [5,5.5,5.8,6,6.4,7,7.6,8.8,11.4] [5.1,5.5,5.8,6.2,6.6,7.1,7.8,8.8,10.8] 0.05953 104.5 PASS 3.159 2.8 FAIL 0.2 3.6 PASS PASS PASS_at_KS_(2/3) -unambiguous p-tnt NA NA NA NA all ng/l 99.98 {ng/l:99.98,ug/l:0.02} ng/l 32887 400470 [7,9,11,15,18,23,30,42,74] [7,9,12,15,19,25,34,51,105] 0.04291 48.34 PASS -29.16 185.5 FAIL 1 33 PASS PASS PASS_at_KS_(2/3) -unambiguous l-monos NA NA NA NA all % 99.4 {%:99.4,e9/l:0.6} % 31974 434312 [6,7,8,8,9,10,11,12,13] [5,7,7.4,8,9,10,10.1,11.7,13] 0.03102 24.6 PASS 2.538 1.953 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) -unambiguous fs-ph NA NA NA NA all ph 100 {ph:100} ph 30367 986 [7.34,7.36,7.37,7.38,7.39,7.4,7.41,7.42,7.44] [7.38,7.4,7.41,7.42,7.43,7.43,7.44,7.45,7.47] 0.3802 123.9 FAIL 0.9998 0.4983 PASS 0.04 0.06 PASS PASS PASS_at_T_(2/3) -unambiguous ca++/7.40 NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 27423 98719 [1.18,1.2,1.2,1.22,1.23,1.25,1.27,1.3,1.33] [1.14,1.18,1.21,1.22,1.23,1.24,1.26,1.27,1.31] 0.1306 300 PASS 27.76 167.5 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) -unambiguous ca-ion NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 27272 99169 [1.18,1.2,1.21,1.23,1.24,1.26,1.28,1.3,1.32] [1.14,1.18,1.21,1.23,1.24,1.26,1.27,1.29,1.33] 0.1066 211.3 PASS 3.516 3.358 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) -unambiguous fe-folaat NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 27167 76563 [313.6,396.2,479,591,763,1023,1309,1617,2032] [354,452,568,727,968,1302,1580,1854,2290] 0.09833 168.5 PASS -31.8 219.1 FAIL 205 1626 PASS PASS PASS_at_KS_(2/3) -unambiguous fs-folaat NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 26471 163828 [6.9,8.9,10.9,13.2,16.3,21,27.9,37.2,51] [7.5,9.7,11.9,14.2,17,20.8,25.9,32.9,42.44] 0.05394 57.34 PASS 11.64 30.51 FAIL 0.7 23.1 PASS PASS PASS_at_KS_(2/3) -unambiguous b-retik NA NA NA NA all e9/l 99.94 {e9/l:99.94,%:0.06} e9/l 26123 65705 [36.9,46,53.5,60.7,68,76.3,87.8,103.3,134.1] [37,47,54,61,68,76,86,101,130] 0.02002 6.213 PASS 1.564 0.9285 PASS 0 60 PASS PASS PASS_at_KS_(3/3) -unambiguous p-amyl NA NA NA NA all u/l 100 {u/l:100,umol/l:0} u/l 25904 342833 [29,37,43,49,54,60,68,79,100] [26,34,40,46,52,59,68,80,104] 0.04508 42.25 PASS -10.49 25 FAIL 2 51 PASS PASS PASS_at_KS_(2/3) -unambiguous p-ca NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 25414 398611 [2.19,2.25,2.28,2.31,2.34,2.37,2.4,2.44,2.51] [2.21,2.27,2.31,2.34,2.37,2.4,2.44,2.47,2.53] 0.1137 268.8 PASS -28.26 172.6 FAIL 0.03 0.24 PASS PASS PASS_at_KS_(2/3) -unambiguous s-ca-ion NA NA NA NA all mmol/l 100 {mmol/l:100,mmol:0} mmol/l 25366 460023 [1.15,1.19,1.21,1.22,1.24,1.25,1.27,1.3,1.34] [1.14,1.18,1.2,1.21,1.23,1.24,1.26,1.28,1.31] 0.08483 150.2 PASS 17.13 64.7 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) -unambiguous p-psa-suh NA NA NA NA all % 98.61 {%:98.61,form:1.12,ug/l:0.26} % 24327 93796 [0.22,8,12,15,18,20.6,24,28,33.4] [9,12,14,16.8,19,22,25,29,36] 0.1437 300 PASS -34.01 248.8 FAIL 1 21 PASS PASS PASS_at_KS_(2/3) -unambiguous l-neut NA NA NA NA all % 98.82 {%:98.82,e9/l:1.18,osuus:0} % 24285 378348 [3,5,26,44,51,56,60,65,72] [42,48,52,55.5,59,62,65.8,70,76] 0.2856 300 PASS -95.32 300 FAIL 8 27 PASS PASS PASS_at_KS_(2/3) -unambiguous oma-crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 21682 1347 [6,8,12,16,22,30,42,61,96] [6,8,10,13.4,19,26,36,53,81] 0.0552 3.073 PASS 3.631 3.535 FAIL 3 36 PASS PASS PASS_at_KS_(2/3) -unambiguous p-asat NA NA NA NA all u/l 99.95 {u/l:99.95,umol/l:0.05,u/l37:0} u/l 21421 444746 [18,21,24,26,29,34,40,50,73] [17,19,22,24,27,30,35,44,70] 0.07457 98.55 PASS -6.633 10.48 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) -unambiguous pt-glomerulussuodosnopeus,ckd-epi-kaava NA NA NA NA all ml/min/173m2 99.79 {ml/min/173m2:99.79,form:0.21} ml/min/173m2 21275 5606 [37,50,60,68,76,82,88,94,102] [38,49,58,65,72,79,84,89,95] 0.08282 26.2 PASS 7.857 14.36 FAIL 4 48 PASS PASS PASS_at_KS_(2/3) -unambiguous l-eos NA NA NA NA all % 99.56 {%:99.56,e9/l:0.44} % 21090 942601 [0,0.9,1,1.9,2,3,3.2,4.5,6.8] [0,1,1,2,2,3,3.9,4,6] 0.07833 109.8 PASS -5.632 7.745 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) -unambiguous l-neutr NA NA NA NA all % 99.66 {%:99.66,e9/l:0.34,e9:0} % 20755 86909 [43,49,53,56,59,63,66,70,75] [44,49,53,56,59,62.4,66,70,76] 0.01054 1.318 PASS -1.996 1.338 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) -unambiguous p-t4v NA NA NA NA all pmol/l 100 {pmol/l:100} pmol/l 20621 90249 [12.2,13.4,14.2,14.9,15.6,16.3,17.2,18.3,20] [12.7,13.8,14.6,15.3,16,16.7,17.5,18.5,20] 0.05243 39.81 PASS -10.15 23.44 FAIL 0.4 5.7 PASS PASS PASS_at_KS_(2/3) -unambiguous s-b12-vit NA NA NA NA all pmol/l 100 {pmol/l:100,u:0,pmol/:0} pmol/l 20314 76509 [227,280,325,370,417,476,551,650,835] [232,281,321,361,403,452,513,601,768] 0.05142 36.61 PASS 9.714 21.55 FAIL 14 354 PASS PASS PASS_at_KS_(2/3) -unambiguous l-eosin NA NA NA NA all % 100 {%:100} % 19838 82317 [1,1,2,2,3,3,4,5,7] [1,1,2,2,3,3,4,5,6] 0.01263 1.919 PASS 1.953 1.294 PASS 0 3 PASS PASS PASS_at_KS_(3/3) -unambiguous l-lymfos NA NA NA NA all % 100 {%:100} % 19480 83981 [13,17,21,24,26,29,32,36,41] [13,18,21,24,27,30,33,36,42] 0.01782 4.064 PASS -1.254 0.6779 PASS 1 21 PASS PASS PASS_at_KS_(3/3) -unambiguous b-basof NA NA NA NA all e9/l 100 {e9/l:100} e9/l 19447 4729 [0.02,0.03,0.03,0.04,0.04,0.05,0.06,0.07,0.08] [0.02,0.02,0.03,0.04,0.04,0.05,0.05,0.06,0.08] 0.04398 6.105 PASS 7.268 12.4 FAIL 0 0.06 PASS PASS PASS_at_KS_(2/3) -unambiguous b-eosin NA NA NA NA all e9/l 100 {e9/l:100} e9/l 19437 12142 [0.04,0.08,0.11,0.14,0.17,0.2,0.25,0.32,0.44] [0.04,0.08,0.11,0.14,0.17,0.21,0.25,0.31,0.44] 0.009323 0.2745 FAIL 0.6328 0.2783 PASS 0 0.27 PASS PASS PASS_at_T_(2/3) -unambiguous l-basof NA NA NA NA all % 100 {%:100} % 19372 84273 [0,0,1,1,1,1,1,1,1] [0,0,1,1,1,1,1,1,1] 0.02437 7.833 PASS 9.941 22.52 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous p-ca-albk NA NA NA NA all mmol/l 99.95 {mmol/l:99.95,form:0.05,mmol:0} mmol/l 18846 165475 [2.29,2.34,2.37,2.4,2.43,2.46,2.5,2.54,2.61] [2.34,2.39,2.42,2.44,2.47,2.5,2.53,2.57,2.63] 0.1538 300 PASS -33.69 242.1 FAIL 0.04 0.21 PASS PASS PASS_at_KS_(2/3) -unambiguous oma-gluk NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 18525 53 [5.4,6.1,6.8,7.5,8.4,9.3,10.5,12.1,14.7] [5.22,5.74,6.1,6.4,6.7,7.12,8,8.6,11.12] 0.2829 3.519 PASS 5.572 6.066 FAIL 1.7 3.3 PASS PASS PASS_at_KS_(2/3) -unambiguous u-epit NA NA NA NA all e6/l 99.79 {e6/l:99.79,u/field:0.19,u:0.02} e6/l 18155 168750 [0,1,1,1.5,2,3,4,7,14] [0.2,1,1,1.9,2.1,3.2,5,8.1,16.9] 0.04272 25.71 PASS -6.438 9.907 FAIL 0.1 5.1 PASS PASS PASS_at_KS_(2/3) -unambiguous l-lymf NA NA NA NA all % 99.19 {%:99.19,e9/l:0.81} % 17952 287233 [10,15.82,19,23,27,31,35,40.7,49] [12.3,18,21.2,25,28,31,34,38,44] 0.0618 55.82 PASS 2.945 2.49 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) -unambiguous p-ck NA NA NA NA all u/l 100 {u/l:100} u/l 17899 260925 [46,62,75,90,108,133,170,242,409] [43,58,71,86,104,129,169,252,545] 0.03098 13.67 PASS -14.94 49.58 FAIL 4 150 PASS PASS PASS_at_KS_(2/3) -unambiguous l-baso NA NA NA NA all % 99.56 {%:99.56,e9/l:0.43,e/l:0} % 17874 929196 [0,0,0,0.5,1,1,1,1,1] [0,0,0,1,1,1,1,1,1] 0.06496 64.1 PASS -1.288 0.7036 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -unambiguous s-ph(akt) NA NA NA NA all ph 100 {ph:100} ph 16686 97114 [7.35,7.37,7.38,7.39,7.4,7.4,7.41,7.42,7.44] [7.34,7.36,7.38,7.39,7.4,7.41,7.42,7.43,7.45] 0.08186 82.73 PASS -6.569 10.29 FAIL 0 0.09 PASS PASS PASS_at_KS_(2/3) -unambiguous s-ca(7.4) NA NA NA NA all mmol/l 99.92 {mmol/l:99.92,nmol/l:0.08} mmol/l 16482 115493 [1.18,1.2,1.22,1.23,1.24,1.25,1.27,1.28,1.32] [1.12,1.16,1.19,1.21,1.22,1.24,1.25,1.27,1.31] 0.1685 300 PASS 42.01 300 FAIL 0.02 0.12 PASS PASS PASS_at_KS_(2/3) -unambiguous b-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 15770 19712 [-7.5,-5.5,-4.3,-3.4,-2.6,-2,-1.4,-0.9,-0.4] [0.5,1.1,1.7,2.3,3,3.9,5,6.6,9.2] 0.9739 300 FAIL -193.4 300 FAIL 5.6 6 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-d-25 NA NA NA NA all nmol/l 100 {nmol/l:100,mmol/l:0,nmol/:0} nmol/l 15496 380163 [46,55,63,70,76,83,91,102,119] [46,56,63,69,76,82,90,100,116] 0.01766 3.739 PASS 3.216 2.885 FAIL 0 51 PASS PASS PASS_at_KS_(2/3) -unambiguous f-calpro NA NA NA NA all ug/g 100 {ug/g:100,ug/l:0,<100:0} ug/g 13490 130628 [17,27,39,57,85,129,202,355,794.1] [14,23,35,54,81,128,213,394,911] 0.03985 16.58 PASS -2.582 2.007 FAIL 4 195 PASS PASS PASS_at_KS_(2/3) -unambiguous u-osmole NA NA NA NA all mosm/kgh2o 100 {mosm/kgh2o:100} mosm/kgh2o 13152 70655 [364,436,491,542,590,642,700,769,869] [347,415,470,522,570,625,687,762,869] 0.04625 20.33 PASS 7.362 12.72 FAIL 20 411 PASS PASS PASS_at_KS_(2/3) -unambiguous psa-v/psa NA NA NA NA all % 100 {%:100} % 13127 25356 [9.6,12.5,14.9,17.2,19.4,21.8,24.4,27.9,33] [8.4,11,13.3,15.6,17.8,20.2,23,26.6,32.4] 0.07657 43.82 PASS 11.36 29.1 FAIL 1.6 18.3 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-transf NA NA NA NA all g/l 100 {g/l:100} g/l 12905 144990 [1.8,2,2.1,2.25,2.4,2.56,2.7,2.98,3.2] [1.53,1.74,1.9,2.04,2.2,2.31,2.5,2.7,3] 0.1737 300 PASS 40.95 300 FAIL 0.2 1.2 PASS PASS PASS_at_KS_(2/3) -unambiguous s-cdt NA NA NA NA all % 99.96 {%:99.96,u/l:0.04,mg/l:0} % 12434 89543 [1.2,1.4,1.5,1.6,1.6,1.7,1.9,2.1,2.9] [0.8,1.1,1.3,1.4,1.5,1.6,1.7,1.9,2.3] 0.1676 267.7 PASS 30.97 203.7 FAIL 0.1 0.9 PASS PASS PASS_at_KS_(2/3) -unambiguous s-ca-iona NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 12323 382345 [1.13,1.17,1.19,1.21,1.23,1.24,1.26,1.28,1.32] [1.14,1.18,1.2,1.22,1.23,1.25,1.26,1.29,1.32] 0.03902 15.51 PASS -8.946 18.38 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) -unambiguous e-retik NA NA NA NA all % 99.98 {%:99.98,pg:0.01,e9/l:0} % 12082 121560 [0.8,1,1.2,1.3,1.5,1.7,2,2.3,3] [0.9,1.1,1.3,1.5,1.7,1.9,2.2,2.7,3.7] 0.09935 94.16 PASS -17.22 65.1 FAIL 0.2 1.5 PASS PASS PASS_at_KS_(2/3) -unambiguous p-fidd NA NA NA NA all mg/l 100 {mg/l:100,mikrog/ml:0,ug/l:0} mg/l 12060 116811 [0.29,0.3,0.4,0.5,0.6,0.8,1,1.6,3] [0.22,0.3,0.4,0.6,0.7,1,1.44,2.2,4.5] 0.09284 81.71 PASS -14.73 48.09 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) -unambiguous p-mg NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 11982 247648 [0.64,0.7,0.74,0.78,0.81,0.83,0.86,0.9,0.95] [0.64,0.7,0.74,0.77,0.8,0.83,0.85,0.89,0.94] 0.03404 11.21 PASS 2.421 1.81 FAIL 0.01 0.24 PASS PASS PASS_at_KS_(2/3) -unambiguous s-ca(akt) NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 11963 86215 [1.18,1.2,1.22,1.23,1.24,1.26,1.27,1.29,1.33] [1.11,1.15,1.18,1.2,1.22,1.23,1.25,1.27,1.31] 0.2276 300 PASS 45.35 300 FAIL 0.02 0.15 PASS PASS PASS_at_KS_(2/3) -unambiguous hdl/kol. NA NA NA NA all % 100 {%:100} % 11551 1944 [23,27,30,33,36,38,41,45,49] [21,24,28,31,33,36,40,44,49] 0.08936 11.28 PASS 6.189 9.153 FAIL 3 24 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-fe NA NA NA NA all umol/l 100 {umol/l:100,µmol/l:0,ug/l:0} umol/l 11441 141841 [5,7,8.3,10,11.9,13.9,16,18.6,22.5] [5,7,8.8,10.3,11.9,13.5,15.5,18,22] 0.0343 10.53 PASS 1.835 1.177 PASS 0 12.9 PASS PASS PASS_at_KS_(3/3) -unambiguous fs-ca-ion NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 10667 11278 [1.19,1.22,1.23,1.24,1.25,1.27,1.28,1.3,1.33] [1.16,1.2,1.21,1.23,1.24,1.26,1.27,1.3,1.35] 0.1108 58.37 PASS 1 0.4985 PASS 0.01 0.12 PASS PASS PASS_at_KS_(3/3) -unambiguous b-lymf NA NA NA NA all e9/l 98.42 {e9/l:98.42,%:1.58} e9/l 10416 275628 [0.97,1.2,1.41,1.6,1.81,2.02,2.29,2.66,3.315] [0.86,1.14,1.36,1.55,1.74,1.95,2.19,2.5,2.99] 0.04474 17.17 PASS 2.462 1.859 FAIL 0.07 1.59 PASS PASS PASS_at_KS_(2/3) -unambiguous b-erytroblastit NA NA NA NA all e9/l 100 {e9/l:100} e9/l 10388 151903 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.03874 12.39 PASS -16.36 59.39 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous u-prot-o NA NA NA NA all form 99.89 {form:99.89,mg/dl:0.11} form 9860 936 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,1] 0.04588 1.277 FAIL -3.484 3.287 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-t4-v NA NA NA NA all pmol/l 100 {pmol/l:100,pmol:0} pmol/l 9709 242498 [11,12,12,13,13,14,14,15,17] [11,12,12.9,13.1,14,14.5,15.1,16.01,17.5] 0.1618 213.2 PASS -15.97 56 FAIL 1 5.1 PASS PASS PASS_at_KS_(2/3) -unambiguous cp-gluk-hy NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 9537 6395 [5.3,6.5,7.5,8.5,9.5,10.6,11.9,13.4,15.6] [5.4,6.5,7.5,8.5,9.5,10.4,11.6,13.3,15.6] 0.02434 1.677 PASS -1.27 0.6904 PASS 0 7.8 PASS PASS PASS_at_KS_(3/3) -unambiguous nu-albkrea NA NA NA NA all mg/mmol 100 {mg/mmol:100} mg/mmol 9489 11439 [0.2,0.4,0.5,0.7,1,1.6,2.8,6,17.9] [0.3,0.5,0.7,0.9,1.3,2.1,3.8,8.2,27.3] 0.09281 38.61 PASS -6.811 11 FAIL 0.3 2.7 PASS PASS PASS_at_KS_(2/3) -unambiguous p-iga NA NA NA NA all g/l 100 {g/l:100} g/l 9343 52529 [1.06,1.4,1.63,1.9,2.1,2.4,2.74,3.2,4.16] [0.74,1.16,1.46,1.73,2.03,2.37,2.77,3.35,4.51] 0.08621 51.01 PASS -6.038 8.799 FAIL 0.07 2.46 PASS PASS PASS_at_KS_(2/3) -unambiguous p-b12-vit NA NA NA NA all pmol/l 100 {pmol/l:100} pmol/l 9340 37066 [194,243,285,326,371,423,487,577,720] [208,258,299,339,381,429,489,575,748] 0.03999 10.07 PASS -6.574 10.3 FAIL 10 351 PASS PASS PASS_at_KS_(2/3) -unambiguous p-crp-o NA NA NA NA all mg/l 100 {mg/l:100,u/l:0} mg/l 9102 29537 [7,9,13,18,24,33,45,65,98] [6,8,11,14,20,28,40,58,91] 0.07448 33.29 PASS 8.707 17.46 FAIL 4 39 PASS PASS PASS_at_KS_(2/3) -unambiguous cb-pco2 NA NA NA NA all kpa 100 {kpa:100} kpa 9039 107718 [4.2,4.7,5,5,5,5.3,5.7,6,6.7] [4.2,4.5,4.7,4.9,5.1,5.3,5.6,5.9,6.6] 0.1277 118.3 PASS 3.557 3.424 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-pi NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 8841 175027 [0.8,0.9,0.98,1.02,1.1,1.15,1.21,1.32,1.54] [0.78,0.9,0.99,1.07,1.16,1.25,1.38,1.56,1.85] 0.1446 153.3 PASS -25.19 135.2 FAIL 0.06 0.72 PASS PASS PASS_at_KS_(2/3) -unambiguous p-inr-vt NA NA NA NA all inr 100 {inr:100} inr 8487 1439 [1.3,1.8,2,2.1,2.3,2.4,2.6,2.9,3.3] [1,1,1,1,1.1,1.3,1.9,2.4,2.9] 0.5129 297.5 FAIL 23.72 115.7 FAIL 1.2 0.3 FAIL FAIL FAIL_at_MAD_(0/3) -unambiguous fp-ca NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 8418 53236 [2.23,2.29,2.31,2.35,2.38,2.4,2.43,2.49,2.55] [2.19,2.25,2.29,2.33,2.35,2.38,2.42,2.45,2.51] 0.1007 63.87 PASS 18.9 77.73 FAIL 0.03 0.24 PASS PASS PASS_at_KS_(2/3) -unambiguous s-pappa NA NA NA NA all mu/l 99.6 {mu/l:99.6,form:0.4} mu/l 8226 33727 [255,396,527,664,822,1000,1220,1550,2150] [274,426,564,707,859.8,1045,1280,1622,2232] 0.02933 4.649 PASS -2.662 2.11 FAIL 37.85 1286 PASS PASS PASS_at_KS_(2/3) -unambiguous p-t3-v NA NA NA NA all pmol/l 100 {pmol/l:100} pmol/l 8195 73828 [3.5,3.9,4.1,4.3,4.5,4.8,5,5.4,6.2] [3.5,3.8,4.1,4.3,4.6,4.8,5.1,5.5,6.2] 0.0259 4.005 PASS -0.7015 0.3161 PASS 0.1 1.8 PASS PASS PASS_at_KS_(3/3) -unambiguous s-iglck-v NA NA NA NA all mg/l 100 {mg/l:100} mg/l 7877 39042 [9.6,13.9,18.4,23.5,30,40.1,55.8,89.68,220] [7.8,12.1,16.2,21,27.1,35.7,50.3,81.2,172] 0.05025 14.1 PASS 3.239 2.92 FAIL 2.9 49.8 PASS PASS PASS_at_KS_(2/3) -unambiguous cb-hco3-st NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 7860 64090 [20.9,22.4,23.9,24.7,25.3,26.1,27.2,28.82,31.2] [21,22.4,23.3,24,25,25.6,26.3,27.5,29.5] 0.1021 63.24 PASS 12.93 37.18 FAIL 0.3 6 PASS PASS PASS_at_KS_(2/3) -unambiguous s-iglcl-v NA NA NA NA all mg/l 100 {mg/l:100} mg/l 7669 38822 [6.5,9.7,12.8,16,19.6,25,32.9,49.8,124] [6.1,9.2,12,15.1,19,23.9,31.8,48.6,118] 0.03176 5.319 PASS -2.897 2.424 FAIL 0.6 31.5 PASS PASS PASS_at_KS_(2/3) -unambiguous crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 7205 71 [6,9,12,16,22,30,42,58,90] [6,8,12,16,25,38,58,64,88] 0.1079 0.4437 FAIL -0.6403 0.2806 PASS 3 57 PASS PASS PASS_at_T_(2/3) -unambiguous p-ck-mbm NA NA NA NA all ug/l 100 {ug/l:100} ug/l 7160 69802 [1.3,1.7,2,2.3,2.6,3.1,3.8,4.9,7.81] [1.1,1.5,1.9,2.2,2.8,3.4,4.5,7.1,18] 0.0901 45.59 PASS -19.06 79.34 FAIL 0.2 4.2 PASS PASS PASS_at_KS_(2/3) -unambiguous s-testo NA NA NA NA all nmol/l 99.93 {nmol/l:99.93,pmol/l:0.03,form:0.03} nmol/l 6954 77552 [2.9,6.5,8.1,9.5,11,13,15.7,19,23.87] [1.5,6.6,9,11,12.8,14.7,17,19.8,24.4] 0.09349 48.27 PASS -2.242 1.603 FAIL 1.8 15.6 PASS PASS PASS_at_KS_(2/3) -unambiguous p-pi NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 6629 179614 [0.69,0.81,0.9,0.98,1.05,1.14,1.23,1.37,1.6] [0.74,0.87,0.97,1.05,1.13,1.23,1.35,1.51,1.79] 0.105 61.07 PASS -18.9 77.09 FAIL 0.08 0.72 PASS PASS PASS_at_KS_(2/3) -unambiguous u-osmest NA NA NA NA all mosm/kgh2o 100 {mosm/kgh2o:100,mo/kg/h2o:0,mo/kgh2o:0} mosm/kgh2o 6305 89312 [291,363,418,465,515,573,634.2,703,803.4] [262,327,378,425,472,523,584,656,768] 0.08677 38.3 PASS 14.79 48.04 FAIL 43 390 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-krea NA NA NA NA all umol/l 100 {umol/l:100} umol/l 6255 759945 [62,70,77,87,96,103,110,121,146] [56,62,68,73,78,84,92,105,140] 0.246 300 PASS 6.138 9.052 FAIL 18 45 PASS PASS PASS_at_KS_(2/3) -unambiguous p-tt NA NA NA NA all % 100 {%:100,form:0} % 6023 465481 [41,57,67,77,86,94,102,112,126] [50,65,74,82,88,95,102,110,121] 0.08411 36.31 PASS -5.824 8.218 FAIL 2 54 PASS PASS PASS_at_KS_(2/3) -unambiguous p-ld NA NA NA NA all u/l 100 {u/l:100} u/l 5895 215599 [163,180,193,207,221,238,258,289,357] [166,184,198,212,226,244,269,310,413] 0.04455 9.609 PASS -10.44 24.61 FAIL 5 126 PASS PASS PASS_at_KS_(2/3) -unambiguous p-bil-kj NA NA NA NA all umol/l 100 {umol/l:100} umol/l 5806 124636 [2,3,3,4,5,6,7,9,15] [3,3,4,4,5,6,8,11,26] 0.06147 17.94 PASS -9.79 21.76 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) -unambiguous b-leukosyytit NA NA NA NA all e9/l 100 {e9/l:100,1:0} e9/l 5646 370214 [4.8,6,7,8.3,8.7,9.2,9.9,10.8,13] [4.4,5.1,5.7,6.2,6.8,7.4,8.2,9.3,11.3] 0.3046 300 FAIL 21.83 100.9 FAIL 1.9 4.8 PASS PASS PASS_at_MAD_(1/3) -unambiguous p-urea NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 5615 168276 [4.1,5.4,6.8,8.5,10.5,12.7,15.3,18.8,24.7] [4.2,5.5,6.9,8.7,10.9,13.4,16.4,20,25.3] 0.0386 6.745 PASS -3.726 3.708 FAIL 0.4 16.2 PASS PASS PASS_at_KS_(2/3) -unambiguous crp-pika NA NA NA NA all mg/l 100 {mg/l:100} mg/l 5400 3081 [6,8,11,16,23,33,47,69,103] [7,9,13,18,25,34,47,69,106] 0.05675 5.211 PASS -1.678 1.029 PASS 2 51 PASS PASS PASS_at_KS_(3/3) -unambiguous -trfesat NA NA NA NA all % 100 {%:100,g/l:0} % 5367 49060 [8,12,16,19,22,26,29,34,41] [9.2,13.8,17,20,23,26.26,30,34.7,42] 0.05622 13.01 PASS -6.034 8.775 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) -unambiguous p-amylp NA NA NA NA all u/l 100 {u/l:100} u/l 5279 91217 [13,18,21,24,28,31,35,43,60] [14,20,23,26,30,34,40,51,85] 0.07912 26.89 PASS -8.148 15.35 FAIL 2 30 PASS PASS PASS_at_KS_(2/3) -unambiguous s-prot NA NA NA NA all g/l 100 {g/l:100} g/l 5242 87590 [59,62.5,65,67,68.4,70,71.5,73.9,77] [57,61,63,65,67,69,70.6,73,76.2] 0.09527 38.8 PASS 10.78 26.12 FAIL 1.4 15 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-urea NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 5232 124584 [5,6.6,8,9.7,11.4,13.6,16.1,19.88,25] [5,6.9,8.9,11.3,13.9,16.5,19.2,22.4,27.3] 0.1204 63.19 PASS -14.53 46.26 FAIL 2.5 18.9 PASS PASS PASS_at_KS_(2/3) -unambiguous 14272 NA NA NA NA all e9/l 100 {e9/l:100} e9/l 5212 79059 [1.5,2,2.5,2.9,3.4,3.9,4.7,5.8,8.1] [1.06,1.72,2.24,2.72,3.24,3.83,4.61,5.76,8.02] 0.07552 23.97 PASS 3.429 3.214 FAIL 0.16 4.38 PASS PASS PASS_at_KS_(2/3) -unambiguous pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava NA NA NA NA all ml/min/173m2 99.81 {ml/min/173m2:99.81,1:0.19} ml/min/173m2 5151 202854 [30,38.2,44,49,53,57,62,69,82] [34,48,59,68,75,82,87,93,101] 0.3791 300 FAIL -57.84 300 FAIL 22 51 PASS PASS PASS_at_MAD_(1/3) -unambiguous -nt NA NA NA NA all mm 100 {mm:100} mm 5019 11772 [0.8,0.9,1,1.1,1.2,1.2,1.3,1.5,1.7] [0.9,1,1.1,1.2,1.27,1.34,1.49,1.6,1.8] 0.1319 53.08 PASS -11.64 30.4 FAIL 0.07 0.75 PASS PASS PASS_at_KS_(2/3) -unambiguous s-hcgbv/d NA NA NA NA all ug/l 100 {ug/l:100} ug/l 4990 14513 [22.4,30.3,37.1,44.7,52.7,62.64,74.9,91.5,120] [22.6,31.2,38.7,46.3,55,64.9,77.8,94.1,125.5] 0.02665 1.997 PASS -3.451 3.251 FAIL 2.3 70.5 PASS PASS PASS_at_KS_(2/3) -unambiguous s-mkomp-1 NA NA NA NA all g/l 100 {g/l:100} g/l 4885 29826 [0,0,0,1.1,2.5,4.2,7.1,11.4,19.1] [0,0,0,0,0,0.3,1.8,5.1,11.2] 0.2583 246.7 PASS 21.27 96.01 FAIL 2.5 0 FAIL PASS PASS_at_KS_(1/3) -unambiguous s-li NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 4651 33555 [0.4,0.5,0.58,0.6,0.7,0.72,0.8,0.9,1] [0.4,0.5,0.54,0.6,0.69,0.7,0.8,0.9,1] 0.02917 2.728 PASS 1.317 0.726 PASS 0.01 0.51 PASS PASS PASS_at_KS_(3/3) -unambiguous p-ca-iona NA NA NA NA all mmol/l 100 {mmol/l:100,%:0,kpa:0} mmol/l 4581 404577 [1.1,1.14,1.16,1.17,1.19,1.21,1.23,1.25,1.29] [1.04,1.08,1.11,1.13,1.15,1.17,1.19,1.21,1.25] 0.2532 255.7 PASS 33.65 230.1 FAIL 0.04 0.15 PASS PASS PASS_at_KS_(2/3) -unambiguous s-valpr NA NA NA NA all umol/l 99.9 {umol/l:99.9,%:0.1} umol/l 4307 31514 [197,257,299.8,340.4,382,423,465,517,588.4] [221,285,332,372,409,446,487,533,601] 0.0818 21.78 PASS -10.07 22.95 FAIL 27 300 PASS PASS PASS_at_KS_(2/3) -unambiguous p-ca-ion. NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 4300 356672 [1.11,1.14,1.16,1.18,1.2,1.21,1.23,1.26,1.29] [1.03,1.08,1.11,1.13,1.16,1.18,1.2,1.22,1.25] 0.251 235.6 PASS 41.48 300 FAIL 0.04 0.18 PASS PASS PASS_at_KS_(2/3) -unambiguous u-albkrea NA NA NA NA all mg/mmol 99.24 {mg/mmol:99.24,mg/mmol/l:0.76} mg/mmol 4132 10589 [0.4,0.7,1.1,1.9,3.4,4.9,7.7,14.4,36.99] [0.3,0.4,0.6,0.7,1,1.3,1.8,3,9.12] 0.343 300 FAIL 9.367 20 FAIL 2.4 1.8 FAIL FAIL FAIL_at_MAD_(0/3) -unambiguous fs-trigly NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,form:0} mmol/l 3980 258906 [0.6,0.72,0.83,0.93,1.06,1.2,1.39,1.64,2.11] [0.7,0.84,0.98,1.11,1.27,1.45,1.68,2,2.57] 0.1417 68.43 PASS -20.61 89.3 FAIL 0.21 1.26 PASS PASS PASS_at_KS_(2/3) -unambiguous b-crp-vt NA NA NA NA all mg/l 99.98 {mg/l:99.98,crp:0.02,g/l:0.01} mg/l 3965 16204 [2.64,5.7,8,12,18,26,40,57,89] [6,8,11,14,19,27,38,54,88] 0.1545 66.18 PASS -1.14 0.5947 PASS 1 36 PASS PASS PASS_at_KS_(3/3) -unambiguous sy-leuk NA NA NA NA all e6/l 99.75 {e6/l:99.75,e9/l:0.25} e6/l 3964 11394 [117.3,262.6,500,1123,2804,5405,1.011e+04,1.868e+04,3.801e+04] [100.3,225,510,1400,3320,6503,1.12e+04,1.91e+04,3.72e+04] 0.03253 2.413 PASS -0.3365 0.1328 PASS 516 9654 PASS PASS PASS_at_KS_(3/3) -unambiguous b-ghba1cp NA NA NA NA all % 100 {%:100} % 3927 888 [6,6.3,6.6,6.9,7.2,7.4,7.8,8.2,8.8] [5.9,6.1,6.5,6.8,7.1,7.52,7.9,8.3,9.4] 0.06144 2.095 PASS -3.643 3.545 FAIL 0.1 2.7 PASS PASS PASS_at_KS_(2/3) -unambiguous fs-kol-hdl NA NA NA NA all mmol/l 100 {mmol/l:100,form:0,mmol/:0} mmol/l 3887 254480 [1.03,1.16,1.25,1.34,1.43,1.53,1.64,1.77,1.96] [1,1.1,1.2,1.3,1.4,1.5,1.6,1.74,2] 0.07186 16.91 PASS 1.839 1.18 PASS 0.03 0.75 PASS PASS PASS_at_KS_(3/3) -unambiguous fs-kol NA NA NA NA all mmol/l 100 {mmol/l:100,mmol/:0,form:0} mmol/l 3794 255206 [3.5,4,4.3,4.6,4.9,5.2,5.5,5.8,6.4] [3.7,4.2,4.5,4.8,5,5.3,5.6,5.9,6.4] 0.06004 11.43 PASS -6.382 9.711 FAIL 0.1 2.1 PASS PASS PASS_at_KS_(2/3) -unambiguous fs-kol-ldl NA NA NA NA all mmol/l 100 {mmol/l:100,form:0,mmol/:0} mmol/l 3772 255211 [1.7,2.2,2.5,2.8,3.1,3.4,3.671,3.996,4.5] [1.9,2.3,2.6,2.9,3.1,3.4,3.7,4,4.5] 0.04679 6.785 PASS -3.555 3.417 FAIL 0 2.1 PASS PASS PASS_at_KS_(2/3) -unambiguous p-bnp NA NA NA NA all ng/l 99.98 {ng/l:99.98,ng/ml:0.02} ng/l 3770 88507 [42,72,109,144,194,258,352,511.4,899.1] [20,36,58,88,131,195,292,462,895] 0.1578 78.37 PASS 2.555 1.973 FAIL 63 312 PASS PASS PASS_at_KS_(2/3) -unambiguous p-igg NA NA NA NA all g/l 100 {g/l:100} g/l 3736 73214 [6,7.4,8.6,9.5,10.4,11.4,12.6,14.5,17.95] [5,6.6,7.7,8.7,9.6,10.6,11.7,13.3,16.6] 0.1016 31.71 PASS 8.605 16.97 FAIL 0.8 7.8 PASS PASS PASS_at_KS_(2/3) -unambiguous cp-glukoosi,ihopistosn,vieritestihoitoyksikössä NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 3716 1349 [5.3,6.2,7.1,8,9.1,10.3,11.9,13.9,16.9] [5.2,6.2,7,7.9,8.9,10.2,11.9,14.2,17.2] 0.0217 0.1369 FAIL 0.5007 0.21 PASS 0.2 8.4 PASS PASS PASS_at_T_(2/3) -unambiguous ab-emäsylimäärä NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 3701 9136 [-9.2,-6.4,-4.8,-3.7,-2.8,-2.1,-1.6,-1.1,-0.5] [-0.8,0.4,1.1,1.7,2.4,3.3,4.5,6.1,8.9] 0.8699 300 FAIL -89.69 300 FAIL 5.2 6 PASS PASS PASS_at_MAD_(1/3) -unambiguous u-sg NA NA NA NA all kg/l 100 {kg/l:100} kg/l 3697 130 [1.005,1.005,1.01,1.01,1.015,1.015,1.02,1.02,1.025] [1.01,1.01,1.01,1.015,1.015,1.017,1.02,1.02,1.025] 0.182 3.385 PASS 2 1.341 FAIL 0 0.015 PASS PASS PASS_at_KS_(2/3) -unambiguous vb-emäsylimäärä NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 3632 12064 [-9.1,-6.3,-4.6,-3.5,-2.6,-2,-1.3,-0.8,-0.3] [-2.6,-0.2,0.7,1.3,2.1,2.8,3.6,4.7,6.7] 0.7533 300 FAIL -77.35 300 FAIL 4.7 5.7 PASS PASS PASS_at_MAD_(1/3) -unambiguous b-ph NA NA NA NA all ph 100 {ph:100} ph 3554 35592 [7.31,7.34,7.36,7.38,7.39,7.41,7.43,7.44,7.46] [7.35,7.38,7.4,7.41,7.42,7.43,7.44,7.46,7.48] 0.2071 121.3 PASS -23.05 109.9 FAIL 0.03 0.09 PASS PASS PASS_at_KS_(2/3) -unambiguous vb-pco2 NA NA NA NA all kpa 100 {kpa:100} kpa 3514 187248 [4.523,5,5.2,5.4,5.7,5.9,6.2,6.5,7.1] [4.7,5.1,5.3,5.6,5.8,6,6.3,6.6,7.1] 0.06585 12.72 PASS -5.987 8.629 FAIL 0.1 1.8 PASS PASS PASS_at_KS_(2/3) -unambiguous vb-po2 NA NA NA NA all kpa 100 {kpa:100} kpa 3497 134116 [3.2,3.8,4.386,4.8,5.2,5.6,6.2,7.4,10] [2.8,3.4,3.9,4.3,4.7,5.1,5.7,6.5,8.3] 0.1189 41.73 PASS 13.92 42.21 FAIL 0.5 3.6 PASS PASS PASS_at_KS_(2/3) -unambiguous mb-ph NA NA NA NA all ph 100 {ph:100} ph 3444 279 [7.29,7.32,7.34,7.36,7.373,7.39,7.401,7.419,7.435] [7.318,7.34,7.36,7.37,7.38,7.4,7.41,7.42,7.44] 0.13 3.535 PASS -3.9 3.936 FAIL 0.007 0.09 PASS PASS PASS_at_KS_(2/3) -unambiguous b-crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 3350 2366 [5,7,9,12,17,24,35,54,87] [6,8,9,13,18,25,35,55,90] 0.09378 10.34 PASS -1.146 0.5987 PASS 1 33 PASS PASS PASS_at_KS_(3/3) -unambiguous p-gluk-vt NA NA NA NA all mmol/l 98.08 {mmol/l:98.08,1:1.92} mmol/l 3313 2048 [5,5.7,6.4,7.2,8.2,9.5,11,12.8,15.9] [4.5,4.7,4.9,5.1,5.4,5.8,6.5,7.56,9.63] 0.3966 177.7 FAIL 20.93 92.33 FAIL 2.8 2.4 FAIL FAIL FAIL_at_MAD_(0/3) -unambiguous ab-po2 NA NA NA NA all kpa 99.99 {kpa:99.99,mmol/l:0,%:0} kpa 3269 391556 [6.7,7.7,8.2,8.8,9.4,10,10.9,12,14.2] [8.1,9.1,9.9,10.6,11.4,12.4,13.8,16.2,21.5] 0.2746 215.8 PASS -43.56 300 FAIL 2 7.2 PASS PASS PASS_at_KS_(2/3) -unambiguous ab-pco2 NA NA NA NA all kpa 99.99 {kpa:99.99,mmol/l:0,%:0} kpa 3239 392179 [3.9,4.3,4.6,4.8,5,5.3,5.7,6.3,7.4] [4.1,4.5,4.7,5,5.2,5.4,5.6,5.9,6.5] 0.07603 15.87 PASS 3.66 3.592 FAIL 0.2 1.8 PASS PASS PASS_at_KS_(2/3) -unambiguous li-leuk NA NA NA NA all e6/l 100 {e6/l:100} e6/l 3193 10896 [0,0,1,1,2,3,4,10,65.6] [0,0,1,1,2,3,5,11,58] 0.03269 2 PASS -2.785 2.27 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) -unambiguous li-eryt NA NA NA NA all e6/l 100 {e6/l:100} e6/l 3189 11741 [0,0,0,1,3,10,43.6,199.4,1766] [0,0,1,2,4,12,45,232,2250] 0.02869 1.501 PASS 0.6696 0.2983 PASS 1 12 PASS PASS PASS_at_KS_(3/3) -unambiguous p-crp-vt NA NA NA NA all mg/l 100 {mg/l:100} mg/l 3141 6868 [5,6.9,9,14,20,28,40,59,91] [5,7,10,14,20,28,40,61,94] 0.0366 2.22 PASS -0.7086 0.3201 PASS 0 42 PASS PASS PASS_at_KS_(3/3) -unambiguous b-crp-o NA NA NA NA all mg/l 100 {mg/l:100} mg/l 3125 1516 [7,10,14,19,26,35,47,67,98] [6,8,11,15,21,28,40,59,90] 0.08443 6.057 PASS 3.708 3.672 FAIL 5 42 PASS PASS PASS_at_KS_(2/3) -unambiguous s-psa NA NA NA NA all ug/l 99.99 {ug/l:99.99,mg/l:0.01,%:0} ug/l 3123 88424 [0.37,0.57,0.73,0.95,1.3,1.7,2.6,4.2,7.5] [0.39,0.57,0.75,0.97,1.24,1.63,2.26,3.3,5.4] 0.05689 8.201 PASS 2.235 1.593 FAIL 0.06 2.22 PASS PASS PASS_at_KS_(2/3) -unambiguous p-apcres. NA NA NA NA all form 100 {form:100} form 3090 64 [2.5,2.7,2.8,2.9,2.9,3,3,3.1,3.2] [2.7,2.8,2.8,2.8,2.9,2.9,2.9,3,3] 0.1794 1.512 PASS -0.7183 0.3234 PASS 0 0.3 PASS PASS PASS_at_KS_(3/3) -unambiguous cp-gluk NA NA NA NA all mmol/l 99.85 {mmol/l:99.85,mmol/:0.15} mmol/l 3068 1987 [5.9,6.8,7.8,9,10.25,11.9,13.89,15.96,19.2] [5.1,6.3,7.7,9.1,10.6,12.7,14.4,16.4,19.3] 0.06829 4.613 PASS 0.1958 0.07327 PASS 0.35 12.6 PASS PASS PASS_at_KS_(3/3) -unambiguous lieriöt NA NA NA NA all e6/l 100 {e6/l:100} e6/l 2938 23942 [0,0,0,0,0,0,0.1,0.3,0.9] [0,0,0,0,0,0.1,0.3,0.42,1] 0.1694 65.4 PASS -0.1685 0.06237 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -unambiguous crp(päiv.hoitaja) NA NA NA NA all mg/l 99.18 {mg/l:99.18,g/l:0.27,mg/:0.27} mg/l 2927 361 [6,8,10,14,19,27,39.2,56,91.4] [6,7,9,12,15,21,28,47,71] 0.09255 2.122 PASS 3.49 3.279 FAIL 4 27 PASS PASS PASS_at_KS_(2/3) -unambiguous u-happamuusaste(kval) NA NA NA NA all form 100 {form:100} form 2872 32 [5,5.5,5.5,5.5,6,6,6,6.5,7] [5,5.5,5.5,5.5,5.5,6,6,6.5,7] 0.09706 0.04638 FAIL 0.1506 0.05489 PASS 0.5 1.5 PASS PASS PASS_at_T_(2/3) -unambiguous p-cea NA NA NA NA all ug/l 100 {ug/l:100} ug/l 2813 49240 [1.2,1.7,2,2.2,3,3.1,4,5,6.9] [1.6,2.1,2.4,2.8,3.4,4.3,5.9,10,33] 0.181 76.06 PASS -8.645 17.17 FAIL 0.4 4.5 PASS PASS PASS_at_KS_(2/3) -unambiguous happamuusaste,laskimoveri NA NA NA NA all ph 100 {ph:100} ph 2733 819 [7.32,7.35,7.36,7.38,7.39,7.4,7.41,7.43,7.45] [7.3,7.34,7.36,7.37,7.39,7.4,7.41,7.43,7.45] 0.05006 1.088 FAIL 2.574 1.993 FAIL 0 0.09 PASS PASS PASS_at_MAD_(1/3) -unambiguous tffesat NA NA NA NA all % 100 {%:100} % 2726 900 [7.6,10.8,13.7,16.6,19.4,22.3,25.9,30.3,37] [8.19,11.68,15,18.1,21.2,24.34,27.63,31.84,38.41] 0.07481 3.017 PASS -2.62 2.051 FAIL 1.8 23.7 PASS PASS PASS_at_KS_(2/3) -unambiguous u-lieriöt NA NA NA NA all e6/l 99.54 {e6/l:99.54,u/field:0.46,u/ul:0} e6/l 2719 59778 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0.14,0.42,1] 0.3489 282.7 FAIL -27.96 168.5 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-gamma NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2700 28537 [5.6,6.68,7.5,8.2,9.2,10.1,11.2,12.7,15.9] [4.5,6.3,7.5,8.5,9.5,10.5,11.7,13.5,17.3] 0.06216 8.004 PASS -2.571 1.992 FAIL 0.3 8.1 PASS PASS PASS_at_KS_(2/3) -unambiguous erytroblastit NA NA NA NA all e9/l 100 {e9/l:100} e9/l 2691 141098 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.04834 5.075 PASS -6.487 9.984 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous ab-hco3-st NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 2612 255830 [20,22,23,24,25,26,27,28,30] [21,22,23,24,25,25,26,27,29] 0.05808 7.299 PASS 3.353 3.091 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) -unambiguous p-kysc NA NA NA NA all mg/l 100 {mg/l:100} mg/l 2572 52852 [0.76,0.9,1.013,1.13,1.27,1.44,1.64,1.91,2.359] [0.85,0.96,1.08,1.23,1.42,1.64,1.93,2.35,3.15] 0.1083 24.79 PASS -18.23 69.86 FAIL 0.15 1.41 PASS PASS PASS_at_KS_(2/3) -unambiguous s-alfa-2 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2555 27644 [5.7,6.2,6.5,6.8,7.1,7.5,7.9,8.4,9.4] [5.5,5.9,6.3,6.7,7,7.4,7.8,8.4,9.37] 0.06415 8.084 PASS 4.402 4.955 FAIL 0.1 3 PASS PASS PASS_at_KS_(2/3) -unambiguous s-alfa-1 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2552 27708 [1.5,1.7,1.9,2.1,2.4,2.6,2.9,3.2,3.8] [2.2,2.4,2.6,2.7,2.9,3,3.2,3.5,4.1] 0.3316 228.8 FAIL -23.7 113 FAIL 0.5 1.2 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-album NA NA NA NA all g/l 100 {g/l:100} g/l 2547 25430 [31.4,35,37.3,39,40.3,41.5,43,44.5,46.3] [31,34.3,36.2,37.6,38.7,39.8,40.9,42.1,43.7] 0.1625 53.15 PASS 12.94 36.55 FAIL 1.6 9 PASS PASS PASS_at_KS_(2/3) -unambiguous s-beta-2 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2541 27334 [2.1,2.4,2.6,2.8,3,3.3,3.6,4.1,4.8] [2.3,2.6,2.8,3.1,3.4,3.6,4,4.5,5.5] 0.1285 33.22 PASS -15.11 49.61 FAIL 0.4 2.1 PASS PASS PASS_at_KS_(2/3) -unambiguous s-beta-1 NA NA NA NA all g/l 99.96 {g/l:99.96,%:0.04} g/l 2540 27387 [3.4,3.7,3.9,4,4.2,4.4,4.6,4.8,5.2] [3.3,3.5,3.7,3.9,4,4.2,4.4,4.6,5] 0.1268 32.31 PASS 5.524 7.448 FAIL 0.2 1.2 PASS PASS PASS_at_KS_(2/3) -unambiguous s-norklot NA NA NA NA all nmol/l 99.98 {nmol/l:99.98,umol/l:0.02} nmol/l 2538 22343 [321,458.4,572,704.8,826,970,1111,1326,1687] [344,489,614,734,863,1000,1166,1390,1713] 0.03663 2.367 PASS -2.018 1.36 FAIL 37 1041 PASS PASS PASS_at_KS_(2/3) -unambiguous p-korsol NA NA NA NA all nmol/l 100 {nmol/l:100,pmol/l:0} nmol/l 2505 51414 [185,261,314,350,394,434,482,539,637.6] [84,204.6,266,312,352,391,434,486,567] 0.1124 26 PASS 13.05 37.1 FAIL 42 330 PASS PASS PASS_at_KS_(2/3) -unambiguous s-igg4 NA NA NA NA all g/l 99.98 {g/l:99.98,form:0.02} g/l 2503 9778 [0.119,0.2164,0.3326,0.4408,0.58,0.7958,1.1,1.69,2.93] [0.11,0.209,0.31,0.439,0.59,0.787,1.06,1.56,2.623] 0.02386 0.6934 FAIL 4.122 4.413 FAIL 0.01 1.209 PASS PASS PASS_at_MAD_(1/3) -unambiguous p-igm NA NA NA NA all g/l 100 {g/l:100} g/l 2460 38211 [0.4,0.6,0.76,0.94,1,1.2,1.58,2.29,5.028] [0.26,0.4,0.56,0.7,0.88,1.09,1.35,1.8,3.34] 0.1456 42.47 PASS 2.462 1.858 FAIL 0.12 1.44 PASS PASS PASS_at_KS_(2/3) -unambiguous l-nlt NA NA NA NA all % 100 {%:100} % 2422 7143 [16,28,38,45,52,59,65,72,81] [25,38,46,53,59,65,70,76,83] 0.1145 20.38 PASS -11.13 27.64 FAIL 7 45 PASS PASS PASS_at_KS_(2/3) -unambiguous s-iga NA NA NA NA all g/l 100 {g/l:100,mg/l:0} g/l 2410 35623 [0.99,1.32,1.55,1.8,2.05,2.33,2.69,3.27,4.331] [1.05,1.34,1.56,1.77,1.99,2.23,2.53,2.93,3.66] 0.05965 6.697 PASS 6.321 9.512 FAIL 0.06 1.8 PASS PASS PASS_at_KS_(2/3) -unambiguous s-van NA NA NA NA all mg/l 100 {mg/l:100} mg/l 2406 34483 [7.3,9,10.5,11.7,13,14.1,15.6,17.8,21.4] [6.9,8.6,10,11.1,12.4,13.7,15,17,19.8] 0.04717 4.062 PASS 5.626 7.692 FAIL 0.6 10.2 PASS PASS PASS_at_KS_(2/3) -unambiguous s-cea NA NA NA NA all ug/l 100 {ug/l:100,<5:0} ug/l 2353 87770 [1.1,1.3,1.6,1.9,2.2,2.7,3.5,4.66,7.3] [1.1,1.4,1.7,2,2.4,3.1,4.1,6.3,17.4] 0.07905 12.18 PASS -16.63 61.01 FAIL 0.2 3.3 PASS PASS PASS_at_KS_(2/3) -unambiguous zb-be NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 2350 2420 [-6.1,-4.1,-3.2,-2.6,-2,-1.5,-1.2,-0.7,-0.4] [0.4,0.8,1.2,1.7,2.2,2.9,3.8,4.9,7.4] 1 300 FAIL -70.65 300 FAIL 4.2 4.2 PASS PASS PASS_at_MAD_(1/3) -unambiguous p-crp-hy NA NA NA NA all mg/l 100 {mg/l:100} mg/l 2326 6913 [7,10,13,18,24,33,46,66,101.5] [6,8,11,15,21,29,41,59,91] 0.06881 6.886 PASS 4.653 5.47 FAIL 3 42 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-trfesat NA NA NA NA all % 100 {%:100} % 2313 88543 [8,11,14,17,20,24,28,34,41.8] [9,13,16,19,22,25,28,33,40] 0.08891 15.23 PASS -2.173 1.525 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) -unambiguous s-k NA NA NA NA all mmol/l 100 {mmol/l:100,mml/l:0} mmol/l 2255 138249 [3.8,3.9,4.1,4.1,4.2,4.3,4.3,4.4,4.6] [3.8,4,4.1,4.2,4.2,4.3,4.4,4.5,4.6] 0.05636 5.841 PASS -4.525 5.198 FAIL 0 0.6 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-laktaat NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 2205 299118 [0.9,1,1.1,1.2,1.4,1.6,1.8,2.2,3] [0.5,0.7,0.8,0.9,1,1.2,1.4,1.7,2.3] 0.2916 164.6 PASS 13.23 37.77 FAIL 0.4 1.2 PASS PASS PASS_at_KS_(2/3) -unambiguous pf-eryt NA NA NA NA all e6/l 99.86 {e6/l:99.86,e9/l:0.14} e6/l 2155 3474 [300,700,1121,1900,3200,5600,1.11e+04,2.434e+04,7.96e+04] [300,800,1740,3300,6000,1.04e+04,2e+04,4.594e+04,1.3e+05] 0.1203 16.49 PASS -1.241 0.6679 PASS 2800 1.694e+04 PASS PASS PASS_at_KS_(3/3) -unambiguous vb-happamuusaste NA NA NA NA all 1 100 {1:100} 1 2150 59 [7.31,7.34,7.36,7.37,7.388,7.4,7.41,7.43,7.45] [7.288,7.35,7.38,7.39,7.4,7.41,7.426,7.434,7.452] 0.1619 1.058 FAIL -1.075 0.5427 PASS 0.012 0.09 PASS PASS PASS_at_T_(2/3) -unambiguous pf-leuk NA NA NA NA all e6/l 99.02 {e6/l:99.02,e9/l:0.98} e6/l 2145 4958 [143.8,262.8,405.6,585,804,1129,1638,2613,4980] [123.7,230,367,548.8,780.5,1120,1674,2547,4805] 0.0346 1.268 FAIL 1.1 0.5666 PASS 23.5 1804 PASS PASS PASS_at_T_(2/3) -unambiguous pt-gfre-md NA NA NA NA all ml/min/173m2 99.94 {ml/min/173m2:99.94,form:0.06} ml/min/173m2 2116 26941 [34,44,51,56,60,69,77,85,96] [34,45,52,57,61,72,81,90,101] 0.0529 4.485 PASS -4.037 4.253 FAIL 1 54 PASS PASS PASS_at_KS_(2/3) -unambiguous u-lieriö NA NA NA NA all e6/l 100 {e6/l:100} e6/l 2104 5122 [0,0,0,0,0.11,0.11,0.23,0.34,0.81] [0,0,0,0,0,0,0,0.1,1] 0.3671 178.8 FAIL -2.826 2.326 FAIL 0.11 0 FAIL FAIL FAIL_at_MAD_(0/3) -unambiguous l-myel NA NA NA NA all % 100 {%:100} % 2051 13362 [0,0,0,0,0,1,1,2,4] [0,0,0,0,1,1,1,2,4] 0.06706 6.669 PASS -0.8266 0.3888 PASS 1 3 PASS PASS PASS_at_KS_(3/3) -unambiguous s-tfr NA NA NA NA all mg/l 99.99 {mg/l:99.99,mg:0.01} mg/l 2018 75736 [1.8,2.2,2.6,3.1,3.6,4.2,5.1,6.3,8.1] [1,1.2,1.5,1.9,2.4,2.8,3.3,4.1,5.6] 0.2886 144.8 PASS 20.34 83.32 FAIL 1.2 3.3 PASS PASS PASS_at_KS_(2/3) -unambiguous s-trigly NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,mmol:0} mmol/l 1993 30438 [0.62,0.76,0.87,0.99,1.11,1.27,1.484,1.736,2.19] [0.7,0.8,0.95,1.1,1.2,1.4,1.6,1.9,2.5] 0.09324 13.88 PASS -8.974 18.25 FAIL 0.09 1.2 PASS PASS PASS_at_KS_(2/3) -unambiguous b-tacro NA NA NA NA all ug/l 100 {ug/l:100} ug/l 1993 43350 [4.3,5.1,6,6.8,7.5,8.5,9.8,11,13] [4.5,5.3,6,6.6,7.2,8,8.8,9.9,11.7] 0.09282 14.01 PASS 5.29 6.871 FAIL 0.3 5.4 PASS PASS PASS_at_KS_(2/3) -unambiguous s-igg1 NA NA NA NA all g/l 99.96 {g/l:99.96,form:0.04} g/l 1991 4826 [4.27,4.96,5.5,5.97,6.55,7.08,7.72,8.66,10.1] [3.7,4.5,5.08,5.6,6.14,6.7,7.31,8.2,9.73] 0.08725 9.061 PASS 5.43 7.219 FAIL 0.41 4.32 PASS PASS PASS_at_KS_(2/3) -unambiguous s-igg2 NA NA NA NA all g/l 99.96 {g/l:99.96,form:0.04} g/l 1988 4814 [1.42,1.854,2.14,2.41,2.67,3.01,3.35,3.9,4.64] [1.27,1.72,2.08,2.39,2.69,3.06,3.43,4,4.89] 0.04364 2.043 PASS -0.7587 0.3487 PASS 0.02 2.61 PASS PASS PASS_at_KS_(3/3) -unambiguous s-kol-hdl NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,mmol/mol:0} mmol/l 1987 33871 [0.99,1.12,1.22,1.31,1.39,1.49,1.6,1.74,1.94] [1,1.1,1.2,1.3,1.4,1.5,1.6,1.79,2] 0.03836 2.11 PASS -4.253 4.66 FAIL 0.01 0.78 PASS PASS PASS_at_KS_(2/3) -unambiguous l-nst NA NA NA NA all % 100 {%:100} % 1987 7096 [0,0,0,0,1,1,1,2,5] [0,0,0,0,1,1,1,2,5] 0.009132 0.0002801 FAIL 0.05908 0.02096 PASS 0 3 PASS PASS PASS_at_T_(2/3) -unambiguous s-dnanab. NA NA NA NA all kiu/l 100 {kiu/l:100} kiu/l 1975 1572 [0.6,0.8,0.9,1.1,1.3,1.7,2.3,3.2,5] [0.7,0.9,1.3,2.2,6.55,14,22,37,76] 0.4659 171.5 FAIL -18.91 71.35 FAIL 5.25 17.85 PASS PASS PASS_at_MAD_(1/3) -unambiguous p-luakptt NA NA NA NA all ratio 99.45 {ratio:99.45,form:0.55} ratio 1952 1258 [0.97,1,1.01,1.03,1.04,1.06,1.08,1.11,1.17] [0.98,1,1.02,1.04,1.05,1.07,1.1,1.13,1.2] 0.07757 3.729 PASS -2.819 2.315 FAIL 0.01 0.15 PASS PASS PASS_at_KS_(2/3) -unambiguous s-igg3 NA NA NA NA all g/l 99.96 {g/l:99.96,form:0.04} g/l 1951 4826 [0.13,0.17,0.2,0.24,0.27,0.31,0.37,0.45,0.58] [0.13,0.18,0.22,0.26,0.31,0.36,0.44,0.55,0.72] 0.09618 10.91 PASS -7.247 12.32 FAIL 0.04 0.39 PASS PASS PASS_at_KS_(2/3) -unambiguous p-fsh NA NA NA NA all u/l 100 {u/l:100} u/l 1935 8372 [3.3,4.6,5.7,6.9,8.4,13,23.74,45,71] [3.41,4.8,5.9,7.2,9.4,15,30,52,73] 0.04243 2.172 PASS -2.927 2.462 FAIL 1 17.7 PASS PASS PASS_at_KS_(2/3) -unambiguous p-luakrvv NA NA NA NA all ratio 99.45 {ratio:99.45,form:0.55} ratio 1926 1256 [0.89,0.92,0.94,0.96,0.98,1,1.03,1.06,1.14] [0.89,0.93,0.95,0.97,0.99,1.01,1.04,1.08,1.18] 0.06371 2.404 PASS -2.024 1.366 FAIL 0.01 0.15 PASS PASS PASS_at_KS_(2/3) -unambiguous p-prl NA NA NA NA all mu/l 99.81 {mu/l:99.81,nmol/l:0.19} mu/l 1914 8542 [150,186,222,261.2,306,364,439.1,550,784] [138.1,185,224,261,306,361,436,572,938.9] 0.03245 1.14 FAIL -5.431 7.242 FAIL 0 372 PASS PASS PASS_at_MAD_(1/3) -unambiguous l-bas NA NA NA NA all % 100 {%:100} % 1904 7218 [0.2,0.3,0.4,0.4,0.5,0.6,0.7,0.8,1] [0.1,0.2,0.3,0.4,0.4,0.5,0.6,0.7,0.9] 0.1096 15.48 PASS 7.773 13.97 FAIL 0.1 0.6 PASS PASS PASS_at_KS_(2/3) -unambiguous cp-crp-hy NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1836 10332 [1.8,3.2,5,7,9,13,19.5,34,61] [4.7,7,10,14,20,29,42,62,95] 0.2423 80.31 PASS -17.14 62.17 FAIL 11 42 PASS PASS PASS_at_KS_(2/3) -unambiguous p-haptog NA NA NA NA all g/l 100 {g/l:100} g/l 1821 18301 [0.65,0.9,1.09,1.3,1.5,1.69,1.96,2.26,2.78] [0.41,0.7,0.92,1.12,1.33,1.54,1.8,2.14,2.66] 0.09576 12.94 PASS 7.152 11.94 FAIL 0.17 1.68 PASS PASS PASS_at_KS_(2/3) -unambiguous ab-t NA NA NA NA all °c 100 {°c:100} °c 1813 1617 [36.2,36.5,36.7,36.9,37,37,37.1,37.4,37.8] [36.3,36.5,36.8,37,37,37,37.3,37.5,38] 0.0633 2.698 PASS -2.93 2.467 FAIL 0 1.2 PASS PASS PASS_at_KS_(2/3) -unambiguous p-aptt NA NA NA NA all s 100 {s:100} s 1806 143489 [24,25,26,27,29,30,32,35,39] [25,26,27,28.5,30,31,33,36,46] 0.09448 13.59 PASS -13.92 41.3 FAIL 1 12 PASS PASS PASS_at_KS_(2/3) -unambiguous p-prealb NA NA NA NA all g/l 98.99 {g/l:98.99,mg/l:1.01} g/l 1802 17703 [0.13,0.16,0.19,0.2,0.22,0.24,0.27,0.31,138.8] [0.09,0.13,0.16,0.18,0.2,0.22,0.24,0.26,0.29] 0.1505 32.11 PASS 16.05 53.57 FAIL 0.02 0.15 PASS PASS PASS_at_KS_(2/3) -unambiguous s-kol-ldl NA NA NA NA all mmol/l 99.99 {mmol/l:99.99,mmool/l:0,mmol/:0} mmol/l 1798 30028 [1.6,2.1,2.4,2.7,2.9,3.3,3.6,3.9,4.5] [1.8,2.2,2.4,2.7,2.9,3.1,3.4,3.7,4.1] 0.09459 12.93 PASS 4.63 5.409 FAIL 0 1.8 PASS PASS PASS_at_KS_(2/3) -unambiguous cu-alb NA NA NA NA all ug/min 99.93 {ug/min:99.93,mg:0.07} ug/min 1778 5389 [3,5,8,15,26,47,85,173.2,428.6] [4,6,10,18,29,48.8,84,161,427.4] 0.04503 2.07 PASS 0.05861 0.02079 PASS 3 75 PASS PASS PASS_at_KS_(3/3) -unambiguous b-retind NA NA NA NA all osuus 100 {osuus:100} osuus 1744 9157 [0.4,0.5,0.6,0.7,0.8,0.9,1,1.2,1.5] [0.4,0.5,0.7,0.8,0.9,1,1.2,1.5,1.9] 0.1196 17.99 PASS -10.57 24.99 FAIL 0.1 0.9 PASS PASS PASS_at_KS_(2/3) -unambiguous cp-gluk-po NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1737 782 [4.7,5.9,7,8.1,9.2,10.6,12.4,14.68,18.3] [4.6,5.82,7.3,8.4,9.4,10.7,12,14.18,17.49] 0.03385 0.2577 FAIL 0.504 0.2116 PASS 0.2 9.75 PASS PASS PASS_at_T_(2/3) -unambiguous f-elast1 NA NA NA NA all ug/g 99.93 {ug/g:99.93,âug/g:0.07} ug/g 1732 10975 [61.1,124,185,235,292,348,398.7,448,494.9] [48,95,144.2,197,248,302.4,357,412,470] 0.0885 9.918 PASS 7.52 13.11 FAIL 44 396 PASS PASS PASS_at_KS_(2/3) -unambiguous l-prom NA NA NA NA all % 100 {%:100} % 1731 9986 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,1] 0.02093 0.276 FAIL -2.235 1.594 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -unambiguous e-erytrosyytit,kokojakauma NA NA NA NA all % 100 {%:100} % 1729 117212 [14,15,15,15,16,16,17,18,19] [13,13,13,13,14,14,15,16,17] 0.5122 300 FAIL 37.93 230.7 FAIL 2 3 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-mkomp-2 NA NA NA NA all g/l 100 {g/l:100} g/l 1703 27016 [0,0,0,0,0,0,0,0,0.3] [0,0,0,0,0,0,0,0,0] 0.0506 3.277 PASS 4.632 5.413 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous ly-t-cd4/8 NA NA NA NA all ratio 100 {ratio:100} ratio 1701 115 [0.5,0.8,1.1,1.3,1.5,1.8,2.1,2.6,3.6] [0.6,0.8,1,1.26,1.6,1.84,2.08,2.42,3.16] 0.05797 0.07576 FAIL 1.434 0.8134 PASS 0.1 2.1 PASS PASS PASS_at_T_(2/3) -unambiguous l-metam NA NA NA NA all % 100 {%:100} % 1617 7291 [0,0,0,0,0,1,1,1,2] [0,0,0,0,0,1,1,2,3] 0.06055 3.936 PASS -5.99 8.629 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) -unambiguous s-crp NA NA NA NA all mg/l 99.97 {mg/l:99.97,form:0.03,mg/ml:0} mg/l 1601 153116 [2.1,6,8,11,14,19,28,43,77] [1,2,5,7,10,14,20,32,58] 0.1583 34.43 PASS 7.877 14.22 FAIL 4 24.3 PASS PASS PASS_at_KS_(2/3) -unambiguous b-peth NA NA NA NA all umol/l 99.99 {umol/l:99.99,umol/:0.01} umol/l 1586 18209 [0.07,0.12,0.18,0.27,0.36,0.5,0.69,0.98,1.52] [0.06,0.09,0.14,0.2,0.29,0.41,0.59,0.88,1.41] 0.0811 8.068 PASS 4.388 4.917 FAIL 0.07 0.63 PASS PASS PASS_at_KS_(2/3) -unambiguous l-bla NA NA NA NA all % 100 {%:100} % 1582 9301 [0,0,0,0,0,0,0,0,1] [0,0,0,0,0,0,0,0,0] 0.05241 2.943 PASS 1.476 0.8539 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -unambiguous s-igg NA NA NA NA all g/l 100 {g/l:100} g/l 1567 20871 [5.912,7.672,8.67,9.5,10.27,11.1,12,13.61,17.09] [5.59,7.17,8.2,9.1,9.9,10.8,11.8,13.2,16] 0.05565 3.639 PASS 4.038 4.25 FAIL 0.37 6.9 PASS PASS PASS_at_KS_(2/3) -unambiguous p-glukpoc NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1562 957 [5.9,6.5,7,7.6,8.3,9.1,9.8,11.1,13.1] [6.06,6.7,7.3,7.8,8.4,9.2,10.2,11.2,12.94] 0.0537 1.205 FAIL -3.181 2.822 FAIL 0.1 5.1 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-mkomp-3 NA NA NA NA all g/l 100 {g/l:100} g/l 1542 25589 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.003735 -0 FAIL 1.195 0.6341 PASS 0 0 PASS PASS PASS_at_T_(2/3) -unambiguous nu-alb NA NA NA NA all ug/min 100 {ug/min:100} ug/min 1512 442 [1,2.2,4,8,20,33,54,100.8,231.8] [3,6.2,8.3,12,15,18,26,72,195.4] 0.1773 9.15 PASS 2.014 1.354 FAIL 5 27 PASS PASS PASS_at_KS_(2/3) -unambiguous cu-alb-mi NA NA NA NA all ug/min 100 {ug/min:100} ug/min 1510 5748 [2,4,8,19,31.05,54,96,164.2,347.7] [2,3,4,6,9.9,17,34.39,79,218] 0.2215 51.18 PASS 1.206 0.6418 PASS 21.15 23.7 PASS PASS PASS_at_KS_(3/3) -unambiguous s-korsol NA NA NA NA all nmol/l 99.99 {nmol/l:99.99,umol/l:0,nmol/:0} nmol/l 1508 43706 [80.7,202.4,273,322,370.5,414,471.9,542.6,663.6] [138,244,308,360,409,460,517,589,699] 0.09016 10.04 PASS -7.142 11.86 FAIL 38.5 408 PASS PASS PASS_at_KS_(2/3) -unambiguous b-inrpika NA NA NA NA all inr 100 {inr:100} inr 1503 1540 [2,2.2,2.4,2.5,2.6,2.8,2.9,3.2,3.5] [2,2.1,2.3,2.4,2.6,2.7,2.9,3.1,3.4] 0.04325 0.9526 FAIL 2.358 1.734 FAIL 0 1.2 PASS PASS PASS_at_MAD_(1/3) -unambiguous myel NA NA NA NA all % 100 {%:100} % 1491 4482 [0,0,0,0,0,0,1,1,3.5] [0,0,0,0,0,0,1,1,3] 0.0565 2.823 PASS 1.955 1.295 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -unambiguous prom NA NA NA NA all % 100 {%:100} % 1475 4479 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.02467 0.3016 FAIL 3.061 2.652 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -unambiguous u-epipien NA NA NA NA all e6/l 100 {e6/l:100} e6/l 1465 16238 [0,0.1,0.44,0.9,1.5,2.3,3.4,5.1,8.7] [0.1,0.2,0.4,0.6,0.8,1,1.6,2.5,4.8] 0.2005 47.09 PASS 8.468 16.24 FAIL 0.7 1.8 PASS PASS PASS_at_KS_(2/3) -unambiguous happamuusaste,kapillaariveri NA NA NA NA all ph 100 {ph:100} ph 1457 122 [7.33,7.36,7.38,7.39,7.4,7.42,7.43,7.44,7.46] [7.35,7.38,7.39,7.41,7.42,7.43,7.44,7.45,7.48] 0.1377 1.599 PASS -3.045 2.558 FAIL 0.02 0.09 PASS PASS PASS_at_KS_(2/3) -unambiguous bla NA NA NA NA all % 100 {%:100} % 1446 3320 [0,0,0,0,0,0,0,0,1] [0,0,0,0,0,0,0,0,0] 0.03304 0.6665 FAIL -1.082 0.5537 PASS 0 0 PASS PASS PASS_at_T_(2/3) -unambiguous u-leuk-bv NA NA NA NA all e6/l 100 {e6/l:100} e6/l 1442 17865 [1,1.6,2.43,3.7,5.95,12.12,34.37,128.6,621] [0.9,1.7,2.7,4.2,7.3,14.04,34.2,115.4,596.2] 0.0376 1.349 PASS -0.1062 0.03837 PASS 1.35 19.2 PASS PASS PASS_at_KS_(3/3) -unambiguous fs-sappih NA NA NA NA all umol/l 100 {umol/l:100} umol/l 1438 3976 [2,2.5,3,4,4.8,6,6.9,8.2,12.2] [1.6,2,2.4,3,3.7,4.5,5.7,7.6,13.3] 0.1293 15.12 PASS -0.9085 0.4393 PASS 1.1 5.1 PASS PASS PASS_at_KS_(3/3) -unambiguous s-igg-sum NA NA NA NA all g/l 100 {g/l:100} g/l 1434 477 [7.15,8.28,9.149,9.91,10.74,11.57,12.7,14.21,17.21] [6.898,8.282,9.118,9.748,10.9,11.91,13.04,14.71,18.14] 0.03981 0.219 FAIL -0.4105 0.1665 PASS 0.16 7.14 PASS PASS PASS_at_T_(2/3) -unambiguous s-mkomp-4 NA NA NA NA all g/l 100 {g/l:100} g/l 1434 25572 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.000743 -0 FAIL -1.039 0.5247 PASS 0 0 PASS PASS PASS_at_T_(2/3) -unambiguous i-statcrea NA NA NA NA all umol/l 98.17 {umol/l:98.17,mmol/l:1.83} umol/l 1433 161 [55,65,71,79,88,98,110.4,129,166.6] [54,61,66,72,82,88,95,108,121] 0.1425 2.304 PASS 4.047 4.162 FAIL 6 63 PASS PASS PASS_at_KS_(2/3) -unambiguous s-ige NA NA NA NA all u/ml 99.97 {u/ml:99.97,u/l:0.03} u/ml 1427 34187 [8,14.92,24,35,57.3,93.04,149,250.8,536.4] [8,15,23.7,36,54.7,84,137,248,607] 0.02957 0.7485 FAIL -1.366 0.764 PASS 2.6 134.1 PASS PASS PASS_at_T_(2/3) -unambiguous nlt NA NA NA NA all % 100 {%:100} % 1410 4470 [15,24,35,43,49,54,60,68,76] [25,40,48,53,57.75,62,67,73,80] 0.1787 29.65 PASS -11.72 30.23 FAIL 8.75 38.25 PASS PASS PASS_at_KS_(2/3) -unambiguous p-k-vt NA NA NA NA all mmol/l 98.21 {mmol/l:98.21,1:1.79} mmol/l 1404 2199 [3.4,3.6,3.7,3.8,3.9,4,4.1,4.3,4.5] [3.4,3.6,3.8,3.9,4,4,4.2,4.3,4.5] 0.02996 0.3822 FAIL -0.1062 0.03836 PASS 0.1 0.9 PASS PASS PASS_at_T_(2/3) -unambiguous metam NA NA NA NA all % 100 {%:100} % 1398 3264 [0,0,0,0,0,0,0,1,3] [0,0,0,0,0,0,1,1,3] 0.1022 8.638 PASS 0.008348 0.002902 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -unambiguous nst NA NA NA NA all % 100 {%:100} % 1385 3292 [0,0,0,0,0,1,1,2,5] [0,0,0,0,1,1,1,2,5] 0.08924 6.481 PASS -2.057 1.401 FAIL 1 3 PASS PASS PASS_at_KS_(2/3) -unambiguous fp-glukoosi NA NA NA NA all mmol/l 99.93 {mmol/l:99.93,nmol/l:0.07} mmol/l 1356 21503 [6.1,6.2,6.4,6.6,6.8,7,7.4,7.9,9.2] [5.1,5.3,5.5,5.7,5.9,6.1,6.5,7,8] 0.5693 300 FAIL 19.53 75 FAIL 0.9 1.8 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-igf1sds NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 1323 85 [-2.4,-1.5,-0.9,-0.6,-0.2,0.3,0.8,1.3,2.2] [0.4,0.6,0.82,0.96,1.2,1.4,1.5,2.3,2.72] 0.5314 20.76 FAIL -9.756 15.71 FAIL 1.4 1.5 PASS PASS PASS_at_MAD_(1/3) -unambiguous tromboplastiiniaika,inr-tulostus,plasmasta NA NA NA NA all inr 99.91 {inr:99.91,1:0.09} inr 1310 15979 [1,1.1,1.2,1.5,2,2.2,2.4,2.7,3] [1,1,1.1,1.4,1.9,2.2,2.5,2.7,3.1] 0.055 2.898 PASS 0.1715 0.06354 PASS 0.1 2.4 PASS PASS PASS_at_KS_(3/3) -unambiguous b-mo/abs NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1306 797 [0.37,0.43,0.48,0.53,0.57,0.63,0.69,0.77,0.91] [0.36,0.43,0.49,0.54,0.58,0.65,0.71,0.79,0.93] 0.03945 0.3865 FAIL -0.2467 0.09411 PASS 0.01 0.42 PASS PASS PASS_at_T_(2/3) -unambiguous b-ly/abs NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1306 797 [1.08,1.32,1.54,1.71,1.89,2.08,2.24,2.53,2.95] [0.916,1.15,1.35,1.53,1.75,1.93,2.14,2.418,3.028] 0.1056 4.535 PASS 2.854 2.359 FAIL 0.14 1.56 PASS PASS PASS_at_KS_(2/3) -unambiguous b-ba/abs NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1306 797 [0.02,0.02,0.03,0.03,0.03,0.04,0.05,0.05,0.07] [0.02,0.02,0.03,0.03,0.04,0.04,0.05,0.05,0.06] 0.06841 1.737 PASS 1.33 0.7357 PASS 0.01 0.03 PASS PASS PASS_at_KS_(3/3) -unambiguous b-hb-vt NA NA NA NA all g/l 99.66 {g/l:99.66,hb:0.34} g/l 1301 2922 [98,111,119,124,129,134,140,146,154] [106,116,122,127,131,135,140,146,154] 0.07122 3.694 PASS -3.499 3.322 FAIL 2 36 PASS PASS PASS_at_KS_(2/3) -unambiguous u-epilevy NA NA NA NA all e6/l 100 {e6/l:100} e6/l 1298 14634 [0.1,0.3,0.7,1.3,2.2,3.7,7.2,12.36,25.2] [0,0.1,0.3,0.5,0.9,1.3,2.2,4.3,10.4] 0.2038 43.16 PASS 9.13 18.63 FAIL 1.3 2.4 PASS PASS PASS_at_KS_(2/3) -unambiguous u-a1miglo NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1294 344 [7.1,9.5,12.09,15.52,19.5,25.6,33.31,43.44,64.98] [6.03,7.5,9.49,12,16,24.48,37.1,55.08,97.23] 0.1196 3.123 PASS -2.659 2.09 FAIL 3.5 29.7 PASS PASS PASS_at_KS_(2/3) -unambiguous emäsylimäärä,laskimoveri NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1291 2438 [-7.8,-5.5,-4,-3.2,-2.4,-1.7,-1.2,-0.8,-0.4] [0.5,1.2,1.7,2.3,2.9,3.5,4.3,5.3,6.9] 0.9852 300 FAIL -59.48 300 FAIL 5.3 4.8 FAIL FAIL FAIL_at_MAD_(0/3) -unambiguous du-ca NA NA NA NA all mmol 98.36 {mmol:98.36,mmol/24h:1.59,*sai:0.05} mmol 1285 12333 [1.7,2.8,3.728,4.54,5.67,6.588,7.682,8.782,10.3] [1.77,2.74,3.61,4.5,5.39,6.3,7.4,8.7,10.76] 0.03778 1.153 FAIL -0.2523 0.09644 PASS 0.28 7.08 PASS PASS PASS_at_T_(2/3) -unambiguous crp(vo:nyhteydessäotettu),tth NA NA NA NA all mg/l 99.37 {mg/l:99.37,alle:0.63} mg/l 1267 158 [5,5,5,8,8,8,13,22,44] [5,5,5,6,8,9,13.9,18,37.9] 0.09585 0.8513 FAIL 1.094 0.5602 PASS 0 9 PASS PASS PASS_at_T_(2/3) -unambiguous pika-crp NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1257 3592 [6,8.92,12,19,26,35,50,69.8,101.4] [6,8,11,15,21,30,42,61,93] 0.06889 3.564 PASS 3.121 2.738 FAIL 5 42 PASS PASS PASS_at_KS_(2/3) -unambiguous cb-hb NA NA NA NA all g/l 100 {g/l:100} g/l 1251 15173 [94,105,112,119,124,130,135,142,152] [98,107,115,122,128,134,140,147,157] 0.08193 6.471 PASS -5.985 8.565 FAIL 4 48 PASS PASS PASS_at_KS_(2/3) -unambiguous cb-po2 NA NA NA NA all kpa 100 {kpa:100} kpa 1248 47686 [6.3,7.1,7.9,8.5,9.2,10,10.8,11.7,12.83] [6.3,7,7.6,8.2,8.7,9.3,10,10.8,11.9] 0.1074 11.93 PASS 7.035 11.49 FAIL 0.5 4.5 PASS PASS PASS_at_KS_(2/3) -unambiguous s-ana NA NA NA NA all titre 99.99 {titre:99.99,mmol/mol:0.01} titre 1248 16685 [80,160,320,320,320,320,640,640,1280] [80,160,160,320,320,320,400,640,1280] 0.1359 18.43 PASS 2.543 1.955 FAIL 0 480 PASS PASS PASS_at_KS_(2/3) -unambiguous p-fibr NA NA NA NA all g/l 100 {g/l:100} g/l 1233 38558 [2,2.3,2.6,2.9,3.1,3.4,3.8,4.3,5.18] [1.7,2.2,2.5,2.8,3.2,3.5,4,4.6,5.6] 0.06094 3.573 PASS -3.062 2.65 FAIL 0.1 2.91 PASS PASS PASS_at_KS_(2/3) -unambiguous s-ca-i7.4 NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1232 45578 [1.18,1.21,1.23,1.25,1.26,1.27,1.29,1.3,1.33] [1.17,1.2,1.22,1.24,1.25,1.27,1.28,1.3,1.34] 0.05625 3.015 PASS 3.286 2.982 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) -unambiguous i-statna NA NA NA NA all mmol/l 98.26 {mmol/l:98.26,mmol/:1.16,umol/l:0.58} mmol/l 1231 169 [132,135,137,138,139,140,141,142,143] [134,136,137,139,140,140,141,142,143] 0.0551 0.1344 FAIL -0.9083 0.438 PASS 1 6 PASS PASS PASS_at_T_(2/3) -unambiguous i-statk NA NA NA NA all mmol/l 98.81 {mmol/l:98.81,umol/l:0.6,mmol/:0.6} mmol/l 1230 166 [3.3,3.6,3.7,3.8,3.9,4,4.2,4.3,4.6] [3.3,3.5,3.6,3.8,3.9,4,4.2,4.3,4.5] 0.06251 0.2274 FAIL -0.9169 0.4431 PASS 0 0.9 PASS PASS PASS_at_T_(2/3) -unambiguous li-igg/alb NA NA NA NA all osuus 99.76 {osuus:99.76,ratio:0.24} osuus 1212 823 [0.09,0.1,0.11,0.13,0.14,0.15,0.17,0.2,0.28] [0.09,0.1,0.11,0.12,0.13,0.14,0.15,0.17,0.238] 0.08623 2.899 PASS 2.772 2.249 FAIL 0.01 0.09 PASS PASS PASS_at_KS_(2/3) -unambiguous p-gfreepi NA NA NA NA all ml/min/173m2 100 {ml/min/173m2:100} ml/min/173m2 1212 6373 [18.72,36.14,45.36,51.5,55.85,59.66,65.24,69.9,76.9] [23.24,37.04,43.5,48.7,53,56.3,59.6,65.8,73.1] 0.1066 9.811 PASS 3.509 3.335 FAIL 2.85 33.6 PASS PASS PASS_at_KS_(2/3) -unambiguous p-omagluk NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1212 255 [5.4,5.9,6.4,6.8,7.3,7.9,8.4,9.5,12.1] [5.8,6.2,6.6,6.9,7.3,7.8,8.7,9.6,11.36] 0.07709 0.8125 FAIL 0.3778 0.1514 PASS 0 3.6 PASS PASS PASS_at_T_(2/3) -unambiguous p-kreatiniini NA NA NA NA all umol/l 100 {umol/l:100} umol/l 1210 116933 [59,98,104,110,117,127,143,166,209] [55,61,66,71,77,83,91,103,130] 0.5727 300 FAIL 20.52 79.93 FAIL 40 45 PASS PASS PASS_at_MAD_(1/3) -unambiguous p-hcg-tot NA NA NA NA all iu/l 100 {iu/l:100} iu/l 1197 3737 [4.8,11.8,27.38,66.42,147.2,352,1044,3432,1.564e+04] [4,10.32,28.4,72.58,183.5,425.9,1037,3053,1.542e+04] 0.03315 0.5771 FAIL -0.2025 0.07594 PASS 36.3 540.9 PASS PASS PASS_at_T_(2/3) -unambiguous s-shbg NA NA NA NA all nmol/l 100 {nmol/l:100,g/l:0} nmol/l 1192 28134 [15,20,24,28,33,37,44,52,64] [17,21,25,29,33,38,44,52,65] 0.04081 1.366 PASS -0.7427 0.3393 PASS 0 33 PASS PASS PASS_at_KS_(3/3) -unambiguous u-sakka,eryt NA NA NA NA all u/field 100 {u/field:100} u/field 1161 85 [0,0,0,0,1,1,2,3,8] [0,1,1,1,1,2,2.8,4,7] 0.3415 8.008 FAIL -0.516 0.2169 PASS 0 3 PASS PASS PASS_at_T_(2/3) -unambiguous u-alb-mi NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1149 6339 [1,3,4,6,8,11,18,40,143] [3,4,5.5,7.576,11,18.48,35.4,84.52,321] 0.1507 19.01 PASS -3.853 3.919 FAIL 3 24 PASS PASS PASS_at_KS_(2/3) -unambiguous s-haptog NA NA NA NA all g/l 100 {g/l:100} g/l 1142 10330 [0.68,0.97,1,1.064,1.345,1.65,2,2.05,2.93] [0.47,0.7,0.9,1.13,1.31,1.54,1.8,2.18,2.7] 0.1397 17.24 PASS 3.316 3.028 FAIL 0.035 1.65 PASS PASS PASS_at_KS_(2/3) -unambiguous s-alb NA NA NA NA all g/l 99.91 {g/l:99.91,%:0.05,mg/g:0.03} g/l 1141 23178 [32,35,36.4,37.5,38.6,39.6,40.9,42,44] [34,36.9,38,39,40,41,42,43,45] 0.191 34.48 PASS -9.29 19.17 FAIL 1.4 9 PASS PASS PASS_at_KS_(2/3) -unambiguous gluk-pika NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1140 727 [5.5,6.1,6.5,7.1,7.7,8.5,9.4,10.7,12.8] [5,5.5,5.9,6.2,6.6,7.2,7.9,9.08,11.4] 0.1982 15.02 PASS 5.046 6.295 FAIL 1.1 3.6 PASS PASS PASS_at_KS_(2/3) -unambiguous vb-hco3-st NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1122 104777 [18,20,21,23,23,24,25,26,28] [20,21,22,23,24,25,25,26,28] 0.092 7.899 PASS -4.621 5.371 FAIL 1 6 PASS PASS PASS_at_KS_(2/3) -unambiguous crppika NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1122 869 [6,9,13,19.4,27,37,51,74.8,111] [6,7,10,13,18,26,39,56,88.2] 0.126 6.51 PASS 5.477 7.312 FAIL 9 36 PASS PASS PASS_at_KS_(2/3) -unambiguous s-pölyer NA NA NA NA all u/ml 99.02 {u/ml:99.02,form:0.79,estimate:0.19} u/ml 1120 7301 [0.03,0.05,0.09,0.216,0.575,1.624,3.573,8.788,22.06] [0.03,0.04,0.05,0.09,0.19,0.54,1.84,5.68,16.4] 0.1304 14.12 PASS 3.206 2.861 FAIL 0.385 0.51 PASS PASS PASS_at_KS_(2/3) -unambiguous b-gluk/pi NA NA NA NA all mmol/l 100 {mmol/l:100} mmol/l 1119 295 [5.3,5.8,6.3,6.7,7.4,8.1,9.2,10.4,12.84] [4.9,5.4,5.8,6.2,6.6,7.2,7.8,9.22,12.54] 0.1551 4.644 PASS 2.703 2.148 FAIL 0.8 3.6 PASS PASS PASS_at_KS_(2/3) -unambiguous s-t3-v NA NA NA NA all pmol/l 99.99 {pmol/l:99.99,pmol/:0.01} pmol/l 1116 18326 [3.5,3.8,4,4.2,4.4,4.6,4.8,5.2,5.8] [3.7,4.1,4.3,4.5,4.7,4.9,5.1,5.4,6.095] 0.1496 20.28 PASS -8.972 18.04 FAIL 0.3 1.5 PASS PASS PASS_at_KS_(2/3) -unambiguous s-mpoabg NA NA NA NA all iu/ml 98.8 {iu/ml:98.8,u/ml:1.2} iu/ml 1105 1315 [4.2,5.6,7.2,9.1,11,16,23,35,57] [3.6,4.8,6.2,7.7,9.7,13,18.8,28.2,49] 0.08196 3.236 PASS 2.755 2.228 FAIL 1.3 16.8 PASS PASS PASS_at_KS_(2/3) -unambiguous b-crp-pik NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1059 353 [7,10,14,19,25,34,46,60,97] [9,13,17,23,30,40,51.8,72,105.8] 0.08782 1.486 PASS -2.634 2.061 FAIL 5 54 PASS PASS PASS_at_KS_(2/3) -unambiguous b-pvk+tkd,leuk NA NA NA NA all e9/l 100 {e9/l:100} e9/l 1051 3390 [4.4,5.1,5.6,6.1,6.7,7.4,8,8.7,10.2] [4.6,5.3,5.9,6.5,7.1,7.7,8.4,9.4,10.9] 0.06786 2.933 PASS -4.69 5.535 FAIL 0.4 4.8 PASS PASS PASS_at_KS_(2/3) -unambiguous s-sappih NA NA NA NA all umol/l 100 {umol/l:100} umol/l 1039 9064 [2,3,3,4,4.4,5.1,7,10,18] [2,2.9,3.5,4.4,6,7.6,10.7,17,32.07] 0.1419 16.11 PASS -3.752 3.738 FAIL 1.6 10.5 PASS PASS PASS_at_KS_(2/3) -unambiguous fs-c-pept NA NA NA NA all nmol/l 100 {nmol/l:100} nmol/l 1029 14049 [0.2316,0.4,0.543,0.66,0.778,0.9108,1.08,1.329,1.705] [0.23,0.4,0.54,0.67,0.79,0.9318,1.13,1.4,1.95] 0.04121 1.126 FAIL -4.433 4.998 FAIL 0.012 1.11 PASS PASS PASS_at_MAD_(1/3) -unambiguous s-lzm NA NA NA NA all mg/l 100 {mg/l:100} mg/l 1022 24683 [5.21,7.42,8.73,10,11,12,13.2,15,18.28] [1.8,8,10,11,12,13.2,14.9,16,19] 0.1322 14.68 PASS -2.802 2.287 FAIL 1 9 PASS PASS PASS_at_KS_(2/3) -unambiguous u-sakka,leuk NA NA NA NA all u/field 100 {u/field:100} u/field 1002 85 [0,0,0,0,0,1,2,5,11.9] [0,0,0,0,0,1,1,2,5] 0.1061 0.4997 FAIL 1.483 0.8506 PASS 0 0 PASS PASS PASS_at_T_(2/3) -ambiguous b-hkr split_by_score 0.8595 0.9783 0 low osuus 46.72 {%:53.16,osuus:46.72,fl:0.08} osuus 1558906 4240703 [0.32,0.35,0.37,0.386,0.4,0.41,0.42,0.44,0.46] [0.31,0.34,0.36,0.38,0.39,0.41,0.42,0.44,0.46] 0.03919 300 PASS 10.5 25.04 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) -ambiguous b-hkr split_by_score 0.8595 0.9783 0 high % 53.16 {%:53.16,osuus:46.72,fl:0.08} % 191557 4824770 [32,34,37,38,39,41,42,43,45] [30,33,36,38,39,41,42,43,45] 0.05765 300 PASS 53.64 300 FAIL 0 12 PASS PASS PASS_at_KS_(2/3) -ambiguous p-tt-inr skipped NA NA NA all inr 93.35 {inr:93.35,form:6.65,1:0.01} inr 1026823 339780 [1,1.1,1.2,1.6,2,2.2,2.5,2.7,3.1] [1,1,1.1,1.2,1.5,2,2.3,2.6,3] 0.1171 300 PASS 97.96 300 FAIL 0.5 1.5 PASS PASS PASS_at_KS_(2/3) -ambiguous s-ph skipped NA NA NA all 1 83.33 {1:83.33,ph:16.67} 1 396270 140 [7.34,7.36,7.37,7.38,7.39,7.41,7.42,7.43,7.45] [7.36,7.38,7.39,7.4,7.405,7.42,7.42,7.43,7.45] 0.1458 2.334 PASS -2.552 1.929 FAIL 0.015 0.045 PASS PASS PASS_at_KS_(2/3) -ambiguous b-eos skipped NA NA NA all e9/l 97.68 {e9/l:97.68,%:2.3,e6/l:0.02} e9/l 382440 1092967 [0.01,0.04,0.08,0.11,0.14,0.18,0.22,0.29,0.42] [0.02,0.07,0.1,0.12,0.15,0.19,0.23,0.3,0.4] 0.06737 300 PASS 2.498 1.903 FAIL 0.01 0.24 PASS PASS PASS_at_KS_(2/3) -ambiguous ab-ph skipped NA NA NA all ph 72.83 {ph:72.83,form:26.24,mmol/l:0.44} ph 380651 2975 [7.33,7.36,7.39,7.4,7.42,7.43,7.45,7.46,7.49] [7.37,7.39,7.41,7.42,7.43,7.44,7.45,7.47,7.48] 0.1419 51.61 PASS -14.52 45.54 FAIL 0.01 0.09 PASS PASS PASS_at_KS_(2/3) -ambiguous b-monos skipped NA NA NA all e9/l 97.82 {e9/l:97.82,%:2.18} e9/l 373740 965697 [0.34,0.42,0.47,0.53,0.58,0.65,0.72,0.82,0.98] [0.32,0.4,0.46,0.5,0.57,0.61,0.7,0.78,0.92] 0.05309 300 PASS 41.14 300 FAIL 0.01 0.45 PASS PASS PASS_at_KS_(2/3) -ambiguous p-tsh skipped NA NA NA all mu/l 97.24 {mu/l:97.24,miu/l:2.41,mlu/l:0.35} mu/l 344154 1315114 [0.48,0.93,1.26,1.56,1.89,2.2,2.62,3.27,4.4] [0.53,0.92,1.21,1.5,1.8,2.1,2.51,3.1,4.2] 0.03165 237.1 PASS -24.22 128.8 FAIL 0.09 2.43 PASS PASS PASS_at_KS_(2/3) -ambiguous b-ly skipped NA NA NA all e9/l 97.41 {e9/l:97.41,%:2.59} e9/l 335323 784182 [0.8,1.07,1.28,1.48,1.67,1.89,2.13,2.44,2.97] [0.9,1.16,1.38,1.56,1.74,1.94,2.18,2.48,2.94] 0.05066 300 PASS -1.136 0.592 PASS 0.07 1.56 PASS PASS PASS_at_KS_(3/3) -ambiguous u-suhti skipped NA NA NA all kg/l 91.82 {kg/l:91.82,g/ml:6.83,ratio:1.26} kg/l 261486 41398 [1.01,1.013,1.015,1.015,1.018,1.02,1.02,1.024,1.026] [1.01,1.01,1.013,1.015,1.015,1.02,1.02,1.021,1.025] 0.1232 300 PASS -0.627 0.2752 PASS 0.003 0.015 PASS PASS PASS_at_KS_(3/3) -ambiguous u-keto-o skipped NA NA NA all estimate 94.61 {estimate:94.61,l:4.7,form:0.69} estimate 49568 133623 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.00291 0.03687 FAIL 5.854 8.315 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -ambiguous u-ph-o skipped NA NA NA all N 52.17 {N:52.17,form:47.78,70:0.03} N 48516 2076 [5,5.5,6,6,6,6.5,7,7,7.5] [5.5,6,6,6,6.5,7,7,7,7.5] 0.151 39.36 PASS -16.11 54.73 FAIL 0.5 1.5 PASS PASS PASS_at_KS_(2/3) -ambiguous b-ghb-a1c skipped NA NA NA all % 95.93 {%:95.93,mmol/mol:4.07} % 39036 48557 [5.2,5.5,5.6,5.8,6.1,6.3,6.7,7.4,8.5] [5.2,5.4,5.5,5.7,5.8,6,6.3,6.8,7.8] 0.1436 300 PASS 28 170.3 FAIL 0.3 1.2 PASS PASS PASS_at_KS_(2/3) -ambiguous p-tromboplastiiniaika,inr-tulostus skipped NA NA NA all inr 57.5 {inr:57.5,1:40,form:2.5} inr 38382 92 [1.1,1.4,1.9,2.1,2.3,2.5,2.7,2.9,3.3] [1.8,2.1,2.2,2.3,2.5,2.66,2.7,2.9,3.1] 0.1638 1.899 PASS -2.477 1.821 FAIL 0.2 0.9 PASS PASS PASS_at_KS_(2/3) -ambiguous mono split_by_score 2.627 0.7429 0 low e9/l 15.13 {%:84.87,e9/l:15.13} e9/l 17003 7454 [0.39,0.45,0.5,0.57,0.62,0.7,0.78,0.88,1] [0.36,0.42,0.47,0.52,0.57,0.62,0.68,0.74,0.86] 0.148 98.76 PASS 22.25 107.5 FAIL 0.05 0.39 PASS PASS PASS_at_KS_(2/3) -ambiguous mono split_by_score 2.627 0.7429 0 high % 84.87 {%:84.87,e9/l:15.13} % 13637 41798 [6,7,8,8,9,10,11,12,14] [5.1,7,7.7,8,9,10,10.4,12,13.9] 0.05219 24.05 PASS 9.37 20.1 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) -ambiguous baso skipped NA NA NA all e9/l 13.73 {%:86.27,e9/l:13.73} e9/l 30199 8002 [0,0.02,0.03,0.04,0.05,0.08,1,1,1] [0.02,0.02,0.03,0.04,0.04,0.05,0.06,0.07,0.08] 0.3413 300 FAIL 103 300 FAIL 0.01 0.06 PASS PASS PASS_at_MAD_(1/3) -ambiguous lymf split_by_score 7.03 0.7018 0 low e9/l 13.98 {%:86.02,e9/l:13.98} e9/l 12928 7619 [0.95,1.16,1.35,1.54,1.75,1.96,2.19,2.51,3.04] [1.06,1.34,1.51,1.68,1.84,2.03,2.23,2.5,2.92] 0.09616 38.31 PASS -2.645 2.087 FAIL 0.09 1.35 PASS PASS PASS_at_KS_(2/3) -ambiguous lymf split_by_score 7.03 0.7018 0 high % 86.02 {%:86.02,e9/l:13.98} % 13769 46895 [14,18,22,25,28,31,34,38,45] [13,18,22,25,28,31,34,37,43] 0.03562 11.45 PASS 11.49 29.71 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) -ambiguous s-tsh skipped NA NA NA all mu/l 72.2 {mu/l:72.2,miu/l:27.73,u/l:0.04} mu/l 26229 248419 [0.41,0.863,1.17,1.42,1.7,2.04,2.46,3.1,4.41] [0.62,0.91,1.13,1.39,1.6,1.84,2.2,2.62,3.5] 0.0714 104.9 PASS 8.223 15.68 FAIL 0.1 1.92 PASS PASS PASS_at_KS_(2/3) -ambiguous b-lymfos skipped NA NA NA all e9/l 96.27 {e9/l:96.27,%:3.73} e9/l 19817 4466 [0.89,1.12,1.3,1.48,1.65,1.83,2.05,2.34,2.83] [1.02,1.29,1.46,1.63,1.81,2,2.22,2.53,3.01] 0.09359 27.51 PASS -0.4248 0.1733 PASS 0.16 1.44 PASS PASS PASS_at_KS_(3/3) -ambiguous b-neutr skipped NA NA NA all e9/l 76.51 {e9/l:76.51,%:23.49} e9/l 19426 7723 [2.07,2.6,3.02,3.43,3.85,4.32,4.9,5.73,7.24] [1.9,2.34,2.756,3.158,3.59,4.07,4.67,5.41,6.87] 0.07016 23.37 PASS 4.47 5.104 FAIL 0.26 3.57 PASS PASS PASS_at_KS_(2/3) -ambiguous b-hb-a1c skipped NA NA NA all % 85.06 {%:85.06,mmol/mol:14.85,%/mmol:0.06} % 18914 43586 [5.4,5.5,5.6,5.8,6,6.2,6.5,7.2,8.1] [5.3,5.4,5.6,5.8,5.9,6.1,6.4,6.9,7.7] 0.05016 28.55 PASS 7.633 13.63 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) -ambiguous u-suhteellinentiheys skipped NA NA NA all 1 78.44 {1:78.44,kg/l:21.56} 1 17548 262 [1.01,1.012,1.015,1.015,1.017,1.02,1.02,1.023,1.025] [1.01,1.015,1.015,1.015,1.02,1.02,1.02,1.025,1.025] 0.1136 2.631 PASS -0.06127 0.02174 PASS 0.003 0.015 PASS PASS PASS_at_KS_(3/3) -ambiguous eos skipped NA NA NA all % 91.96 {%:91.96,e9/l:8.04} % 14491 49739 [0,1,2,2,3,3,4,5,7] [0,1,2,2,3,3,4,5,6] 0.03345 10.61 PASS 5.809 8.197 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) -ambiguous s-ttgaba skipped NA NA NA all u/ml 91.82 {u/ml:91.82,eliau/ml:7.73,form:0.44} u/ml 13768 32224 [0.2,0.3,0.4,0.5,0.6,0.7,0.8,1.1,1.9] [0.2,0.3,0.4,0.5,0.6,0.7,0.8,1.1,1.9] 0.01981 2.992 PASS -4.377 4.917 FAIL 0 0.9 PASS PASS PASS_at_KS_(2/3) -ambiguous neut skipped NA NA NA all % 93.42 {%:93.42,e9/l:6.58} % 12259 61798 [42,48,52,55,58,61,64,68,74] [43.1,49,52.8,56,59,62,65,69.4,75.4] 0.03737 12.12 PASS -8.523 16.78 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) -ambiguous fp-pth skipped NA NA NA all ng/l 80.05 {ng/l:80.05,pmol/l:19.95} ng/l 11194 122007 [7,15,36,50,63,77,92,116,169] [35,51,66,84,106,135,179,253,408] 0.2661 300 PASS -67.71 300 FAIL 43 177 PASS PASS PASS_at_KS_(2/3) -ambiguous b-erytrosyytit,tilavuusosuus skipped NA NA NA all osuus 77.47 {osuus:77.47,%:22.53,1:0} osuus 10999 292478 [0.34,0.37,0.38,0.4,0.41,0.42,0.43,0.44,0.46] [0.31,0.34,0.37,0.38,0.4,0.41,0.42,0.44,0.46] 0.1015 94.72 PASS -0.7254 0.3295 PASS 0.01 0.12 PASS PASS PASS_at_KS_(3/3) -ambiguous p-antifxa skipped NA NA NA all iu/ml 56.03 {iu/ml:56.03,u/ml:43.91,umol/l:0.06} iu/ml 10859 13789 [0.13,0.17,0.21,0.26,0.31,0.38,0.45,0.54,0.7] [0.13,0.16,0.21,0.25,0.3,0.36,0.42,0.51,0.68] 0.04087 8.526 PASS 4.094 4.371 FAIL 0.01 0.39 PASS PASS PASS_at_KS_(2/3) -ambiguous fs-trfesat skipped NA NA NA all % 80.03 {%:80.03,osuus:18.85,1:1.13} % 10835 1915 [0.09,0.13,0.16,0.19,0.22,0.25,0.29,0.34,0.42] [7,11,14,17,20,23,27,32,39] 0.9897 300 FAIL -65.58 300 FAIL 19.78 24 PASS PASS PASS_at_MAD_(1/3) -ambiguous u-happamuusaste bimodal_cautious 6.205 0.1646 0 low 1 91.97 {1:91.97,5170:7.63,form:0.4} 1 2901 229 [5,5.5,5.5,5.5,6,6,6,6,6] [5.5,6,6,6,6,6,6.5,6.5,7] 0.3319 20.58 FAIL -13.77 31.58 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -ambiguous u-happamuusaste bimodal_cautious 6.205 0.1646 0 high 1 91.97 {1:91.97,5170:7.63,form:0.4} 1 7722 229 [6.5,6.5,7,7,7,7,7.5,7.5,8] [5.5,6,6,6,6,6,6.5,6.5,7] 0.6681 97.2 FAIL 24.78 67.43 FAIL 1 0 FAIL FAIL FAIL_at_MAD_(0/3) -ambiguous p-tromboplastiiniaika,inr-tulos skipped NA NA NA all inr 52.05 {inr:52.05,1:47.95} inr 8123 6341 [1.7,2,2.2,2.3,2.5,2.6,2.8,3,3.4] [1,1.1,1.1,1.3,1.9,2.2,2.4,2.7,3.1] 0.3644 300 FAIL 44.74 300 FAIL 0.6 2.4 PASS PASS PASS_at_MAD_(1/3) -ambiguous b-pvk+t skipped NA NA NA all % 43.01 {%:43.01,e9/l:23.04,g/l:13.71} % 7646 8614 [1,1,1,1,1,1,1,1,1] [6,10,12,13,14,28,39,52,62] 0.9975 300 FAIL 1.556 0.9216 PASS 13 27 PASS PASS PASS_at_T_(2/3) -ambiguous s-ccpab skipped NA NA NA all u/ml 83.24 {u/ml:83.24,eliau/ml:15.54,form:1.22} u/ml 7611 30305 [0.6,0.7,0.9,1,1.1,1.3,1.5,1.8,5] [0.6,0.8,0.9,1,1.2,1.4,1.6,2.2,21] 0.06054 19.1 PASS -8.189 15.55 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) -ambiguous l-mono skipped NA NA NA all % 97.66 {%:97.66,e9/l:2.34} % 7071 58379 [2.6,5,6.9,7.6,8.1,9,10,11.3,13] [4.6,6,7,8,9,9.3,10,11.7,14] 0.07021 26.75 PASS -8.86 18.02 FAIL 0.9 6 PASS PASS PASS_at_KS_(2/3) -ambiguous l-ly split_by_score 6.662 0.7783 0 low e9/l 2.01 {%:97.98,e9/l:2.01,osuus:0} e9/l 1408 2846 [1.097,1.38,1.59,1.76,1.93,2.1,2.31,2.59,2.98] [1.1,1.3,1.5,1.7,1.83,2,2.2,2.5,2.9] 0.07858 4.785 PASS 2.455 1.849 FAIL 0.1 1.29 PASS PASS PASS_at_KS_(2/3) -ambiguous l-ly split_by_score 6.662 0.7783 0 high % 97.98 {%:97.98,e9/l:2.01,osuus:0} % 5054 138412 [15.63,19.6,23,25.9,28.2,31,34,37.7,43.57] [13,18,22,25.1,28.1,31.2,34.9,38.9,45] 0.04859 9.719 PASS 1.478 0.8553 PASS 0.1 24.3 PASS PASS PASS_at_KS_(3/3) -ambiguous p-rf skipped NA NA NA all iu/ml 92.76 {iu/ml:92.76,u/ml:7.21,iu/l:0.03} iu/ml 6213 10583 [5,6,7,9,11,14,20,34,86] [7,10,11,12.7,15,19,27,48.3,105] 0.2662 244.7 PASS -6.241 9.351 FAIL 4 18 PASS PASS PASS_at_KS_(2/3) -ambiguous s-fsh skipped NA NA NA all iu/l 51.12 {iu/l:51.12,u/l:48.88} iu/l 6137 14866 [3.1,4.6,5.9,7.1,8.9,13,23.6,44.08,69.4] [3.3,4.7,6,7.6,10.1,17.2,33.1,51.9,72.9] 0.05693 11.95 PASS -5.692 7.89 FAIL 1.2 20.7 PASS PASS PASS_at_KS_(2/3) -ambiguous u-osmoest skipped NA NA NA all mosm/kgh2o 60.17 {mosm/kgh2o:60.17,mosm/l:34.05,e6/l:5.78} mosm/kgh2o 5941 25256 [340,440,520,550,630,700,740,850,960] [330,440,520,550,630,700,740,850,1000] 0.02943 3.326 PASS -5.525 7.464 FAIL 0 450 PASS PASS PASS_at_KS_(2/3) -ambiguous neutrofiilit bimodal 53.09 0.6531 0 low % 70.69 {%:70.69,e9/l:29.31,52%:0} % 2762 25265 [1,3,5,7,11,16,23,31,42] [43,48,52,56,59,62,65,69,75] 0.8126 300 FAIL -138.2 300 FAIL 48 24 FAIL FAIL FAIL_at_MAD_(0/3) -ambiguous neutrofiilit bimodal 53.09 0.6531 0 high % 70.69 {%:70.69,e9/l:29.31,52%:0} % 1797 25265 [60,67,73,78,82,85,89,91,94] [43,48,52,56,59,62,65,69,75] 0.5689 300 FAIL 69.36 300 FAIL 23 24 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-klotsa split_by_score 35.23 0.9066 0 low nmol/l 79.87 {nmol/l:79.87,umol/l:20.06,âumol/l:0.07} nmol/l 733 37623 [0.644,1,1.1,1.4,1.6,1.9,2,2.3,2.78] [586,870,1100,1312,1520,1740,1986,2304,2797] 0.9978 300 FAIL -340.1 300 FAIL 1518 1704 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-klotsa split_by_score 35.23 0.9066 0 high nmol/l 79.87 {nmol/l:79.87,umol/l:20.06,âumol/l:0.07} nmol/l 3675 37623 [526,787.4,1014,1237,1458,1687,1930,2238,2697] [586,870,1100,1312,1520,1740,1986,2304,2797] 0.04005 4.375 PASS -4.016 4.221 FAIL 62 1704 PASS PASS PASS_at_KS_(2/3) -ambiguous s-digoks skipped NA NA NA all nmol/l 96.59 {nmol/l:96.59,ug/l:3.41} nmol/l 3559 18447 [0.5,0.6,0.6,0.7,0.8,0.9,1,1.1,1.3] [0.4,0.5,0.6,0.7,0.8,0.9,1,1.1,1.4] 0.03224 2.401 PASS -3.499 3.327 FAIL 0 0.6 PASS PASS PASS_at_KS_(2/3) -ambiguous s-tshrab skipped NA NA NA all iu/l 84.17 {iu/l:84.17,u/l:15.54,iu/ml:0.2} iu/l 3513 6615 [1.7,2.5,3,3.5,4.1,4.9,6.3,9,16] [1.7,2,2.4,2.9,3.3,3.9,5,7.3,14] 0.1548 47.72 PASS 5.067 6.382 FAIL 0.8 4.2 PASS PASS PASS_at_KS_(2/3) -ambiguous na skipped NA NA NA all mmol/l 19.19 {mmol/l:19.19,%:15.12,e9/l:14.7} mmol/l 3419 8463 [1.7,2,2.1,2.3,2.4,2.6,2.9,3.2,4.4] [1.3,2,3.1,3.8,4.1,4.82,6,11.7,139] 0.5017 300 FAIL 1.791 1.134 PASS 1.7 6 PASS PASS PASS_at_T_(2/3) -ambiguous b-hba1cvt skipped NA NA NA all mmol/mol 58.36 {mmol/mol:58.36,%:41.64} mmol/mol 3196 10683 [46,51,55,58,61,64,68,74,82] [41,45,48,51,54,57,61,66,75] 0.2325 116.7 PASS 18.64 73.96 FAIL 7 24 PASS PASS PASS_at_KS_(2/3) -ambiguous s-prealb split_by_score 6.265 0.9397 0 low g/l 46.45 {mg/l:53.55,g/l:46.45} g/l 2235 33018 [0.1,0.13,0.16,0.18,0.2,0.22,0.24,0.26,0.3] [0.09,0.12,0.16,0.18,0.2,0.22,0.24,0.26,0.29] 0.03626 2.1 PASS -0.5916 0.2564 PASS 0 0.18 PASS PASS PASS_at_KS_(3/3) -ambiguous s-prealb split_by_score 6.265 0.9397 0 high mg/l 53.55 {mg/l:53.55,g/l:46.45} mg/l 955 38068 [98.4,139,161.2,188,207,229,247,269,294] [122,158,184,205,224,241,260,281,312] 0.09698 7.354 PASS -6.33 9.431 FAIL 17 147 PASS PASS PASS_at_KS_(2/3) -ambiguous s-rf skipped NA NA NA all iu/ml 72.43 {iu/ml:72.43,kiu/l:25.76,u/ml:1.74} iu/ml 3025 11352 [5,6,7,8,9,10,11,15,40.6] [8,9,10,11,11.1,12,14,21,52.98] 0.3576 273.2 FAIL -2.897 2.423 FAIL 2.1 6.3 PASS PASS PASS_at_MAD_(1/3) -ambiguous p-inr-pika skipped NA NA NA all % 96.06 {%:96.06,inr:3.94} % 2999 829 [1.9,2.1,2.3,2.4,2.6,2.7,2.9,3.2,3.6] [1.8,2.1,2.2,2.4,2.5,2.6,2.8,3,3.3] 0.08404 3.716 PASS 4.052 4.269 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) -ambiguous s-prl skipped NA NA NA all mu/l 94.27 {mu/l:94.27,miu/l:5.51,nmol/l:0.19} mu/l 2987 28193 [137,180,218,259,308,369,452,588.8,900.6] [115,152.1,185,220,262,314,389,522.6,840] 0.101 23.73 PASS -0.08868 0.03183 PASS 46 342 PASS PASS PASS_at_KS_(3/3) -ambiguous s-mypnabg split_by_score 26.53 0.6575 0 low eiu 82.35 {eiu:82.35,au/ml:12.74,ru/ml:4.32} eiu 1163 7323 [0.5,0.9,1.4,2,2.7,3.7,5.3,7.5,13.18] [51,65,79,95,113,135,160,200,259.8] 0.9771 300 FAIL -129.9 300 FAIL 110.3 144 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-mypnabg split_by_score 26.53 0.6575 0 high eiu 82.35 {eiu:82.35,au/ml:12.74,ru/ml:4.32} eiu 1764 7323 [51,63,77,92.68,108,131,155,191,246.4] [51,65,79,95,113,135,160,200,259.8] 0.0287 0.7263 FAIL -1.654 1.008 PASS 5 144 PASS PASS PASS_at_T_(2/3) -ambiguous u-osmol skipped NA NA NA all mosm/kgh2o 95.64 {mosm/kgh2o:95.64,mo/kgh2o:3.88,form:0.35} mosm/kgh2o 2913 7279 [175,233.4,281,323,368,412,464,534,638] [171,228,276,320,367,417,474,544,645] 0.01897 0.3605 FAIL -0.5542 0.237 PASS 1 375 PASS PASS PASS_at_T_(2/3) -ambiguous li-igg-ind skipped NA NA NA all osuus 80.28 {osuus:80.28,index:10.18,ratio:8.34} osuus 2901 741 [0.41,0.44,0.47,0.49,0.51,0.54,0.59,0.69,0.99] [0.44,0.47,0.48,0.49,0.5,0.52,0.55,0.61,0.83] 0.1172 6.8 PASS 3.409 3.18 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) -ambiguous b-mono skipped NA NA NA all e9/l 93.53 {e9/l:93.53,%:6.47} e9/l 2899 66813 [0.4,0.5,0.5,0.6,0.6,0.7,0.83,0.92,1.1] [0.32,0.4,0.48,0.5,0.59,0.61,0.7,0.8,0.92] 0.1804 78.87 PASS 10.97 26.73 FAIL 0.01 0.45 PASS PASS PASS_at_KS_(2/3) -ambiguous p-cmvnh skipped NA NA NA all iu/ml 82.84 {iu/ml:82.84,u/ml:17.16} iu/ml 2630 7076 [45,64,90.7,130,180,270,530,1100,4600] [41,54,72,101,153,234,410.5,849,2735] 0.07093 8.109 PASS 3.115 2.73 FAIL 27 327 PASS PASS PASS_at_KS_(2/3) -ambiguous u-veri-o skipped NA NA NA all form 97.62 {form:97.62,u/field:2.38} form 2524 41 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01783 -0 FAIL 2.933 2.469 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-tpoab skipped NA NA NA all iu/ml 58.56 {iu/ml:58.56,u/ml:41.28,form:0.11} iu/ml 2449 7169 [0.4,6,13.74,37,70,140.9,250,418.2,695.4] [4,8,13,31,41,64,140,271.4,546] 0.1186 22.1 PASS 7.955 14.63 FAIL 29 108 PASS PASS PASS_at_KS_(2/3) -ambiguous p-tni split_by_score 0.3025 0.3568 0 low ng/l 89.7 {ng/l:89.7,ug/l:10.3} ng/l 520 218179 [0,0.006,0.0197,0.04,0.05,0.06,0.07,0.1,0.15] [4,5,7,10,15,24,46,119,764] 1 300 FAIL -49.15 300 FAIL 14.95 33 PASS PASS PASS_at_MAD_(1/3) -ambiguous p-tni split_by_score 0.3025 0.3568 0 high ng/l 89.7 {ng/l:89.7,ug/l:10.3} ng/l 1889 218179 [3,4,6,9,13,23,36.6,73,201.4] [4,5,7,10,15,24,46,119,764] 0.09576 14.67 PASS -14.21 43.5 FAIL 2 33 PASS PASS PASS_at_KS_(2/3) -ambiguous u-prot split_by_score 11.23 0.6347 0 low mg/l 55.44 {mg/l:55.44,g/l:44.55,mg/dl:0} mg/l 2060 14966 [0,0.09,0.1,0.2,0.3,0.4,0.7,1,1.807] [65,82,99,119,144,181,241,386,961] 0.9994 300 FAIL -23.1 115.3 FAIL 143.7 207 PASS PASS PASS_at_MAD_(1/3) -ambiguous u-prot split_by_score 11.23 0.6347 0 high mg/l 55.44 {mg/l:55.44,g/l:44.55,mg/dl:0} mg/l 259 14966 [34,50,71.4,76.2,89,101.8,131,196.2,412.4] [65,82,99,119,144,181,241,386,961] 0.292 19.04 PASS -7.437 12.28 FAIL 55 207 PASS PASS PASS_at_KS_(2/3) -ambiguous s-hcg-b-v skipped NA NA NA all ug/l 93.46 {ug/l:93.46,pmol/l:6.48,iu/l:0.02} ug/l 2184 15974 [21,30,37,45,53,63,76,95,127.4] [22.69,30.8,38,45.3,54,63.9,76,93,123] 0.01979 0.3631 FAIL 1.734 1.08 PASS 1 69 PASS PASS PASS_at_T_(2/3) -ambiguous s-mypnabm skipped NA NA NA all index 56.62 {index:56.62,s/co:42.67,form:0.63} index 2145 1445 [1,1.58,2,2.5,3,3.5,4.5,5.8,8.16] [1.5,2.2,2.8,3.4,4.2,5.2,6.6,8.4,11] 0.1865 25.99 PASS -11.33 28.4 FAIL 1.2 6.3 PASS PASS PASS_at_KS_(2/3) -ambiguous l-mon skipped NA NA NA all % 88.17 {%:88.17,e9/l:11.83} % 2104 12735 [4,8,11,12,12,13,14,15,16] [6,7,7.5,8,8.7,9,10,10.7,12] 0.5543 300 FAIL 24.12 114.2 FAIL 3.3 4.8 PASS PASS PASS_at_MAD_(1/3) -ambiguous pt-ekg-12 skipped NA NA NA all form 80.56 {form:80.56,tehtu:16.67,u:2.78} form 2052 58 [0,0,0,0,0,0,1,1,1] [0,0,0,0,0,0,48.5,1.029e+05,2.109e+05] 0.3239 5.039 FAIL -3.733 3.359 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-enaab skipped NA NA NA all u/ml 87.7 {u/ml:87.7,ratio:12.2,titre:0.1} u/ml 1973 1690 [0.1,0.1,0.16,0.2,0.2,0.2,0.3,0.4,0.7] [0.1,0.1,0.2,0.2,0.2,0.2,0.3,0.4,1.2] 0.05344 1.978 PASS -3.039 2.622 FAIL 0 0.3 PASS PASS PASS_at_KS_(2/3) -ambiguous s-dmklots split_by_score 22.05 0.9235 0 low nmol/l 61.43 {nmol/l:61.43,umol/l:38.41,âumol/l:0.14} nmol/l 516 13627 [0.4,0.5,0.69,0.8,0.9,1,1,1.2,1.4] [349,489.2,603,718,842,973,1127,1319,1617] 0.9991 300 FAIL -210 300 FAIL 841.1 981 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-dmklots split_by_score 22.05 0.9235 0 high nmol/l 61.43 {nmol/l:61.43,umol/l:38.41,âumol/l:0.14} nmol/l 1421 13627 [386,542,698,816,928,1061,1226,1420,1707] [349,489.2,603,718,842,973,1127,1319,1617] 0.0867 8.139 PASS 5.861 8.258 FAIL 86 981 PASS PASS PASS_at_KS_(2/3) -ambiguous p-pct skipped NA NA NA all ug/l 93.91 {ug/l:93.91,ng/ml:6.09} ug/l 1917 23100 [0.05,0.07,0.09,0.11,0.14,0.18,0.28,0.51,1.33] [0.07,0.1,0.14,0.2,0.28,0.42,0.72,1.5,5.461] 0.2222 76.53 PASS -1.105 0.5702 PASS 0.14 0.6 PASS PASS PASS_at_KS_(3/3) -ambiguous s-pr3ab skipped NA NA NA all iu/ml 75.45 {iu/ml:75.45,u/ml:23.28,kiu/l:1.27} iu/ml 1866 2324 [2.55,3.6,5,6.9,9.85,15,26,39,66] [2.5,4.1,6.1,8.7,13,19,27,41,73] 0.07762 5.149 PASS -2.413 1.799 FAIL 3.15 29.1 PASS PASS PASS_at_KS_(2/3) -ambiguous s-crp-o skipped NA NA NA all mg/l 88.8 {mg/l:88.8,form:10.67,u/ml:0.35} mg/l 1736 2521 [5,7,10.05,14,19,28,38,57,94] [5,5,5.6,8,10,15,22,35,64] 0.2009 36.05 PASS 10.38 24.11 FAIL 9 15 PASS PASS PASS_at_KS_(2/3) -ambiguous b-tbifng skipped NA NA NA all iu/ml 96.03 {iu/ml:96.03,iu/l:3.93,form:0.03} iu/ml 1724 2858 [0,0,0,0,0.01,0.01,0.02,0.04,0.36] [0,0,0,0,0,0.01,0.01,0.03,0.09] 0.1051 10.07 PASS 3.322 3.043 FAIL 0.01 0 FAIL PASS PASS_at_KS_(1/3) -ambiguous du-prot split_by_score 15.1 0.6975 0 low mg 65.4 {mg:65.4,g:32.31,mg/24h:1.32} mg 915 9936 [0.13,0.2,0.3,0.436,0.6,0.8,1.1,1.71,3] [98,151,250,415,666,1040,1630,2570,4429] 0.997 300 FAIL -65.65 300 FAIL 665.4 1659 PASS PASS PASS_at_MAD_(1/3) -ambiguous du-prot split_by_score 15.1 0.6975 0 high mg 65.4 {mg:65.4,g:32.31,mg/24h:1.32} mg 802 9936 [101,155.2,243.9,362,500,688.4,1027,1782,3480] [98,151,250,415,666,1040,1630,2570,4429] 0.1102 7.577 PASS -5.619 7.608 FAIL 166 1659 PASS PASS PASS_at_KS_(2/3) -ambiguous s-chpnabm bimodal 0.9363 0.6431 0 low index 96.11 {index:96.11,u/ml:2.63,titre:0.69} index 682 841 [0.08,0.102,0.13,0.144,0.17,0.2,0.25,0.298,0.37] [0.05,0.07,0.08,0.1,0.12,0.14,0.17,0.21,0.29] 0.2482 20.15 PASS -0.676 0.3017 PASS 0.05 0.15 PASS PASS PASS_at_KS_(3/3) -ambiguous s-chpnabm bimodal 0.9363 0.6431 0 high index 96.11 {index:96.11,u/ml:2.63,titre:0.69} index 672 841 [2.3,3,3.5,4,4.5,5.2,6.2,7.5,9.99] [0.05,0.07,0.08,0.1,0.12,0.14,0.17,0.21,0.29] 0.9869 300 FAIL 19.23 65.74 FAIL 4.38 0.15 FAIL FAIL FAIL_at_MAD_(0/3) -ambiguous b-b-cd19 skipped NA NA NA all e9/l 66.67 {e9/l:66.67,e6/l:33.33} e9/l 1316 1826 [0,0,0,0.02,0.065,0.13,0.2,0.31,0.46] [0,0,0,0.01,0.06,0.13,0.2,0.29,0.47] 0.02213 0.07716 FAIL -2.042 1.384 FAIL 0.005 0.18 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-hepyabg skipped NA NA NA all u/ml 81.11 {u/ml:81.11,index:11,eiu:4.08} u/ml 1308 4091 [0.927,2.812,10,14,30,76.2,166.5,410,1600] [0.1,0.1,0.4,10,10.7,11.6,13.8,22.9,83] 0.3368 99.57 FAIL 12.38 32.66 FAIL 19.3 30.9 PASS PASS PASS_at_MAD_(1/3) -ambiguous s-chpnabg skipped NA NA NA all eiu 42.53 {eiu:42.53,u/ml:35.3,bu/ml:10.86} eiu 1294 1829 [4.2,7.8,10.2,12.5,15.8,32,64,81.8,128] [45,52,60,70,82,95,114,141,184] 0.5852 240.5 FAIL -23.19 108.3 FAIL 66.2 90 PASS PASS PASS_at_MAD_(1/3) -ambiguous i-stathct bimodal 0.8089 0.9655 0 low %pcv 60.91 {%pcv:60.91,%:35.45,mmol/l:1.82} %pcv 1018 67 [0.33,0.36,0.39,0.4,0.41,0.43,0.44,0.46,0.49] [34.6,37,38,40,41,42,44,46,46.4] 1 107.6 FAIL -53.01 55.1 FAIL 40.59 12 FAIL FAIL FAIL_at_MAD_(0/3) -ambiguous i-stathct bimodal 0.8089 0.9655 0 high %pcv 60.91 {%pcv:60.91,%:35.45,mmol/l:1.82} %pcv 222 67 [32,35.2,38,40,41,42,44,46,47] [34.6,37,38,40,41,42,44,46,46.4] 0.0712 0.0288 FAIL -0.7825 0.3611 PASS 0 12 PASS PASS PASS_at_T_(2/3) -ambiguous u-epitel bimodal 1.004 0.7048 0 low /sunf 95.22 {/sunf:95.22,sunf:4.78} /sunf 902 1316 [0,0,0,0,0,1,1,1,1] [0,0,0,0,0,0,0,1,2] 0.2103 20.48 PASS -1.413 0.8017 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -ambiguous u-epitel bimodal 1.004 0.7048 0 high /sunf 95.22 {/sunf:95.22,sunf:4.78} /sunf 218 1316 [2,2,2,2,2,3,3,4,5] [0,0,0,0,0,0,0,1,2] 0.8685 154 FAIL 19.8 52.93 FAIL 2 0 FAIL FAIL FAIL_at_MAD_(0/3) -ambiguous c-reaktiivinenproteiini,vieritutkimus,plasmasta skipped NA NA NA all mg/l 95 {mg/l:95,1:5} mg/l 1118 38 [3.2,6,9.01,14,20,29,41,62,95] [5.85,6.64,8.47,11,15,22.8,56.2,59.6,94.4] 0.1044 0.1088 FAIL 0.1372 0.04983 PASS 5 27.75 PASS PASS PASS_at_T_(2/3) -ambiguous s-gadab skipped NA NA NA all iu/ml 77.97 {iu/ml:77.97,ru:20.5,u/ml:1.16} iu/ml 1035 1685 [0.1,0.1,1,1,1,1,3.8,22.2,136] [1,1,1,1,1,2,11.8,55,207.6] 0.2763 42.88 PASS -1.673 1.025 PASS 0 0 PASS PASS PASS_at_KS_(3/3) -ambiguous s-hbsab skipped NA NA NA all miu/ml 70.21 {miu/ml:70.21,iu/l:16.15,u/l:12.92} miu/ml 1022 6885 [15.87,27,43,69.72,100.1,153.2,230,330.8,560] [19,32,50,77,122,186,280,418,638.6] 0.05887 2.398 PASS -3.896 3.99 FAIL 21.9 294 PASS PASS PASS_at_KS_(2/3) +TYPE TEST_NAME BIMODAL_STATUS BIMODAL_SEP BIMODAL_BC BIMODAL_DIP_P SCORE_GLOBAL SCORE_SPLIT SCORE_IMPROVEMENT SUB_DIST CUTOFF UNIT UNIT_PREVALENCE PREVALENCE_DICT N_CANDIDATE N_TARGET CAND_DECILES TARG_DECILES KS_STAT KS_MLOGP KS_PASS T_STAT T_MLOGP T_PASS MAD_DIST MAD_THRESHOLD MAD_PASS OUTCOME NOTES +unambiguous b-eryt NA NA NA NA NA NA NA all inf e12/l 99.99 {e12/l:99.99,%:0.01,e9/l:0} 2702234 8026175 [3.25,3.63,3.9,4.1,4.28,4.44,4.6,4.79,5.04] [3.3,3.7,3.99,4.2,4.35,4.5,4.67,4.83,5.1] 0.05101 300 PASS -81.68 300 FAIL 0.07 1.35 PASS PASS PASS_at_KS_(2/3) +unambiguous p-kol-hdl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 61142 221234 [0.97,1.09,1.2,1.3,1.4,1.51,1.64,1.8,2.03] [0.96,1.09,1.2,1.3,1.4,1.51,1.63,1.79,2.02] 0.006651 1.542 PASS 3.266 2.963 FAIL 0 0.84 PASS PASS PASS_at_KS_(2/3) +unambiguous p-t4v NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100} 20621 90249 [12.2,13.4,14.2,14.9,15.6,16.3,17.2,18.3,20] [12.7,13.8,14.6,15.3,16,16.7,17.5,18.5,20] 0.05243 39.81 PASS -10.15 23.44 FAIL 0.4 5.7 PASS PASS PASS_at_KS_(2/3) +unambiguous s-iglck-v NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 7877 39042 [9.6,13.9,18.4,23.5,30,40.1,55.8,89.68,220] [7.8,12.1,16.2,21,27.1,35.7,50.3,81.2,172] 0.05025 14.1 PASS 3.239 2.92 FAIL 2.9 49.8 PASS PASS PASS_at_KS_(2/3) +unambiguous b-crp NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 3350 2366 [5,7,9,12,17,24,35,54,87] [6,8,9,13,18,25,35,55,90] 0.09378 10.34 PASS -1.146 0.5987 PASS 1 33 PASS PASS PASS_at_KS_(3/3) +unambiguous s-tfr NA NA NA NA NA NA NA all inf mg/l 99.99 {mg/l:99.99,mg:0.01} 2018 75736 [1.8,2.2,2.6,3.1,3.6,4.2,5.1,6.3,8.1] [1,1.2,1.5,1.9,2.4,2.8,3.3,4.1,5.6] 0.2886 144.8 PASS 20.34 83.32 FAIL 1.2 3.3 PASS PASS PASS_at_KS_(2/3) +unambiguous s-mkomp-4 NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1434 25572 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.000743 -0 FAIL -1.039 0.5247 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous b-crp-pik NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1059 353 [7,10,14,19,25,34,46,60,97] [9,13,17,23,30,40,51.8,72,105.8] 0.08782 1.486 PASS -2.634 2.061 FAIL 5 54 PASS PASS PASS_at_KS_(2/3) +unambiguous s-psa-suh NA NA NA NA NA NA NA all inf % 99.24 {%:99.24,ug/l:0.75,ug:0.01} 699 15340 [0.33,7.684,10,11,13,14,15,20,28] [11,14.18,17,19,21,24,26.95,30.83,37] 0.4731 137.3 FAIL -23.09 89.42 FAIL 8 18 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-cl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,%:0,kpa:0} 503 441201 [96.2,100,102,104,105,106,107,108,110] [98,101,103,104,105,107,108,109,111] 0.07716 2.32 PASS -3.598 3.453 FAIL 0 9 PASS PASS PASS_at_KS_(2/3) +ambiguous b-hkr split_by_score 0.8595 0.9783 0 0.1094 0.04121 0.6232 low 0.8595 osuus 46.72 {%:53.16,osuus:46.72,fl:0.08} 1558906 4240703 [0.32,0.35,0.37,0.386,0.4,0.41,0.42,0.44,0.46] [0.31,0.34,0.36,0.38,0.39,0.41,0.42,0.44,0.46] 0.03919 300 PASS 10.5 25.04 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +ambiguous b-hkr split_by_score 0.8595 0.9783 0 0.1094 0.04121 0.6232 high inf % 53.16 {%:53.16,osuus:46.72,fl:0.08} 191557 4824770 [32,34,37,38,39,41,42,43,45] [30,33,36,38,39,41,42,43,45] 0.05765 300 PASS 53.64 300 FAIL 0 12 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tt-inr skipped NA NA NA 0.1171 0.21 -0.7933 all inf inr 93.35 {inr:93.35,form:6.65,1:0.01} 1026823 339780 [1,1.1,1.2,1.6,2,2.2,2.5,2.7,3.1] [1,1,1.1,1.2,1.5,2,2.3,2.6,3] 0.1171 300 PASS 97.96 300 FAIL 0.5 1.5 PASS PASS PASS_at_KS_(2/3) +ambiguous s-ph skipped NA NA NA 0.1458 0.1458 -1.236e-05 all inf 1 83.33 {1:83.33,ph:16.67} 396270 140 [7.34,7.36,7.37,7.38,7.39,7.41,7.42,7.43,7.45] [7.36,7.38,7.39,7.4,7.405,7.42,7.42,7.43,7.45] 0.1458 2.334 PASS -2.552 1.929 FAIL 0.015 0.045 PASS PASS PASS_at_KS_(2/3) +ambiguous b-eos skipped NA NA NA 0.06737 0.1114 -0.6536 all inf e9/l 97.68 {e9/l:97.68,%:2.3,e6/l:0.02} 382440 1092967 [0.01,0.04,0.08,0.11,0.14,0.18,0.22,0.29,0.42] [0.02,0.07,0.1,0.12,0.15,0.19,0.23,0.3,0.4] 0.06737 300 PASS 2.498 1.903 FAIL 0.01 0.24 PASS PASS PASS_at_KS_(2/3) +ambiguous ab-ph skipped NA NA NA 0.1419 0.4469 -2.149 all inf ph 72.83 {ph:72.83,form:26.24,mmol/l:0.44} 380651 2975 [7.33,7.36,7.39,7.4,7.42,7.43,7.45,7.46,7.49] [7.37,7.39,7.41,7.42,7.43,7.44,7.45,7.47,7.48] 0.1419 51.61 PASS -14.52 45.54 FAIL 0.01 0.09 PASS PASS PASS_at_KS_(2/3) +ambiguous b-monos skipped NA NA NA 0.05309 0.2645 -3.983 all inf e9/l 97.82 {e9/l:97.82,%:2.18} 373740 965697 [0.34,0.42,0.47,0.53,0.58,0.65,0.72,0.82,0.98] [0.32,0.4,0.46,0.5,0.57,0.61,0.7,0.78,0.92] 0.05309 300 PASS 41.14 300 FAIL 0.01 0.45 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tsh skipped NA NA NA 0.03165 0.1393 -3.401 all inf mu/l 97.24 {mu/l:97.24,miu/l:2.41,mlu/l:0.35} 344154 1315114 [0.48,0.93,1.26,1.56,1.89,2.2,2.62,3.27,4.4] [0.53,0.92,1.21,1.5,1.8,2.1,2.51,3.1,4.2] 0.03165 237.1 PASS -24.22 128.8 FAIL 0.09 2.43 PASS PASS PASS_at_KS_(2/3) +ambiguous b-ly skipped NA NA NA 0.05066 0.4815 -8.504 all inf e9/l 97.41 {e9/l:97.41,%:2.59} 335323 784182 [0.8,1.07,1.28,1.48,1.67,1.89,2.13,2.44,2.97] [0.9,1.16,1.38,1.56,1.74,1.94,2.18,2.48,2.94] 0.05066 300 PASS -1.136 0.592 PASS 0.07 1.56 PASS PASS PASS_at_KS_(3/3) +ambiguous u-suhti skipped NA NA NA 0.08946 0.09035 -0.01002 all inf kg/l 91.82 {kg/l:91.82,g/ml:6.83,ratio:1.26} 261486 41398 [1.01,1.013,1.015,1.015,1.018,1.02,1.02,1.024,1.026] [1.01,1.01,1.013,1.015,1.015,1.02,1.02,1.021,1.025] 0.1232 300 PASS -0.627 0.2752 PASS 0.003 0.015 PASS PASS PASS_at_KS_(3/3) +ambiguous u-keto-o skipped NA NA NA 0.00291 0.00291 -2.615e-05 all inf estimate 94.61 {estimate:94.61,l:4.7,form:0.69} 49568 133623 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.00291 0.03687 FAIL 5.854 8.315 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) diff --git a/scripts/injection/data/plot_data.json b/scripts/injection/data/plot_data.json new file mode 100644 index 0000000..22d1239 --- /dev/null +++ b/scripts/injection/data/plot_data.json @@ -0,0 +1 @@ +{"b-eryt": {"outcome": "PASS", "decided_by": "KS", "prevalence": "{e12/l:99.99,%:0.01,e9/l:0}", "n_candidate": 2702234, "n_target": 8026175, "ecdf": {"c_x": [-10.0, 2.52, 2.69, 2.8, 2.89, 2.9699999999999998, 3.03, 3.1, 3.15, 3.2, 3.26, 3.3, 3.34, 3.39, 3.42, 3.46, 3.5, 3.5300000000000002, 3.57, 3.6, 3.63, 3.66, 3.7, 3.7199999999999998, 3.74, 3.77, 3.8, 3.82, 3.85, 3.87, 3.9, 3.91, 3.94, 3.96, 3.99, 4.0, 4.02, 4.05, 4.07, 4.09, 4.1, 4.12, 4.14, 4.16, 4.18, 4.2, 4.21, 4.23, 4.25, 4.27, 4.29, 4.3, 4.31, 4.33, 4.35, 4.37, 4.39, 4.4, 4.41, 4.43, 4.45, 4.47, 4.49, 4.5, 4.5, 4.52, 4.54, 4.5600000000000005, 4.58, 4.6, 4.61, 4.63, 4.65, 4.67, 4.6899999999999995, 4.7, 4.71, 4.74, 4.76, 4.78, 4.8, 4.82, 4.84, 4.87, 4.9, 4.91, 4.9399999999999995, 4.98, 5.0, 5.04, 5.08, 5.11, 5.16, 5.2, 5.26, 5.32, 5.4, 5.52, 5.7, 10.0], "c_y": [2e-05, 0.01012, 0.02022, 0.03032, 0.04042, 0.05052, 0.06062, 0.07072, 0.08082, 0.09092, 0.10102, 0.11112, 0.12122, 0.13132, 0.14142, 0.15152, 0.16162, 0.17172, 0.18182, 0.19192, 0.20202, 0.21212, 0.22222, 0.23232, 0.24242, 0.25254, 0.26264, 0.27274, 0.28284, 0.29294, 0.30304, 0.31314, 0.32324, 0.33334, 0.34344, 0.35354, 0.36364, 0.37374, 0.38384, 0.39394, 0.40404, 0.41414, 0.42424, 0.43434, 0.44444, 0.45454, 0.46464, 0.47474, 0.48484, 0.49494, 0.50506, 0.51516, 0.52526, 0.53536, 0.54546, 0.55556, 0.56566, 0.57576, 0.58586, 0.59596, 0.60606, 0.61616, 0.62626, 0.63636, 0.64646, 0.65656, 0.66666, 0.67676, 0.68686, 0.69696, 0.70706, 0.71716, 0.72726, 0.73736, 0.74746, 0.75758, 0.76768, 0.77778, 0.78788, 0.79798, 0.80808, 0.81818, 0.82828, 0.83838, 0.84848, 0.85858, 0.86868, 0.87878, 0.88888, 0.89898, 0.90908, 0.91918, 0.92928, 0.93938, 0.94948, 0.95958, 0.96968, 0.97978, 0.98988, 1.0], "t_x": [1.1400000000000001, 2.6, 2.77, 2.89, 2.98, 3.04, 3.1, 3.19, 3.22, 3.3, 3.33, 3.39, 3.42, 3.48, 3.5, 3.55, 3.6, 3.61, 3.66, 3.7, 3.71, 3.75, 3.8, 3.8, 3.84, 3.88, 3.9, 3.91, 3.94, 3.98, 4.0, 4.0, 4.03, 4.06, 4.1, 4.1, 4.11, 4.14, 4.16, 4.19, 4.2, 4.2, 4.22, 4.25, 4.27, 4.29, 4.3, 4.3, 4.32, 4.34, 4.37, 4.39, 4.4, 4.4, 4.42, 4.44, 4.46, 4.48, 4.5, 4.5, 4.51, 4.53, 4.55, 4.57, 4.59, 4.6, 4.6, 4.62, 4.64, 4.66, 4.6899999999999995, 4.7, 4.7, 4.71, 4.74, 4.77, 4.79, 4.8, 4.8, 4.83, 4.86, 4.89, 4.9, 4.91, 4.9399999999999995, 4.98, 5.0, 5.01, 5.05, 5.1, 5.1, 5.16, 5.2, 5.23, 5.3, 5.36, 5.42, 5.53, 5.7, 9.2], "t_y": [2e-05, 0.01012, 0.02022, 0.03032, 0.04042, 0.05052, 0.06062, 0.07072, 0.08082, 0.09092, 0.10102, 0.11112, 0.12122, 0.13132, 0.14142, 0.15152, 0.16162, 0.17172, 0.18182, 0.19192, 0.20202, 0.21212, 0.22222, 0.23232, 0.24242, 0.25254, 0.26264, 0.27274, 0.28284, 0.29294, 0.30304, 0.31314, 0.32324, 0.33334, 0.34344, 0.35354, 0.36364, 0.37374, 0.38384, 0.39394, 0.40404, 0.41414, 0.42424, 0.43434, 0.44444, 0.45454, 0.46464, 0.47474, 0.48484, 0.49494, 0.50506, 0.51516, 0.52526, 0.53536, 0.54546, 0.55556, 0.56566, 0.57576, 0.58586, 0.59596, 0.60606, 0.61616, 0.62626, 0.63636, 0.64646, 0.65656, 0.66666, 0.67676, 0.68686, 0.69696, 0.70706, 0.71716, 0.72726, 0.73736, 0.74746, 0.75758, 0.76768, 0.77778, 0.78788, 0.79798, 0.80808, 0.81818, 0.82828, 0.83838, 0.84848, 0.85858, 0.86868, 0.87878, 0.88888, 0.89898, 0.90908, 0.91918, 0.92928, 0.93938, 0.94948, 0.95958, 0.96968, 0.97978, 0.98988, 1.0], "ks_marker": {"x": 4.09, "y_lo": 0.34, "y_hi": 0.4}, "ks": {"stat": 0.05101436343880278, "mlogp": 300.0, "passed": true}}, "kde_linear": {"c_x": [-10.0, -9.746835443037975, -9.49367088607595, -9.240506329113924, -8.987341772151899, -8.734177215189874, -8.481012658227847, -8.227848101265822, -7.974683544303797, -7.7215189873417724, -7.468354430379747, -7.215189873417721, -6.962025316455696, -6.708860759493671, -6.455696202531645, -6.20253164556962, -5.949367088607595, -5.69620253164557, -5.443037974683544, -5.189873417721518, -4.936708860759493, -4.6835443037974684, -4.430379746835443, -4.177215189873417, -3.924050632911392, -3.670886075949367, -3.4177215189873413, -3.1645569620253156, -2.9113924050632907, -2.6582278481012658, -2.40506329113924, -2.1518987341772142, -1.8987341772151893, -1.6455696202531644, -1.3924050632911396, -1.139240506329113, -0.886075949367088, -0.6329113924050631, -0.37974683544303645, -0.12658227848101156, 0.12658227848101333, 0.3797468354430382, 0.6329113924050631, 0.8860759493670898, 1.1392405063291147, 1.3924050632911396, 1.6455696202531662, 1.898734177215191, 2.151898734177216, 2.405063291139241, 2.6582278481012658, 2.9113924050632924, 3.1645569620253173, 3.417721518987342, 3.670886075949369, 3.9240506329113938, 4.177215189873419, 4.4303797468354436, 4.6835443037974684, 4.936708860759495, 5.18987341772152, 5.443037974683545, 5.6962025316455716, 5.949367088607596, 6.202531645569621, 6.455696202531648, 6.708860759493671, 6.962025316455698, 7.215189873417721, 7.4683544303797476, 7.721518987341774, 7.974683544303797, 8.227848101265824, 8.48101265822785, 8.734177215189874, 8.9873417721519, 9.240506329113927, 9.49367088607595, 9.746835443037977, 10.0], "c_y": [9.922415045081634e-05, 6.986473986648042e-07, 2.4388215156800385e-13, 4.2206885239475856e-24, 3.621328341237307e-39, 1.5404010920594975e-58, 3.248486351682615e-82, 3.396327716887599e-110, 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b/scripts/injection/data/summary_table.md index 06622f2..4c30f25 100644 --- a/scripts/injection/data/summary_table.md +++ b/scripts/injection/data/summary_table.md @@ -1,9 +1,9 @@ -*Active threshold: 98% — min count: 1,000 — 542 TEST_NAMEs, 31,839,159 measurements* +*Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements* | Threshold | UNAMBIGUOUS test names | UNAMBIGUOUS measurements | AMBIGUOUS test names | AMBIGUOUS measurements | NO_DATA test names | NO_DATA measurements | | --- | ---: | ---: | ---: | ---: | ---: | ---: | -| 95% | 342 (63.1%) | 26,444,780 (83.1%) | 60 (11.1%) | 4,332,188 (13.6%) | 140 (25.8%) | 1,062,191 (3.3%) | -| 98% \* | 326 (60.1%) | 24,919,426 (78.3%) | 76 (14.0%) | 5,857,542 (18.4%) | 140 (25.8%) | 1,062,191 (3.3%) | -| 99% | 309 (57.0%) | 22,898,275 (71.9%) | 93 (17.2%) | 7,878,693 (24.7%) | 140 (25.8%) | 1,062,191 (3.3%) | -| 100% | 220 (40.6%) | 12,707,871 (39.9%) | 182 (33.6%) | 18,069,097 (56.8%) | 140 (25.8%) | 1,062,191 (3.3%) | -| **TOTAL** | **542** | | | || | +| 95% | 434 (60.7%) | 26,508,342 (82.9%) | 79 (11.0%) | 4,345,264 (13.6%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 98% \* | 413 (57.8%) | 24,979,594 (78.2%) | 100 (14.0%) | 5,874,012 (18.4%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 99% | 392 (54.8%) | 22,954,996 (71.8%) | 121 (16.9%) | 7,898,610 (24.7%) | 202 (28.3%) | 1,108,898 (3.5%) | +| 100% | 275 (38.5%) | 12,745,902 (39.9%) | 238 (33.3%) | 18,107,704 (56.7%) | 202 (28.3%) | 1,108,898 (3.5%) | +| **TOTAL** | **715** | | | || | diff --git a/scripts/injection/data/test_names_exploration_scatter.png b/scripts/injection/data/test_names_exploration_scatter.png index 8ebcd127083d6c86446cf3040cf84d4ad41f093f..db4fe599d33e0f546dca2458719654b58549dcdb 100644 GIT binary patch literal 118922 zcmd?QWn7eP_cjVDh=izsAbsDWgmiDH z9GsiQ1o+@D43eNqotdNiHik}qKTW6y`!7GjVYtMg^R0=qXQqO2q!N) zqqUoxldC8f7v$dyI2~QAxc*YQIRS2R$LWoZD-I6j1MC;BRpu`>99$e6xz{f=Jkz#j 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zAh_MC4482ps}Nd4M2`l59A!QMjx#d&(LfAVDDUm+Yhw!uLpPYT2ei?E_Z?tX7oPPuKN-O=fViy!rrS- z{&S17qkZ7XA5vZezFrdyTSZ+bUHV5NBKG136?8_x=nK%@gF7+gwYoOEL}2Ov60;7u zuM7EU+}vI)Qk**1WngGHU$`pa*tb4&R5(S4XD<=9#ix1PZipaTrv|_IBDA4D_X+FG zFqFaR{_A*-KXWD8Pe>oJD46m=_yg^IDRgrqI{GLTr4`|J}sJn=7Ly{@Mc?)MB zoNh6|1%cwOLr>McoIv*McWlQxP7|a+ypzagkD%am??sg z0A)7;uod_2G0&cL zr1Xj0Xz->kFJ|F13lNIU_b#W|k>SWd2|>Y^pK=9?17GRjupErJ4;ZNjl37P_28l>P zZQaAUrl3zyMG*}yP#}J8D3$;nG7KsL>VgeLp3Wnl)u0_fkZ;5p9W)>efvS*XTxavz z$Ek~>ixF8!_9XBPX{M#B+uatM+le4pL!@FOBQ7Ld&VvU%afBv}=%zCFP+v%fi@1%HpF#&P!ZY5H+A&w_yP zqCz-lN)3=|k+L44^a+D!t;Ufh;+4ep3wug0rQp=gP7z&wqWM;m_aSM_f2wtCTjrc|=6i->?7Ij*c!%**5 Date: Fri, 29 May 2026 21:40:11 +0000 Subject: [PATCH 12/20] deploy site from dev branch for now Co-Authored-By: Claude Sonnet 4.6 --- .github/workflows/deploy_site.yml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.github/workflows/deploy_site.yml b/.github/workflows/deploy_site.yml index 8b930f3..17c6f94 100644 --- a/.github/workflows/deploy_site.yml +++ b/.github/workflows/deploy_site.yml @@ -2,7 +2,7 @@ name: Deploy injection site on: push: - branches: [master] + branches: [dev] paths: - scripts/injection/data/** - scripts/injection/build_site.py From d491f1f4aa38f549e0a5bbb676d45f5f9dbcd2a6 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 21:48:50 +0000 Subject: [PATCH 13/20] fix: create _site dir before building Co-Authored-By: Claude Sonnet 4.6 --- .github/workflows/deploy_site.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/deploy_site.yml b/.github/workflows/deploy_site.yml index 17c6f94..f2eb568 100644 --- a/.github/workflows/deploy_site.yml +++ b/.github/workflows/deploy_site.yml @@ -35,6 +35,7 @@ jobs: - name: Build site run: | + mkdir -p _site python3 scripts/injection/build_site.py \ --data-dir scripts/injection/data \ --out-dir _site From 7f95d8243d9041383f6bf3530300e4a7d6858541 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 21:52:57 +0000 Subject: [PATCH 14/20] fix: trigger workflow on changes to workflow file itself Co-Authored-By: Claude Sonnet 4.6 --- .github/workflows/deploy_site.yml | 1 + 1 file changed, 1 insertion(+) diff --git a/.github/workflows/deploy_site.yml b/.github/workflows/deploy_site.yml index f2eb568..5a6ae31 100644 --- a/.github/workflows/deploy_site.yml +++ b/.github/workflows/deploy_site.yml @@ -7,6 +7,7 @@ on: - scripts/injection/data/** - scripts/injection/build_site.py - scripts/injection/README.md + - .github/workflows/deploy_site.yml permissions: contents: read From bbac31b7667fc53267eeef9da5df2b8980932aa7 Mon Sep 17 00:00:00 2001 From: piotor87 Date: Fri, 29 May 2026 21:55:35 +0000 Subject: [PATCH 15/20] fix: copy scatter PNG into out_dir so it's included in deployed artifact Co-Authored-By: Claude Sonnet 4.6 --- scripts/injection/build_site.py | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/scripts/injection/build_site.py b/scripts/injection/build_site.py index 5ce4b59..b6d7a33 100644 --- a/scripts/injection/build_site.py +++ b/scripts/injection/build_site.py @@ -15,6 +15,7 @@ import os import re import json +import shutil from pathlib import Path import markdown @@ -465,7 +466,10 @@ def _find_scatter(data_dir: Path, out_dir: Path) -> str: p = data_dir / "test_names_exploration_scatter.png" if p.exists(): - return os.path.relpath(p.resolve(), out_dir.resolve()) + dest = out_dir / "test_names_exploration_scatter.png" + if not dest.exists(): + shutil.copy2(p, dest) + return "test_names_exploration_scatter.png" return "" From 333eed6a4c282313badc38e5eebd7f9697fd9ee5 Mon Sep 17 00:00:00 2001 From: pete Date: Wed, 3 Jun 2026 15:58:12 +0300 Subject: [PATCH 16/20] new injection results --- scripts/injection/data/assignment_summary.md | 12 +- scripts/injection/data/injection_results.tsv | 508 +++++++++++++++++++ scripts/injection/data/plot_data.json | 2 +- scripts/injection/html/index.html | 70 +-- 4 files changed, 550 insertions(+), 42 deletions(-) diff --git a/scripts/injection/data/assignment_summary.md b/scripts/injection/data/assignment_summary.md index fe2ad54..d395d3b 100644 --- a/scripts/injection/data/assignment_summary.md +++ b/scripts/injection/data/assignment_summary.md @@ -2,10 +2,10 @@ Assignment summary (successfully assigned) - UNAMBIGUOUS AMBIGUOUS NO_DATA TOTAL - names meas names meas names meas names meas - ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- -All 10/10 2,800,937/2,800,937 10/10 5,300,918/5,300,918 28/202 285,698/1,108,898 48/222 8,387,553/9,210,753 -OMOP-mapped 9/9 2,800,434/2,800,434 10/10 5,300,918/5,300,918 28/66 285,698/802,091 47/85 8,387,050/8,903,443 - ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- + UNAMBIGUOUS AMBIGUOUS NO_DATA TOTAL + names meas names meas names meas names meas + ------- --------------------- ------- --------------------- ------- --------------------- ------- --------------------- +All 403/413 24,956,931/24,979,594 100/100 5,874,012/5,874,012 28/202 285,698/1,108,898 531/715 31,116,641/31,962,504 +OMOP-mapped 359/367 24,839,646/24,860,173 82/82 5,815,545/5,815,545 28/66 285,698/802,091 469/515 30,940,889/31,477,809 + ------- --------------------- ------- --------------------- ------- --------------------- ------- --------------------- ``` diff --git a/scripts/injection/data/injection_results.tsv b/scripts/injection/data/injection_results.tsv index f5132f5..ba9dc14 100644 --- a/scripts/injection/data/injection_results.tsv +++ b/scripts/injection/data/injection_results.tsv @@ -1,13 +1,416 @@ TYPE TEST_NAME BIMODAL_STATUS BIMODAL_SEP BIMODAL_BC BIMODAL_DIP_P SCORE_GLOBAL SCORE_SPLIT SCORE_IMPROVEMENT SUB_DIST CUTOFF UNIT UNIT_PREVALENCE PREVALENCE_DICT N_CANDIDATE N_TARGET CAND_DECILES TARG_DECILES KS_STAT KS_MLOGP KS_PASS T_STAT T_MLOGP T_PASS MAD_DIST MAD_THRESHOLD MAD_PASS OUTCOME NOTES unambiguous b-eryt NA NA NA NA NA NA NA all inf e12/l 99.99 {e12/l:99.99,%:0.01,e9/l:0} 2702234 8026175 [3.25,3.63,3.9,4.1,4.28,4.44,4.6,4.79,5.04] [3.3,3.7,3.99,4.2,4.35,4.5,4.67,4.83,5.1] 0.05101 300 PASS -81.68 300 FAIL 0.07 1.35 PASS PASS PASS_at_KS_(2/3) +unambiguous b-leuk NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100,g/l:0,form:0} 2610059 7601140 [4.4,5.2,5.8,6.4,7,7.7,8.6,9.7,11.7] [4.3,5.1,5.7,6.3,6.9,7.5,8.3,9.5,11.5] 0.03003 300 PASS 40.72 300 FAIL 0.1 4.8 PASS PASS PASS_at_KS_(2/3) +unambiguous b-trom NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100,%:0,form:0} 2413303 7894206 [150,183,207,227,246,267,291,324,381] [154,187,209,229,247,267,291,321,374] 0.01194 228.8 PASS 15.29 52.07 FAIL 1 156 PASS PASS PASS_at_KS_(2/3) +unambiguous p-inr NA NA NA NA NA NA NA all inf inr 99.17 {inr:99.17,ng:0.52,form:0.31} 1094306 73174 [1.5,1.9,2.1,2.3,2.4,2.6,2.7,3,3.3] [1,1.3,1.9,2.1,2.3,2.4,2.6,2.8,3.2] 0.1414 300 PASS 69.28 300 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous b-hb NA NA NA NA NA NA NA all inf g/l 99.99 {g/l:99.99,e9/l:0.01,form:0} 895512 10047206 [106,116,124,129,133,137,142,147,154] [99,110,119,125,130,135,140,145,152] 0.07401 300 PASS 177.8 300 FAIL 3 39 PASS PASS PASS_at_KS_(2/3) +unambiguous e-mcv NA NA NA NA NA NA NA all inf fl 99.96 {fl:99.96,%:0.03,pg:0} 863209 10019368 [84.6,87,89,90,91,93,94,96,99] [85,87,89,90,91,93,94,96,99] 0.009422 61 PASS -18.11 72.59 FAIL 0 9 PASS PASS PASS_at_KS_(2/3) +unambiguous e-mch NA NA NA NA NA NA NA all inf pg 99.78 {pg:99.78,pg/cell:0.21,fl:0} 859269 10022306 [27,29,29,30,30,31,31,32,33] [28,29,29,30,30,31,31,32,33] 0.01713 201.5 PASS -5.64 7.768 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-gfreepi NA NA NA NA NA NA NA all inf ml/min/173m2 99.11 {ml/min/173m2:99.11,form:0.89} 752397 1889100 [39,51,59,67,74,80,86,92,101] [38,54,65,73,80,86,91,97,106] 0.09026 300 PASS 0.6265 0.2749 PASS 6 48 PASS PASS PASS_at_KS_(3/3) +unambiguous p-k NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mmol/mol:0,nmol/l:0} 701228 6736993 [3.5,3.7,3.8,3.9,4,4.1,4.2,4.3,4.5] [3.5,3.7,3.8,3.9,4,4.1,4.2,4.3,4.6] 0.04774 300 PASS 8.691 17.45 FAIL 0 0.9 PASS PASS PASS_at_KS_(2/3) +unambiguous b-neut NA NA NA NA NA NA NA all inf e9/l 98.61 {e9/l:98.61,%:1.39} 678979 1796762 [1.7,2.32,2.81,3.27,3.74,4.29,4.97,5.95,7.77] [1.68,2.28,2.73,3.19,3.63,4.17,4.8,5.74,7.5] 0.02295 225.1 PASS 26.64 155.6 FAIL 0.11 3.87 PASS PASS PASS_at_KS_(2/3) +unambiguous p-na NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mmol/:0,1:0} 615417 6700235 [134,137,138,139,140,141,142,142,144] [134,136,138,139,140,140,141,142,143] 0.08943 300 PASS 110.5 300 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous u-ph NA NA NA NA NA NA NA all inf form 98.78 {form:98.78,ph:1.22} 614126 18003 [5.5,5.5,6,6,6.5,7,7,7,7.5] [5,5,5,5.5,6,6,6.5,7,7] 0.2368 300 PASS 78.83 300 FAIL 0.5 3 PASS PASS PASS_at_KS_(2/3) +unambiguous p-krea NA NA NA NA NA NA NA all inf umol/l 99.98 {umol/l:99.98,umol:0.02,ml/min/173m2:0} 597169 7087388 [56,63,68,73,79,86,94,106,128] [53,60,65,70,76,82,90,104,135] 0.05594 300 PASS -81.6 300 FAIL 3 45 PASS PASS PASS_at_KS_(2/3) +unambiguous p-alat NA NA NA NA NA NA NA all inf u/l 100 {u/l:100,umol/l:0,mmol/l:0} 484108 4339404 [13,16,18,21,24,27,32,40,56] [13,16,18,21,24,28,33,42,61] 0.01793 121.3 PASS -61.36 300 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) +unambiguous e-rdw NA NA NA NA NA NA NA all inf % 100 {%:100} 445075 5838138 [13,13,13,14,14,14,15,15,17] [12.6,13,13,13.5,14,14,15,16,17] 0.04145 300 PASS -18.65 76.9 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-gluk NA NA NA NA NA NA NA all inf mmol/l 99.96 {mmol/l:99.96,nmol/l:0.04,mmol/:0} 377861 1527267 [5.2,5.5,5.7,5.9,6.1,6.4,6.7,7.2,8.2] [5,5.3,5.5,5.7,5.8,6.1,6.4,6.9,7.8] 5.211e-06 -0 FAIL -0.9174 0.445 PASS 0.3 1.5 PASS PASS PASS_at_T_(2/3) +unambiguous b-baso NA NA NA NA NA NA NA all inf e9/l 98.99 {e9/l:98.99,%:1.01} 358577 1025695 [0.01,0.02,0.03,0.03,0.04,0.04,0.05,0.06,0.08] [0,0.02,0.02,0.03,0.04,0.04,0.05,0.07,0.1] 0.06985 300 PASS 17 64.07 FAIL 0 0.06 PASS PASS PASS_at_KS_(2/3) +unambiguous b-hba1c NA NA NA NA NA NA NA all inf mmol/mol 99.68 {mmol/mol:99.68,mmol/m:0.17,mmol:0.07} 356117 1619587 [34,37,38,40,42,44,47,52,62] [33,35,37,38,40,42,44.8,50,60] 0.1172 300 PASS 68.38 300 FAIL 2 15 PASS PASS PASS_at_KS_(2/3) +unambiguous p-crp NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100,mg/ml:0,alle:0} 329485 3909221 [2,4,6,10,15,23,37,58,99] [3,5,8,13,21,34,52,81,133] 0.08114 300 PASS -122 300 FAIL 6 54 PASS PASS PASS_at_KS_(2/3) +unambiguous b-erblast NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 314346 313463 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.003567 1.435 PASS 8.538 16.86 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous e-mchc NA NA NA NA NA NA NA all inf g/l 100 {g/l:100,e9/l:0,form:0} 306131 6813807 [314,320,326,330,333,336,339,343,348] [315,321,325,328,331,333,337,340,346] 0.07143 300 PASS 35.87 280.8 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-kol-ldl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mmol/:0,mmoil/l:0} 300160 1258918 [1.6,2,2.2,2.5,2.8,3.1,3.4,3.78,4.2] [1.5,1.8,2.1,2.38,2.6,2.9,3.2,3.6,4.1] 0.07917 300 PASS 78.61 300 FAIL 0.2 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-kol NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mmol:0,mmol/:0} 246075 1160366 [3.4,3.8,4.1,4.5,4.8,5.1,5.4,5.8,6.3] [3.2,3.6,4,4.3,4.6,4.9,5.2,5.6,6.2] 0.08252 300 PASS 72.12 300 FAIL 0.2 2.4 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-trigly NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mmol/:0} 239400 1104071 [0.7,0.85,1,1.1,1.25,1.41,1.67,1.99,2.55] [0.7,0.82,0.96,1.1,1.21,1.4,1.6,1.89,2.4] 0.03363 193.1 PASS 21.77 104.2 FAIL 0.04 1.17 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-kol-hdl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mml/l:0,mmol:0} 235506 1110652 [0.96,1.1,1.2,1.31,1.42,1.54,1.68,1.85,2.11] [0.95,1.09,1.2,1.3,1.4,1.5,1.63,1.8,2.03] 0.03251 178.1 PASS 30.77 206.9 FAIL 0.02 0.84 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-gfre NA NA NA NA NA NA NA all inf ml/min/173m2 99.63 {ml/min/173m2:99.63,form:0.37,mi/min/173m2:0} 216785 1096392 [42,54,63,71,77,83,88,93,102] [41,57,67,75,82,87,92,98,106.1] 0.08308 300 PASS -56.47 300 FAIL 5 45 PASS PASS PASS_at_KS_(2/3) +unambiguous p-t4-v NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100,nmol/l:0,pmo/l:0} 203419 904186 [12,13,14,14.9,15.5,16.2,17,18.1,19.9] [12,13,14,14.7,15.2,16,17,18,19.5] 0.0401 231.7 PASS 21.9 105.5 FAIL 0.3 5.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-afos NA NA NA NA NA NA NA all inf u/l 100 {u/l:100,umol/l:0} 179506 2452551 [47,55,61,67,74,81,91,106,134] [49,57,64,70,77,85,95,111,151] 0.04779 300 PASS -42.81 300 FAIL 3 57 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-ph NA NA NA NA NA NA NA all inf ph 99.15 {ph:99.15,form:0.64,1:0.21} 174741 931 [7.3,7.33,7.35,7.37,7.38,7.39,7.41,7.42,7.45] [7.31,7.34,7.36,7.37,7.38,7.39,7.4,7.42,7.44] 0.06548 3.169 PASS -1.378 0.7736 PASS 0 0.09 PASS PASS PASS_at_KS_(3/3) +unambiguous b-erybla NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 169159 1041960 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.02442 75.13 PASS 19.22 81.51 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-eryt NA NA NA NA NA NA NA all inf e6/l 98.22 {e6/l:98.22,u/field:0.92,form:0.43} 157713 273727 [1,2,4,5,8,13,23,52,193] [2.2,4,6,7.8,10,13,19,30.9,86.7] 0.1553 300 PASS -5.124 6.523 FAIL 2 19.5 PASS PASS PASS_at_KS_(2/3) +unambiguous u-leuk NA NA NA NA NA NA NA all inf e6/l 99.11 {e6/l:99.11,u/field:0.6,/sunf:0.27} 156801 294204 [1,1,2,4,7,13,29,88,402] [0.8,1,2,3,5,8,16.8,46,216] 0.07322 300 PASS -3.965 4.134 FAIL 2 12 PASS PASS PASS_at_KS_(2/3) +unambiguous b-la NA NA NA NA NA NA NA all inf mm/h 99.95 {mm/h:99.95,mmol:0.03,form:0.01} 156217 1232795 [2,5,6,8,10,15,21,28,41] [2,4,5,7,9,12,16,25,38] 0.06215 300 PASS 1.287 0.7029 PASS 1 18 PASS PASS PASS_at_KS_(3/3) +unambiguous u-lier NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100,u/field:0} 155357 195506 [0,0,0,0,0,0,0,1,3] [0,0,0,0,0,0,0.13,0.81,1.22] 0.09197 300 PASS 48.69 300 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-levyep NA NA NA NA NA NA NA all inf e6/l 99.53 {e6/l:99.53,u/field:0.47} 135481 81771 [0,0,0,0,0,1,2,4,11] [0,0,0,0,1,1,2,4,9] 0.09894 300 PASS 5.548 7.539 FAIL 1 3 PASS PASS PASS_at_KS_(2/3) +unambiguous u-pienep NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 135163 65516 [0,0,0,0,0,1,1,2,4] [0,0,0,0,0,0.9,1,2,4] 0.05883 132.5 PASS -1.225 0.6567 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous cb-ph NA NA NA NA NA NA NA all inf ph 100 {ph:100} 104918 9565 [7.35,7.38,7.39,7.41,7.42,7.43,7.44,7.45,7.47] [7.35,7.37,7.39,7.41,7.42,7.43,7.44,7.46,7.48] 0.02779 5.587 PASS -0.9305 0.4533 PASS 0 0.09 PASS PASS PASS_at_KS_(3/3) +unambiguous p-gt NA NA NA NA NA NA NA all inf u/l 100 {u/l:100,mg/ml:0,mg/l:0} 103122 716550 [15,20,26,33,44,58,78,114,200] [15,19,23,29,36,47,65,100,195] 0.07536 300 PASS 5.969 8.621 FAIL 8 57 PASS PASS PASS_at_KS_(2/3) +unambiguous u-krea NA NA NA NA NA NA NA all inf mmol/l 98.91 {mmol/l:98.91,umol/l:1.09,g/l:0} 102588 389195 [3.3,4.4,5.3,6.3,7.4,8.7,10.3,12.8,18.2] [3.1,4.1,4.9,5.8,6.8,7.9,9.3,11.1,14.2] 0.06325 282.1 PASS 71.26 300 FAIL 0.6 7.8 PASS PASS PASS_at_KS_(2/3) +unambiguous hdl/kol NA NA NA NA NA NA NA all inf % 100 {%:100} 89962 130585 [21,25,28,30,33,36,39,42,47] [21,24,27,30,32,35,38,41,46] 0.033 50.09 PASS 15.48 53.27 FAIL 1 21 PASS PASS PASS_at_KS_(2/3) +unambiguous p-psa NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100,µh/l:0} 85734 353554 [0.36,0.61,0.89,1.2,1.62,2.2,3.02,4.4,6.9] [0.25,0.52,0.82,1.2,1.74,2.54,3.8,5.9,10.6] 0.06999 293.6 PASS -32.53 231.1 FAIL 0.12 4.08 PASS PASS PASS_at_KS_(2/3) +unambiguous fb-leuk NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 78470 326274 [4.5,5.2,5.7,6.2,6.7,7.3,8,8.9,10.4] [4.5,5.1,5.6,6.1,6.6,7.2,7.9,8.8,10.4] 0.01482 11.77 PASS 0.9066 0.4382 PASS 0.1 4.2 PASS PASS PASS_at_KS_(3/3) +unambiguous p-kol-ldl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 76361 340811 [1.3,1.5,1.7,2,2.2,2.5,2.9,3.3,3.8] [1.3,1.5,1.8,2,2.3,2.6,2.9,3.3,3.8] 0.01497 11.84 PASS -8.846 18.04 FAIL 0.1 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous b-tromb NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 75012 323035 [168,193,212,229,246,264,286,314,359] [163,190,210,228,245,263,284,313,361] 0.01738 15.68 PASS 4.206 4.584 FAIL 1 144 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ferrit NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 65282 414832 [12,19,28,39,54,77,111,168,282] [14,23,34,48,67,96,142,224,419] 0.06433 202.6 PASS -32.04 224.1 FAIL 13 147 PASS PASS PASS_at_KS_(2/3) +unambiguous p-kol NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 63596 235312 [3,3.4,3.7,4,4.3,4.6,4.9,5.3,5.9] [3,3.4,3.7,4,4.3,4.6,5,5.4,5.9] 0.02577 28.58 PASS -10.74 26.15 FAIL 0 2.4 PASS PASS PASS_at_KS_(2/3) unambiguous p-kol-hdl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 61142 221234 [0.97,1.09,1.2,1.3,1.4,1.51,1.64,1.8,2.03] [0.96,1.09,1.2,1.3,1.4,1.51,1.63,1.79,2.02] 0.006651 1.542 PASS 3.266 2.963 FAIL 0 0.84 PASS PASS PASS_at_KS_(2/3) +unambiguous p-trigly NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 60090 219531 [0.72,0.88,1,1.12,1.28,1.44,1.66,1.97,2.51] [0.7,0.84,0.97,1.1,1.24,1.4,1.62,1.92,2.49] 0.02559 26.55 PASS 3.328 3.058 FAIL 0.04 1.17 PASS PASS PASS_at_KS_(2/3) +unambiguous u-alb NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100,mg/ml:0,mg/mmol:0} 54491 245848 [3,4,5,7,9.4,14,24.3,45.9,123] [3.7,5,6,9,13,21.5,42,102,337] 0.09064 300 PASS -43.91 300 FAIL 3.6 27 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-be NA NA NA NA NA NA NA all inf mmol/l 99.98 {mmol/l:99.98,ml:0.01,%:0} 52627 328149 [-7.2,-4.9,-3.7,-2.8,-2.2,-1.6,-1.1,-0.7,-0.3] [-4.6,-2.4,-0.8,0.2,1,1.9,2.9,4.2,6.3] 0.5981 300 FAIL -216.4 300 FAIL 3.2 7.5 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-alb NA NA NA NA NA NA NA all inf g/l 100 {g/l:100,%:0} 51547 870387 [26,30,33,34.4,36,37,38,39.2,41] [25,29,32,34,35.6,37,38,39.4,41] 0.04602 89.32 PASS 17.96 71.18 FAIL 0.4 10.8 PASS PASS PASS_at_KS_(2/3) +unambiguous u-albkre NA NA NA NA NA NA NA all inf mg/mmol 100 {mg/mmol:100,g/mol:0} 51403 242629 [0.3,0.4,0.6,0.8,1.2,1.9,3.4,7,20.5] [0.3,0.5,0.7,1,1.6,2.9,6.2,16.1,60.6] 0.08722 280.5 PASS -1.503 0.8765 PASS 0.4 3.9 PASS PASS PASS_at_KS_(3/3) +unambiguous l-lymf(a) NA NA NA NA NA NA NA all inf % 100 {%:100} 50542 588720 [14,19,22,26,28,31,34,38,44] [12,17,21,24,27,30,34,38,44] 0.04828 94.06 PASS 21.39 100.4 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +unambiguous u-gluk-o NA NA NA NA NA NA NA all inf estimate 99.32 {estimate:99.32,form:0.67,A:0.01} 50039 123942 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01171 3.946 PASS 4.074 4.334 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous l-mono(a) NA NA NA NA NA NA NA all inf % 100 {%:100} 49676 588958 [6,7,8,8,9,10,11,12,13] [6,7,8,8,9,10,11,12,13] 0.01509 8.768 PASS -0.3816 0.1532 PASS 0 6 PASS PASS PASS_at_KS_(3/3) +unambiguous l-eos(a) NA NA NA NA NA NA NA all inf % 100 {%:100} 49313 92061 [0,1,2,2,2,3,4,5,6] [0,1,2,2,2,3,4,4,6] 0.0186 9.351 PASS 7.754 14.05 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous l-neut(a) NA NA NA NA NA NA NA all inf % 100 {%:100} 48854 590444 [41,47,51,54,58,61,64,68,74] [41,48,52,55,59,62,66,70,77] 0.0498 96.99 PASS -20.59 93.1 FAIL 1 27 PASS PASS PASS_at_KS_(2/3) +unambiguous u-nitr-o NA NA NA NA NA NA NA all inf estimate 99.34 {estimate:99.34,form:0.66,A:0} 48542 124895 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.0008223 -0 FAIL 3.955 4.116 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous l-baso(a) NA NA NA NA NA NA NA all inf % 100 {%:100} 48061 93247 [0,0,0,1,1,1,1,1,1] [0,0,1,1,1,1,1,1,1] 0.1053 300 PASS -33.15 238.8 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-be NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 46427 126442 [-7.4,-5.3,-4,-3.1,-2.4,-1.8,-1.2,-0.7,-0.3] [-3.4,-0.8,0.3,1,1.7,2.4,3.2,4.2,5.9] 0.7185 300 FAIL -239 300 FAIL 4.1 5.4 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-b12-tc2 NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100,>35:0} 46070 176282 [51,65,76,87,97,107,117,130,160] [52,66,76.7,86,95.1,105,114,124,138] 0.07646 185.4 PASS 24.8 134.4 FAIL 1.9 71.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-bil NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 45706 1372979 [5,6,7,8,9,11,13,17,26] [5,6,7,8,9,11,13,16.4,25] 0.03003 34.39 PASS -1.03 0.5186 PASS 0 9 PASS PASS PASS_at_KS_(3/3) +unambiguous u-suhtih NA NA NA NA NA NA NA all inf kg/l 99.91 {kg/l:99.91,ratio:0.09} 41978 4621 [1.009,1.011,1.013,1.015,1.016,1.018,1.02,1.022,1.025] [1.01,1.01,1.01,1.01,1.015,1.015,1.015,1.02,1.02] 0.2869 300 PASS 19.31 81.92 FAIL 0.001 0.015 PASS PASS PASS_at_KS_(2/3) +unambiguous p-probnp NA NA NA NA NA NA NA all inf ng/l 100 {ng/l:100} 41763 317468 [81,133,211,338,555,907,1400,2220,4148] [81,146,246,412,695,1144,1849,3080,6216] 0.06289 126.6 PASS -36.62 290.5 FAIL 140 1800 PASS PASS PASS_at_KS_(2/3) +unambiguous u-alb-o NA NA NA NA NA NA NA all inf estimate 99.75 {estimate:99.75,form:0.25,A:0} 41443 115398 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.0002578 -0 FAIL 0.961 0.4729 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous u-eryt-o NA NA NA NA NA NA NA all inf estimate 99.32 {estimate:99.32,form:0.68,eru/ul:0} 40464 103663 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01896 8.797 PASS 7.44 12.99 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-leuk-o NA NA NA NA NA NA NA all inf estimate 99.05 {estimate:99.05,form:0.86,u/field:0.05} 39068 102815 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.04043 39.92 PASS 8.452 16.53 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous p-psa-v NA NA NA NA NA NA NA all inf ug/l 99.99 {ug/l:99.99,form:0.01,%:0} 38748 112760 [0.22,0.34,0.44,0.54,0.65,0.78,0.92,1.11,1.54] [0.23,0.34,0.45,0.56,0.69,0.8,1,1.24,1.7] 0.03829 36.44 PASS -14.73 48.34 FAIL 0.04 0.96 PASS PASS PASS_at_KS_(2/3) +unambiguous p-d-25 NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100} 38104 55698 [47,58,66,74,80,88,96,107,124] [47,57,64,71,77,84,93,103,120] 0.04497 39.47 PASS 12.91 37.36 FAIL 3 54 PASS PASS PASS_at_KS_(2/3) +unambiguous s-k/l-s-v NA NA NA NA NA NA NA all inf ratio 99.15 {ratio:99.15,1:0.69,mg/l:0.16} 37831 2440 [0.17,0.77,1.02,1.21,1.4,1.63,2.01,3.43,14.3] [0.12,0.79,0.987,1.19,1.445,1.76,3.09,10,30.9] 0.09989 19.63 PASS 1.874 1.215 PASS 0.045 2.445 PASS PASS PASS_at_KS_(3/3) +unambiguous p-uraat NA NA NA NA NA NA NA all inf umol/l 98.74 {umol/l:98.74,mmol/l:1.26} 37337 226132 [246,288,322,353,383,416,450,492,549] [225,266,298,327,355,385,420,463,526] 0.09345 243.3 PASS 37.11 296.8 FAIL 28 234 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-be NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 36614 63821 [-6.7,-4.6,-3.3,-2.4,-1.6,-1,-0.6,-0.2,2] [-2.8,0,0.7,1.3,2,2.8,3.8,5.2,7.7] 0.6474 300 FAIL -155.1 300 FAIL 3.6 5.7 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-tfr NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 35728 152596 [2.1,2.5,2.9,3.2,3.6,4.1,4.8,5.8,7.5] [0.8,1.3,2.1,2.5,2.9,3.3,3.8,4.6,6.2] 0.2209 300 PASS 57.88 300 FAIL 0.7 3.9 PASS PASS PASS_at_KS_(2/3) +unambiguous p-gluk NA NA NA NA NA NA NA all inf mmol/l 99.96 {mmol/l:99.96,mmol:0.04,%:0} 34995 1187642 [5,5.5,5.8,6,6.4,7,7.6,8.8,11.4] [5.1,5.5,5.8,6.2,6.6,7.1,7.8,8.8,10.8] 0.05953 104.5 PASS 3.159 2.8 FAIL 0.2 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-tnt NA NA NA NA NA NA NA all inf ng/l 99.98 {ng/l:99.98,ug/l:0.02} 32887 400470 [7,9,11,15,18,23,30,42,74] [7,9,12,15,19,25,34,51,105] 0.04291 48.34 PASS -29.16 185.5 FAIL 1 33 PASS PASS PASS_at_KS_(2/3) +unambiguous l-monos NA NA NA NA NA NA NA all inf % 99.4 {%:99.4,e9/l:0.6} 31974 434312 [6,7,8,8,9,10,11,12,13] [5,7,7.4,8,9,10,10.1,11.7,13] 0.03102 24.6 PASS 2.538 1.953 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-ph NA NA NA NA NA NA NA all inf ph 100 {ph:100} 30367 986 [7.34,7.36,7.37,7.38,7.39,7.4,7.41,7.42,7.44] [7.38,7.4,7.41,7.42,7.43,7.43,7.44,7.45,7.47] 0.3802 123.9 FAIL 0.9998 0.4983 PASS 0.04 0.06 PASS PASS PASS_at_T_(2/3) +unambiguous ca++/7.40 NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 27423 98719 [1.18,1.2,1.2,1.22,1.23,1.25,1.27,1.3,1.33] [1.14,1.18,1.21,1.22,1.23,1.24,1.26,1.27,1.31] 0.1306 300 PASS 27.76 167.5 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous ca-ion NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 27272 99169 [1.18,1.2,1.21,1.23,1.24,1.26,1.28,1.3,1.32] [1.14,1.18,1.21,1.23,1.24,1.26,1.27,1.29,1.33] 0.1066 211.3 PASS 3.516 3.358 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous fe-folaat NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100} 27167 76563 [313.6,396.2,479,591,763,1023,1309,1617,2032] [354,452,568,727,968,1302,1580,1854,2290] 0.09833 168.5 PASS -31.8 219.1 FAIL 205 1626 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-folaat NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100} 26471 163828 [6.9,8.9,10.9,13.2,16.3,21,27.9,37.2,51] [7.5,9.7,11.9,14.2,17,20.8,25.9,32.9,42.44] 0.05394 57.34 PASS 11.64 30.51 FAIL 0.7 23.1 PASS PASS PASS_at_KS_(2/3) +unambiguous b-retik NA NA NA NA NA NA NA all inf e9/l 99.94 {e9/l:99.94,%:0.06} 26123 65705 [36.9,46,53.5,60.7,68,76.3,87.8,103.3,134.1] [37,47,54,61,68,76,86,101,130] 0.02002 6.213 PASS 1.564 0.9285 PASS 0 60 PASS PASS PASS_at_KS_(3/3) +unambiguous p-amyl NA NA NA NA NA NA NA all inf u/l 100 {u/l:100,umol/l:0} 25904 342833 [29,37,43,49,54,60,68,79,100] [26,34,40,46,52,59,68,80,104] 0.04508 42.25 PASS -10.49 25 FAIL 2 51 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ca NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 25414 398611 [2.19,2.25,2.28,2.31,2.34,2.37,2.4,2.44,2.51] [2.21,2.27,2.31,2.34,2.37,2.4,2.44,2.47,2.53] 0.1137 268.8 PASS -28.26 172.6 FAIL 0.03 0.24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca-ion NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mmol:0} 25366 460023 [1.15,1.19,1.21,1.22,1.24,1.25,1.27,1.3,1.34] [1.14,1.18,1.2,1.21,1.23,1.24,1.26,1.28,1.31] 0.08483 150.2 PASS 17.13 64.7 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous p-psa-suh NA NA NA NA NA NA NA all inf % 98.61 {%:98.61,form:1.12,ug/l:0.26} 24327 93796 [0.22,8,12,15,18,20.6,24,28,33.4] [9,12,14,16.8,19,22,25,29,36] 0.1437 300 PASS -34.01 248.8 FAIL 1 21 PASS PASS PASS_at_KS_(2/3) +unambiguous l-neut NA NA NA NA NA NA NA all inf % 98.82 {%:98.82,e9/l:1.18,osuus:0} 24285 378348 [3,5,26,44,51,56,60,65,72] [42,48,52,55.5,59,62,65.8,70,76] 0.2856 300 PASS -95.32 300 FAIL 8 27 PASS PASS PASS_at_KS_(2/3) +unambiguous oma-crp NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 21682 1347 [6,8,12,16,22,30,42,61,96] [6,8,10,13.4,19,26,36,53,81] 0.0552 3.073 PASS 3.631 3.535 FAIL 3 36 PASS PASS PASS_at_KS_(2/3) +unambiguous p-asat NA NA NA NA NA NA NA all inf u/l 99.95 {u/l:99.95,umol/l:0.05,u/l37:0} 21421 444746 [18,21,24,26,29,34,40,50,73] [17,19,22,24,27,30,35,44,70] 0.07457 98.55 PASS -6.633 10.48 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-glomerulussuodosnopeus,ckd-epi-kaava NA NA NA NA NA NA NA all inf ml/min/173m2 99.79 {ml/min/173m2:99.79,form:0.21} 21275 5606 [37,50,60,68,76,82,88,94,102] [38,49,58,65,72,79,84,89,95] 0.08282 26.2 PASS 7.857 14.36 FAIL 4 48 PASS PASS PASS_at_KS_(2/3) +unambiguous l-eos NA NA NA NA NA NA NA all inf % 99.56 {%:99.56,e9/l:0.44} 21090 942601 [0,0.9,1,1.9,2,3,3.2,4.5,6.8] [0,1,1,2,2,3,3.9,4,6] 0.07833 109.8 PASS -5.632 7.745 FAIL 0 3 PASS PASS PASS_at_KS_(2/3) +unambiguous l-neutr NA NA NA NA NA NA NA all inf % 99.66 {%:99.66,e9/l:0.34,e9:0} 20755 86909 [43,49,53,56,59,63,66,70,75] [44,49,53,56,59,62.4,66,70,76] 0.01054 1.318 PASS -1.996 1.338 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) unambiguous p-t4v NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100} 20621 90249 [12.2,13.4,14.2,14.9,15.6,16.3,17.2,18.3,20] [12.7,13.8,14.6,15.3,16,16.7,17.5,18.5,20] 0.05243 39.81 PASS -10.15 23.44 FAIL 0.4 5.7 PASS PASS PASS_at_KS_(2/3) +unambiguous s-b12-vit NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100,u:0,pmol/:0} 20314 76509 [227,280,325,370,417,476,551,650,835] [232,281,321,361,403,452,513,601,768] 0.05142 36.61 PASS 9.714 21.55 FAIL 14 354 PASS PASS PASS_at_KS_(2/3) +unambiguous l-eosin NA NA NA NA NA NA NA all inf % 100 {%:100} 19838 82317 [1,1,2,2,3,3,4,5,7] [1,1,2,2,3,3,4,5,6] 0.01263 1.919 PASS 1.953 1.294 PASS 0 3 PASS PASS PASS_at_KS_(3/3) +unambiguous l-lymfos NA NA NA NA NA NA NA all inf % 100 {%:100} 19480 83981 [13,17,21,24,26,29,32,36,41] [13,18,21,24,27,30,33,36,42] 0.01782 4.064 PASS -1.254 0.6779 PASS 1 21 PASS PASS PASS_at_KS_(3/3) +unambiguous b-basof NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 19447 4729 [0.02,0.03,0.03,0.04,0.04,0.05,0.06,0.07,0.08] [0.02,0.02,0.03,0.04,0.04,0.05,0.05,0.06,0.08] 0.04398 6.105 PASS 7.268 12.4 FAIL 0 0.06 PASS PASS PASS_at_KS_(2/3) +unambiguous b-eosin NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 19437 12142 [0.04,0.08,0.11,0.14,0.17,0.2,0.25,0.32,0.44] [0.04,0.08,0.11,0.14,0.17,0.21,0.25,0.31,0.44] 0.009323 0.2745 FAIL 0.6328 0.2783 PASS 0 0.27 PASS PASS PASS_at_T_(2/3) +unambiguous l-basof NA NA NA NA NA NA NA all inf % 100 {%:100} 19372 84273 [0,0,1,1,1,1,1,1,1] [0,0,1,1,1,1,1,1,1] 0.02437 7.833 PASS 9.941 22.52 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ca-albk NA NA NA NA NA NA NA all inf mmol/l 99.95 {mmol/l:99.95,form:0.05,mmol:0} 18846 165475 [2.29,2.34,2.37,2.4,2.43,2.46,2.5,2.54,2.61] [2.34,2.39,2.42,2.44,2.47,2.5,2.53,2.57,2.63] 0.1538 300 PASS -33.69 242.1 FAIL 0.04 0.21 PASS PASS PASS_at_KS_(2/3) +unambiguous oma-gluk NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 18525 53 [5.4,6.1,6.8,7.5,8.4,9.3,10.5,12.1,14.7] [5.22,5.74,6.1,6.4,6.7,7.12,8,8.6,11.12] 0.2829 3.519 PASS 5.572 6.066 FAIL 1.7 3.3 PASS PASS PASS_at_KS_(2/3) +unambiguous u-epit NA NA NA NA NA NA NA all inf e6/l 99.79 {e6/l:99.79,u/field:0.19,u:0.02} 18155 168750 [0,1,1,1.5,2,3,4,7,14] [0.2,1,1,1.9,2.1,3.2,5,8.1,16.9] 0.04272 25.71 PASS -6.438 9.907 FAIL 0.1 5.1 PASS PASS PASS_at_KS_(2/3) +unambiguous l-lymf NA NA NA NA NA NA NA all inf % 99.19 {%:99.19,e9/l:0.81} 17952 287233 [10,15.82,19,23,27,31,35,40.7,49] [12.3,18,21.2,25,28,31,34,38,44] 0.0618 55.82 PASS 2.945 2.49 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ck NA NA NA NA NA NA NA all inf u/l 100 {u/l:100} 17899 260925 [46,62,75,90,108,133,170,242,409] [43,58,71,86,104,129,169,252,545] 0.03098 13.67 PASS -14.94 49.58 FAIL 4 150 PASS PASS PASS_at_KS_(2/3) +unambiguous l-baso NA NA NA NA NA NA NA all inf % 99.56 {%:99.56,e9/l:0.43,e/l:0} 17874 929196 [0,0,0,0.5,1,1,1,1,1] [0,0,0,1,1,1,1,1,1] 0.06496 64.1 PASS -1.288 0.7036 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous s-ph(akt) NA NA NA NA NA NA NA all inf ph 100 {ph:100} 16686 97114 [7.35,7.37,7.38,7.39,7.4,7.4,7.41,7.42,7.44] [7.34,7.36,7.38,7.39,7.4,7.41,7.42,7.43,7.45] 0.08186 82.73 PASS -6.569 10.29 FAIL 0 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca(7.4) NA NA NA NA NA NA NA all inf mmol/l 99.92 {mmol/l:99.92,nmol/l:0.08} 16482 115493 [1.18,1.2,1.22,1.23,1.24,1.25,1.27,1.28,1.32] [1.12,1.16,1.19,1.21,1.22,1.24,1.25,1.27,1.31] 0.1685 300 PASS 42.01 300 FAIL 0.02 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous b-be NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 15770 19712 [-7.5,-5.5,-4.3,-3.4,-2.6,-2,-1.4,-0.9,-0.4] [0.5,1.1,1.7,2.3,3,3.9,5,6.6,9.2] 0.9739 300 FAIL -193.4 300 FAIL 5.6 6 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-d-25 NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100,mmol/l:0,nmol/:0} 15496 380163 [46,55,63,70,76,83,91,102,119] [46,56,63,69,76,82,90,100,116] 0.01766 3.739 PASS 3.216 2.885 FAIL 0 51 PASS PASS PASS_at_KS_(2/3) +unambiguous f-calpro NA NA NA NA NA NA NA all inf ug/g 100 {ug/g:100,ug/l:0,<100:0} 13490 130628 [17,27,39,57,85,129,202,355,794.1] [14,23,35,54,81,128,213,394,911] 0.03985 16.58 PASS -2.582 2.007 FAIL 4 195 PASS PASS PASS_at_KS_(2/3) +unambiguous u-osmole NA NA NA NA NA NA NA all inf mosm/kgh2o 100 {mosm/kgh2o:100} 13152 70655 [364,436,491,542,590,642,700,769,869] [347,415,470,522,570,625,687,762,869] 0.04625 20.33 PASS 7.362 12.72 FAIL 20 411 PASS PASS PASS_at_KS_(2/3) +unambiguous psa-v/psa NA NA NA NA NA NA NA all inf % 100 {%:100} 13127 25356 [9.6,12.5,14.9,17.2,19.4,21.8,24.4,27.9,33] [8.4,11,13.3,15.6,17.8,20.2,23,26.6,32.4] 0.07657 43.82 PASS 11.36 29.1 FAIL 1.6 18.3 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-transf NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 12905 144990 [1.8,2,2.1,2.25,2.4,2.56,2.7,2.98,3.2] [1.53,1.74,1.9,2.04,2.2,2.31,2.5,2.7,3] 0.1737 300 PASS 40.95 300 FAIL 0.2 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-cdt NA NA NA NA NA NA NA all inf % 99.96 {%:99.96,u/l:0.04,mg/l:0} 12434 89543 [1.2,1.4,1.5,1.6,1.6,1.7,1.9,2.1,2.9] [0.8,1.1,1.3,1.4,1.5,1.6,1.7,1.9,2.3] 0.1676 267.7 PASS 30.97 203.7 FAIL 0.1 0.9 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca-iona NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 12323 382345 [1.13,1.17,1.19,1.21,1.23,1.24,1.26,1.28,1.32] [1.14,1.18,1.2,1.22,1.23,1.25,1.26,1.29,1.32] 0.03902 15.51 PASS -8.946 18.38 FAIL 0 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous e-retik NA NA NA NA NA NA NA all inf % 99.98 {%:99.98,pg:0.01,e9/l:0} 12082 121560 [0.8,1,1.2,1.3,1.5,1.7,2,2.3,3] [0.9,1.1,1.3,1.5,1.7,1.9,2.2,2.7,3.7] 0.09935 94.16 PASS -17.22 65.1 FAIL 0.2 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous p-fidd NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100,mikrog/ml:0,ug/l:0} 12060 116811 [0.29,0.3,0.4,0.5,0.6,0.8,1,1.6,3] [0.22,0.3,0.4,0.6,0.7,1,1.44,2.2,4.5] 0.09284 81.71 PASS -14.73 48.09 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous p-mg NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 11982 247648 [0.64,0.7,0.74,0.78,0.81,0.83,0.86,0.9,0.95] [0.64,0.7,0.74,0.77,0.8,0.83,0.85,0.89,0.94] 0.03404 11.21 PASS 2.421 1.81 FAIL 0.01 0.24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca(akt) NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 11963 86215 [1.18,1.2,1.22,1.23,1.24,1.26,1.27,1.29,1.33] [1.11,1.15,1.18,1.2,1.22,1.23,1.25,1.27,1.31] 0.2276 300 PASS 45.35 300 FAIL 0.02 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous hdl/kol. NA NA NA NA NA NA NA all inf % 100 {%:100} 11551 1944 [23,27,30,33,36,38,41,45,49] [21,24,28,31,33,36,40,44,49] 0.08936 11.28 PASS 6.189 9.153 FAIL 3 24 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-fe NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100,µmol/l:0,ug/l:0} 11441 141841 [5,7,8.3,10,11.9,13.9,16,18.6,22.5] [5,7,8.8,10.3,11.9,13.5,15.5,18,22] 0.0343 10.53 PASS 1.835 1.177 PASS 0 12.9 PASS PASS PASS_at_KS_(3/3) +unambiguous fs-ca-ion NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 10667 11278 [1.19,1.22,1.23,1.24,1.25,1.27,1.28,1.3,1.33] [1.16,1.2,1.21,1.23,1.24,1.26,1.27,1.3,1.35] 0.1108 58.37 PASS 1 0.4985 PASS 0.01 0.12 PASS PASS PASS_at_KS_(3/3) +unambiguous b-lymf NA NA NA NA NA NA NA all inf e9/l 98.42 {e9/l:98.42,%:1.58} 10416 275628 [0.97,1.2,1.41,1.6,1.81,2.02,2.29,2.66,3.315] [0.86,1.14,1.36,1.55,1.74,1.95,2.19,2.5,2.99] 0.04474 17.17 PASS 2.462 1.859 FAIL 0.07 1.59 PASS PASS PASS_at_KS_(2/3) +unambiguous b-erytroblastit NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 10388 151903 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.03874 12.39 PASS -16.36 59.39 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous u-prot-o NA NA NA NA NA NA NA all inf form 99.89 {form:99.89,mg/dl:0.11} 9860 936 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,1] 0.04588 1.277 FAIL -3.484 3.287 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-t4-v NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100,pmol:0} 9709 242498 [11,12,12,13,13,14,14,15,17] [11,12,12.9,13.1,14,14.5,15.1,16.01,17.5] 0.1618 213.2 PASS -15.97 56 FAIL 1 5.1 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-gluk-hy NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 9537 6395 [5.3,6.5,7.5,8.5,9.5,10.6,11.9,13.4,15.6] [5.4,6.5,7.5,8.5,9.5,10.4,11.6,13.3,15.6] 0.02434 1.677 PASS -1.27 0.6904 PASS 0 7.8 PASS PASS PASS_at_KS_(3/3) +unambiguous nu-albkrea NA NA NA NA NA NA NA all inf mg/mmol 100 {mg/mmol:100} 9489 11439 [0.2,0.4,0.5,0.7,1,1.6,2.8,6,17.9] [0.3,0.5,0.7,0.9,1.3,2.1,3.8,8.2,27.3] 0.09281 38.61 PASS -6.811 11 FAIL 0.3 2.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-iga NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 9343 52529 [1.06,1.4,1.63,1.9,2.1,2.4,2.74,3.2,4.16] [0.74,1.16,1.46,1.73,2.03,2.37,2.77,3.35,4.51] 0.08621 51.01 PASS -6.038 8.799 FAIL 0.07 2.46 PASS PASS PASS_at_KS_(2/3) +unambiguous p-b12-vit NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100} 9340 37066 [194,243,285,326,371,423,487,577,720] [208,258,299,339,381,429,489,575,748] 0.03999 10.07 PASS -6.574 10.3 FAIL 10 351 PASS PASS PASS_at_KS_(2/3) +unambiguous p-crp-o NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100,u/l:0} 9102 29537 [7,9,13,18,24,33,45,65,98] [6,8,11,14,20,28,40,58,91] 0.07448 33.29 PASS 8.707 17.46 FAIL 4 39 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-pco2 NA NA NA NA NA NA NA all inf kpa 100 {kpa:100} 9039 107718 [4.2,4.7,5,5,5,5.3,5.7,6,6.7] [4.2,4.5,4.7,4.9,5.1,5.3,5.6,5.9,6.6] 0.1277 118.3 PASS 3.557 3.424 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-pi NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 8841 175027 [0.8,0.9,0.98,1.02,1.1,1.15,1.21,1.32,1.54] [0.78,0.9,0.99,1.07,1.16,1.25,1.38,1.56,1.85] 0.1446 153.3 PASS -25.19 135.2 FAIL 0.06 0.72 PASS PASS PASS_at_KS_(2/3) +unambiguous p-inr-vt NA NA NA NA NA NA NA all inf inr 100 {inr:100} 8487 1439 [1.3,1.8,2,2.1,2.3,2.4,2.6,2.9,3.3] [1,1,1,1,1.1,1.3,1.9,2.4,2.9] 0.5129 297.5 FAIL 23.72 115.7 FAIL 1.2 0.3 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous fp-ca NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 8418 53236 [2.23,2.29,2.31,2.35,2.38,2.4,2.43,2.49,2.55] [2.19,2.25,2.29,2.33,2.35,2.38,2.42,2.45,2.51] 0.1007 63.87 PASS 18.9 77.73 FAIL 0.03 0.24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-pappa NA NA NA NA NA NA NA all inf mu/l 99.6 {mu/l:99.6,form:0.4} 8226 33727 [255,396,527,664,822,1000,1220,1550,2150] [274,426,564,707,859.8,1045,1280,1622,2232] 0.02933 4.649 PASS -2.662 2.11 FAIL 37.85 1286 PASS PASS PASS_at_KS_(2/3) +unambiguous p-t3-v NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100} 8195 73828 [3.5,3.9,4.1,4.3,4.5,4.8,5,5.4,6.2] [3.5,3.8,4.1,4.3,4.6,4.8,5.1,5.5,6.2] 0.0259 4.005 PASS -0.7015 0.3161 PASS 0.1 1.8 PASS PASS PASS_at_KS_(3/3) unambiguous s-iglck-v NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 7877 39042 [9.6,13.9,18.4,23.5,30,40.1,55.8,89.68,220] [7.8,12.1,16.2,21,27.1,35.7,50.3,81.2,172] 0.05025 14.1 PASS 3.239 2.92 FAIL 2.9 49.8 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-hco3-st NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 7860 64090 [20.9,22.4,23.9,24.7,25.3,26.1,27.2,28.82,31.2] [21,22.4,23.3,24,25,25.6,26.3,27.5,29.5] 0.1021 63.24 PASS 12.93 37.18 FAIL 0.3 6 PASS PASS PASS_at_KS_(2/3) +unambiguous s-iglcl-v NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 7669 38822 [6.5,9.7,12.8,16,19.6,25,32.9,49.8,124] [6.1,9.2,12,15.1,19,23.9,31.8,48.6,118] 0.03176 5.319 PASS -2.897 2.424 FAIL 0.6 31.5 PASS PASS PASS_at_KS_(2/3) +unambiguous crp NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 7205 71 [6,9,12,16,22,30,42,58,90] [6,8,12,16,25,38,58,64,88] 0.1079 0.4437 FAIL -0.6403 0.2806 PASS 3 57 PASS PASS PASS_at_T_(2/3) +unambiguous p-ck-mbm NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 7160 69802 [1.3,1.7,2,2.3,2.6,3.1,3.8,4.9,7.81] [1.1,1.5,1.9,2.2,2.8,3.4,4.5,7.1,18] 0.0901 45.59 PASS -19.06 79.34 FAIL 0.2 4.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-testo NA NA NA NA NA NA NA all inf nmol/l 99.93 {nmol/l:99.93,pmol/l:0.03,form:0.03} 6954 77552 [2.9,6.5,8.1,9.5,11,13,15.7,19,23.87] [1.5,6.6,9,11,12.8,14.7,17,19.8,24.4] 0.09349 48.27 PASS -2.242 1.603 FAIL 1.8 15.6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-pi NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 6629 179614 [0.69,0.81,0.9,0.98,1.05,1.14,1.23,1.37,1.6] [0.74,0.87,0.97,1.05,1.13,1.23,1.35,1.51,1.79] 0.105 61.07 PASS -18.9 77.09 FAIL 0.08 0.72 PASS PASS PASS_at_KS_(2/3) +unambiguous u-osmest NA NA NA NA NA NA NA all inf mosm/kgh2o 100 {mosm/kgh2o:100,mo/kg/h2o:0,mo/kgh2o:0} 6305 89312 [291,363,418,465,515,573,634.2,703,803.4] [262,327,378,425,472,523,584,656,768] 0.08677 38.3 PASS 14.79 48.04 FAIL 43 390 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-krea NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 6255 759945 [62,70,77,87,96,103,110,121,146] [56,62,68,73,78,84,92,105,140] 0.246 300 PASS 6.138 9.052 FAIL 18 45 PASS PASS PASS_at_KS_(2/3) +unambiguous p-tt NA NA NA NA NA NA NA all inf % 100 {%:100,form:0} 6023 465481 [41,57,67,77,86,94,102,112,126] [50,65,74,82,88,95,102,110,121] 0.08411 36.31 PASS -5.824 8.218 FAIL 2 54 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ld NA NA NA NA NA NA NA all inf u/l 100 {u/l:100} 5895 215599 [163,180,193,207,221,238,258,289,357] [166,184,198,212,226,244,269,310,413] 0.04455 9.609 PASS -10.44 24.61 FAIL 5 126 PASS PASS PASS_at_KS_(2/3) +unambiguous p-bil-kj NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 5806 124636 [2,3,3,4,5,6,7,9,15] [3,3,4,4,5,6,8,11,26] 0.06147 17.94 PASS -9.79 21.76 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous b-leukosyytit NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100,1:0} 5646 370214 [4.8,6,7,8.3,8.7,9.2,9.9,10.8,13] [4.4,5.1,5.7,6.2,6.8,7.4,8.2,9.3,11.3] 0.3046 300 FAIL 21.83 100.9 FAIL 1.9 4.8 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-urea NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 5615 168276 [4.1,5.4,6.8,8.5,10.5,12.7,15.3,18.8,24.7] [4.2,5.5,6.9,8.7,10.9,13.4,16.4,20,25.3] 0.0386 6.745 PASS -3.726 3.708 FAIL 0.4 16.2 PASS PASS PASS_at_KS_(2/3) +unambiguous crp-pika NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 5400 3081 [6,8,11,16,23,33,47,69,103] [7,9,13,18,25,34,47,69,106] 0.05675 5.211 PASS -1.678 1.029 PASS 2 51 PASS PASS PASS_at_KS_(3/3) +unambiguous -trfesat NA NA NA NA NA NA NA all inf % 100 {%:100,g/l:0} 5367 49060 [8,12,16,19,22,26,29,34,41] [9.2,13.8,17,20,23,26.26,30,34.7,42] 0.05622 13.01 PASS -6.034 8.775 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +unambiguous p-amylp NA NA NA NA NA NA NA all inf u/l 100 {u/l:100} 5279 91217 [13,18,21,24,28,31,35,43,60] [14,20,23,26,30,34,40,51,85] 0.07912 26.89 PASS -8.148 15.35 FAIL 2 30 PASS PASS PASS_at_KS_(2/3) +unambiguous s-prot NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 5242 87590 [59,62.5,65,67,68.4,70,71.5,73.9,77] [57,61,63,65,67,69,70.6,73,76.2] 0.09527 38.8 PASS 10.78 26.12 FAIL 1.4 15 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-urea NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 5232 124584 [5,6.6,8,9.7,11.4,13.6,16.1,19.88,25] [5,6.9,8.9,11.3,13.9,16.5,19.2,22.4,27.3] 0.1204 63.19 PASS -14.53 46.26 FAIL 2.5 18.9 PASS PASS PASS_at_KS_(2/3) +unambiguous 14272 NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 5212 79059 [1.5,2,2.5,2.9,3.4,3.9,4.7,5.8,8.1] [1.06,1.72,2.24,2.72,3.24,3.83,4.61,5.76,8.02] 0.07552 23.97 PASS 3.429 3.214 FAIL 0.16 4.38 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-glomerulussuodosnopeus,estimoitu,ckd-epi-kaava NA NA NA NA NA NA NA all inf ml/min/173m2 99.81 {ml/min/173m2:99.81,1:0.19} 5151 202854 [30,38.2,44,49,53,57,62,69,82] [34,48,59,68,75,82,87,93,101] 0.3791 300 FAIL -57.84 300 FAIL 22 51 PASS PASS PASS_at_MAD_(1/3) +unambiguous -nt NA NA NA NA NA NA NA all inf mm 100 {mm:100} 5019 11772 [0.8,0.9,1,1.1,1.2,1.2,1.3,1.5,1.7] [0.9,1,1.1,1.2,1.27,1.34,1.49,1.6,1.8] 0.1319 53.08 PASS -11.64 30.4 FAIL 0.07 0.75 PASS PASS PASS_at_KS_(2/3) +unambiguous s-hcgbv/d NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 4990 14513 [22.4,30.3,37.1,44.7,52.7,62.64,74.9,91.5,120] [22.6,31.2,38.7,46.3,55,64.9,77.8,94.1,125.5] 0.02665 1.997 PASS -3.451 3.251 FAIL 2.3 70.5 PASS PASS PASS_at_KS_(2/3) +unambiguous s-mkomp-1 NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 4885 29826 [0,0,0,1.1,2.5,4.2,7.1,11.4,19.1] [0,0,0,0,0,0.3,1.8,5.1,11.2] 0.2583 246.7 PASS 21.27 96.01 FAIL 2.5 0 FAIL PASS PASS_at_KS_(1/3) +unambiguous s-li NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 4651 33555 [0.4,0.5,0.58,0.6,0.7,0.72,0.8,0.9,1] [0.4,0.5,0.54,0.6,0.69,0.7,0.8,0.9,1] 0.02917 2.728 PASS 1.317 0.726 PASS 0.01 0.51 PASS PASS PASS_at_KS_(3/3) +unambiguous p-ca-iona NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,%:0,kpa:0} 4581 404577 [1.1,1.14,1.16,1.17,1.19,1.21,1.23,1.25,1.29] [1.04,1.08,1.11,1.13,1.15,1.17,1.19,1.21,1.25] 0.2532 255.7 PASS 33.65 230.1 FAIL 0.04 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous s-valpr NA NA NA NA NA NA NA all inf umol/l 99.9 {umol/l:99.9,%:0.1} 4307 31514 [197,257,299.8,340.4,382,423,465,517,588.4] [221,285,332,372,409,446,487,533,601] 0.0818 21.78 PASS -10.07 22.95 FAIL 27 300 PASS PASS PASS_at_KS_(2/3) +unambiguous p-ca-ion. NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 4300 356672 [1.11,1.14,1.16,1.18,1.2,1.21,1.23,1.26,1.29] [1.03,1.08,1.11,1.13,1.16,1.18,1.2,1.22,1.25] 0.251 235.6 PASS 41.48 300 FAIL 0.04 0.18 PASS PASS PASS_at_KS_(2/3) +unambiguous u-albkrea NA NA NA NA NA NA NA all inf mg/mmol 99.24 {mg/mmol:99.24,mg/mmol/l:0.76} 4132 10589 [0.4,0.7,1.1,1.9,3.4,4.9,7.7,14.4,36.99] [0.3,0.4,0.6,0.7,1,1.3,1.8,3,9.12] 0.343 300 FAIL 9.367 20 FAIL 2.4 1.8 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous fs-trigly NA NA NA NA NA NA NA all inf mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,form:0} 3980 258906 [0.6,0.72,0.83,0.93,1.06,1.2,1.39,1.64,2.11] [0.7,0.84,0.98,1.11,1.27,1.45,1.68,2,2.57] 0.1417 68.43 PASS -20.61 89.3 FAIL 0.21 1.26 PASS PASS PASS_at_KS_(2/3) +unambiguous b-crp-vt NA NA NA NA NA NA NA all inf mg/l 99.98 {mg/l:99.98,crp:0.02,g/l:0.01} 3965 16204 [2.64,5.7,8,12,18,26,40,57,89] [6,8,11,14,19,27,38,54,88] 0.1545 66.18 PASS -1.14 0.5947 PASS 1 36 PASS PASS PASS_at_KS_(3/3) +unambiguous sy-leuk NA NA NA NA NA NA NA all inf e6/l 99.75 {e6/l:99.75,e9/l:0.25} 3964 11394 [117.3,262.6,500,1123,2804,5405,1.011e+04,1.868e+04,3.801e+04] [100.3,225,510,1400,3320,6503,1.12e+04,1.91e+04,3.72e+04] 0.03253 2.413 PASS -0.3365 0.1328 PASS 516 9654 PASS PASS PASS_at_KS_(3/3) +unambiguous b-ghba1cp NA NA NA NA NA NA NA all inf % 100 {%:100} 3927 888 [6,6.3,6.6,6.9,7.2,7.4,7.8,8.2,8.8] [5.9,6.1,6.5,6.8,7.1,7.52,7.9,8.3,9.4] 0.06144 2.095 PASS -3.643 3.545 FAIL 0.1 2.7 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-kol-hdl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,form:0,mmol/:0} 3887 254480 [1.03,1.16,1.25,1.34,1.43,1.53,1.64,1.77,1.96] [1,1.1,1.2,1.3,1.4,1.5,1.6,1.74,2] 0.07186 16.91 PASS 1.839 1.18 PASS 0.03 0.75 PASS PASS PASS_at_KS_(3/3) +unambiguous fs-kol NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mmol/:0,form:0} 3794 255206 [3.5,4,4.3,4.6,4.9,5.2,5.5,5.8,6.4] [3.7,4.2,4.5,4.8,5,5.3,5.6,5.9,6.4] 0.06004 11.43 PASS -6.382 9.711 FAIL 0.1 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-kol-ldl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,form:0,mmol/:0} 3772 255211 [1.7,2.2,2.5,2.8,3.1,3.4,3.671,3.996,4.5] [1.9,2.3,2.6,2.9,3.1,3.4,3.7,4,4.5] 0.04679 6.785 PASS -3.555 3.417 FAIL 0 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous p-bnp NA NA NA NA NA NA NA all inf ng/l 99.98 {ng/l:99.98,ng/ml:0.02} 3770 88507 [42,72,109,144,194,258,352,511.4,899.1] [20,36,58,88,131,195,292,462,895] 0.1578 78.37 PASS 2.555 1.973 FAIL 63 312 PASS PASS PASS_at_KS_(2/3) +unambiguous p-igg NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 3736 73214 [6,7.4,8.6,9.5,10.4,11.4,12.6,14.5,17.95] [5,6.6,7.7,8.7,9.6,10.6,11.7,13.3,16.6] 0.1016 31.71 PASS 8.605 16.97 FAIL 0.8 7.8 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-glukoosi,ihopistosn,vieritestihoitoyksikössä NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 3716 1349 [5.3,6.2,7.1,8,9.1,10.3,11.9,13.9,16.9] [5.2,6.2,7,7.9,8.9,10.2,11.9,14.2,17.2] 0.0217 0.1369 FAIL 0.5007 0.21 PASS 0.2 8.4 PASS PASS PASS_at_T_(2/3) +unambiguous ab-emäsylimäärä NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 3701 9136 [-9.2,-6.4,-4.8,-3.7,-2.8,-2.1,-1.6,-1.1,-0.5] [-0.8,0.4,1.1,1.7,2.4,3.3,4.5,6.1,8.9] 0.8699 300 FAIL -89.69 300 FAIL 5.2 6 PASS PASS PASS_at_MAD_(1/3) +unambiguous u-sg NA NA NA NA NA NA NA all inf kg/l 100 {kg/l:100} 3697 130 [1.005,1.005,1.01,1.01,1.015,1.015,1.02,1.02,1.025] [1.01,1.01,1.01,1.015,1.015,1.017,1.02,1.02,1.025] 0.182 3.385 PASS 2 1.341 FAIL 0 0.015 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-emäsylimäärä NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 3632 12064 [-9.1,-6.3,-4.6,-3.5,-2.6,-2,-1.3,-0.8,-0.3] [-2.6,-0.2,0.7,1.3,2.1,2.8,3.6,4.7,6.7] 0.7533 300 FAIL -77.35 300 FAIL 4.7 5.7 PASS PASS PASS_at_MAD_(1/3) +unambiguous b-ph NA NA NA NA NA NA NA all inf ph 100 {ph:100} 3554 35592 [7.31,7.34,7.36,7.38,7.39,7.41,7.43,7.44,7.46] [7.35,7.38,7.4,7.41,7.42,7.43,7.44,7.46,7.48] 0.2071 121.3 PASS -23.05 109.9 FAIL 0.03 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-pco2 NA NA NA NA NA NA NA all inf kpa 100 {kpa:100} 3514 187248 [4.523,5,5.2,5.4,5.7,5.9,6.2,6.5,7.1] [4.7,5.1,5.3,5.6,5.8,6,6.3,6.6,7.1] 0.06585 12.72 PASS -5.987 8.629 FAIL 0.1 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-po2 NA NA NA NA NA NA NA all inf kpa 100 {kpa:100} 3497 134116 [3.2,3.8,4.386,4.8,5.2,5.6,6.2,7.4,10] [2.8,3.4,3.9,4.3,4.7,5.1,5.7,6.5,8.3] 0.1189 41.73 PASS 13.92 42.21 FAIL 0.5 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous mb-ph NA NA NA NA NA NA NA all inf ph 100 {ph:100} 3444 279 [7.29,7.32,7.34,7.36,7.373,7.39,7.401,7.419,7.435] [7.318,7.34,7.36,7.37,7.38,7.4,7.41,7.42,7.44] 0.13 3.535 PASS -3.9 3.936 FAIL 0.007 0.09 PASS PASS PASS_at_KS_(2/3) unambiguous b-crp NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 3350 2366 [5,7,9,12,17,24,35,54,87] [6,8,9,13,18,25,35,55,90] 0.09378 10.34 PASS -1.146 0.5987 PASS 1 33 PASS PASS PASS_at_KS_(3/3) +unambiguous p-gluk-vt NA NA NA NA NA NA NA all inf mmol/l 98.08 {mmol/l:98.08,1:1.92} 3313 2048 [5,5.7,6.4,7.2,8.2,9.5,11,12.8,15.9] [4.5,4.7,4.9,5.1,5.4,5.8,6.5,7.56,9.63] 0.3966 177.7 FAIL 20.93 92.33 FAIL 2.8 2.4 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous ab-po2 NA NA NA NA NA NA NA all inf kpa 99.99 {kpa:99.99,mmol/l:0,%:0} 3269 391556 [6.7,7.7,8.2,8.8,9.4,10,10.9,12,14.2] [8.1,9.1,9.9,10.6,11.4,12.4,13.8,16.2,21.5] 0.2746 215.8 PASS -43.56 300 FAIL 2 7.2 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-pco2 NA NA NA NA NA NA NA all inf kpa 99.99 {kpa:99.99,mmol/l:0,%:0} 3239 392179 [3.9,4.3,4.6,4.8,5,5.3,5.7,6.3,7.4] [4.1,4.5,4.7,5,5.2,5.4,5.6,5.9,6.5] 0.07603 15.87 PASS 3.66 3.592 FAIL 0.2 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous li-leuk NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 3193 10896 [0,0,1,1,2,3,4,10,65.6] [0,0,1,1,2,3,5,11,58] 0.03269 2 PASS -2.785 2.27 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous li-eryt NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 3189 11741 [0,0,0,1,3,10,43.6,199.4,1766] [0,0,1,2,4,12,45,232,2250] 0.02869 1.501 PASS 0.6696 0.2983 PASS 1 12 PASS PASS PASS_at_KS_(3/3) +unambiguous p-crp-vt NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 3141 6868 [5,6.9,9,14,20,28,40,59,91] [5,7,10,14,20,28,40,61,94] 0.0366 2.22 PASS -0.7086 0.3201 PASS 0 42 PASS PASS PASS_at_KS_(3/3) +unambiguous b-crp-o NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 3125 1516 [7,10,14,19,26,35,47,67,98] [6,8,11,15,21,28,40,59,90] 0.08443 6.057 PASS 3.708 3.672 FAIL 5 42 PASS PASS PASS_at_KS_(2/3) +unambiguous s-psa NA NA NA NA NA NA NA all inf ug/l 99.99 {ug/l:99.99,mg/l:0.01,%:0} 3123 88424 [0.37,0.57,0.73,0.95,1.3,1.7,2.6,4.2,7.5] [0.39,0.57,0.75,0.97,1.24,1.63,2.26,3.3,5.4] 0.05689 8.201 PASS 2.235 1.593 FAIL 0.06 2.22 PASS PASS PASS_at_KS_(2/3) +unambiguous p-apcres. NA NA NA NA NA NA NA all inf form 100 {form:100} 3090 64 [2.5,2.7,2.8,2.9,2.9,3,3,3.1,3.2] [2.7,2.8,2.8,2.8,2.9,2.9,2.9,3,3] 0.1794 1.512 PASS -0.7183 0.3234 PASS 0 0.3 PASS PASS PASS_at_KS_(3/3) +unambiguous cp-gluk NA NA NA NA NA NA NA all inf mmol/l 99.85 {mmol/l:99.85,mmol/:0.15} 3068 1987 [5.9,6.8,7.8,9,10.25,11.9,13.89,15.96,19.2] [5.1,6.3,7.7,9.1,10.6,12.7,14.4,16.4,19.3] 0.06829 4.613 PASS 0.1958 0.07327 PASS 0.35 12.6 PASS PASS PASS_at_KS_(3/3) +unambiguous lieriöt NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 2938 23942 [0,0,0,0,0,0,0.1,0.3,0.9] [0,0,0,0,0,0.1,0.3,0.42,1] 0.1694 65.4 PASS -0.1685 0.06237 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous crp(päiv.hoitaja) NA NA NA NA NA NA NA all inf mg/l 99.18 {mg/l:99.18,g/l:0.27,mg/:0.27} 2927 361 [6,8,10,14,19,27,39.2,56,91.4] [6,7,9,12,15,21,28,47,71] 0.09255 2.122 PASS 3.49 3.279 FAIL 4 27 PASS PASS PASS_at_KS_(2/3) +unambiguous u-happamuusaste(kval) NA NA NA NA NA NA NA all inf form 100 {form:100} 2872 32 [5,5.5,5.5,5.5,6,6,6,6.5,7] [5,5.5,5.5,5.5,5.5,6,6,6.5,7] 0.09706 0.04638 FAIL 0.1506 0.05489 PASS 0.5 1.5 PASS PASS PASS_at_T_(2/3) +unambiguous p-cea NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 2813 49240 [1.2,1.7,2,2.2,3,3.1,4,5,6.9] [1.6,2.1,2.4,2.8,3.4,4.3,5.9,10,33] 0.181 76.06 PASS -8.645 17.17 FAIL 0.4 4.5 PASS PASS PASS_at_KS_(2/3) +unambiguous happamuusaste,laskimoveri NA NA NA NA NA NA NA all inf ph 100 {ph:100} 2733 819 [7.32,7.35,7.36,7.38,7.39,7.4,7.41,7.43,7.45] [7.3,7.34,7.36,7.37,7.39,7.4,7.41,7.43,7.45] 0.05006 1.088 FAIL 2.574 1.993 FAIL 0 0.09 PASS PASS PASS_at_MAD_(1/3) +unambiguous tffesat NA NA NA NA NA NA NA all inf % 100 {%:100} 2726 900 [7.6,10.8,13.7,16.6,19.4,22.3,25.9,30.3,37] [8.19,11.68,15,18.1,21.2,24.34,27.63,31.84,38.41] 0.07481 3.017 PASS -2.62 2.051 FAIL 1.8 23.7 PASS PASS PASS_at_KS_(2/3) +unambiguous u-lieriöt NA NA NA NA NA NA NA all inf e6/l 99.54 {e6/l:99.54,u/field:0.46,u/ul:0} 2719 59778 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0.14,0.42,1] 0.3489 282.7 FAIL -27.96 168.5 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-gamma NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,%:0.04} 2700 28537 [5.6,6.68,7.5,8.2,9.2,10.1,11.2,12.7,15.9] [4.5,6.3,7.5,8.5,9.5,10.5,11.7,13.5,17.3] 0.06216 8.004 PASS -2.571 1.992 FAIL 0.3 8.1 PASS PASS PASS_at_KS_(2/3) +unambiguous erytroblastit NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 2691 141098 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.04834 5.075 PASS -6.487 9.984 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-hco3-st NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 2612 255830 [20,22,23,24,25,26,27,28,30] [21,22,23,24,25,25,26,27,29] 0.05808 7.299 PASS 3.353 3.091 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-kysc NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 2572 52852 [0.76,0.9,1.013,1.13,1.27,1.44,1.64,1.91,2.359] [0.85,0.96,1.08,1.23,1.42,1.64,1.93,2.35,3.15] 0.1083 24.79 PASS -18.23 69.86 FAIL 0.15 1.41 PASS PASS PASS_at_KS_(2/3) +unambiguous s-alfa-2 NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,%:0.04} 2555 27644 [5.7,6.2,6.5,6.8,7.1,7.5,7.9,8.4,9.4] [5.5,5.9,6.3,6.7,7,7.4,7.8,8.4,9.37] 0.06415 8.084 PASS 4.402 4.955 FAIL 0.1 3 PASS PASS PASS_at_KS_(2/3) +unambiguous s-alfa-1 NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,%:0.04} 2552 27708 [1.5,1.7,1.9,2.1,2.4,2.6,2.9,3.2,3.8] [2.2,2.4,2.6,2.7,2.9,3,3.2,3.5,4.1] 0.3316 228.8 FAIL -23.7 113 FAIL 0.5 1.2 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-album NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 2547 25430 [31.4,35,37.3,39,40.3,41.5,43,44.5,46.3] [31,34.3,36.2,37.6,38.7,39.8,40.9,42.1,43.7] 0.1625 53.15 PASS 12.94 36.55 FAIL 1.6 9 PASS PASS PASS_at_KS_(2/3) +unambiguous s-beta-2 NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,%:0.04} 2541 27334 [2.1,2.4,2.6,2.8,3,3.3,3.6,4.1,4.8] [2.3,2.6,2.8,3.1,3.4,3.6,4,4.5,5.5] 0.1285 33.22 PASS -15.11 49.61 FAIL 0.4 2.1 PASS PASS PASS_at_KS_(2/3) +unambiguous s-beta-1 NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,%:0.04} 2540 27387 [3.4,3.7,3.9,4,4.2,4.4,4.6,4.8,5.2] [3.3,3.5,3.7,3.9,4,4.2,4.4,4.6,5] 0.1268 32.31 PASS 5.524 7.448 FAIL 0.2 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-norklot NA NA NA NA NA NA NA all inf nmol/l 99.98 {nmol/l:99.98,umol/l:0.02} 2538 22343 [321,458.4,572,704.8,826,970,1111,1326,1687] [344,489,614,734,863,1000,1166,1390,1713] 0.03663 2.367 PASS -2.018 1.36 FAIL 37 1041 PASS PASS PASS_at_KS_(2/3) +unambiguous p-korsol NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100,pmol/l:0} 2505 51414 [185,261,314,350,394,434,482,539,637.6] [84,204.6,266,312,352,391,434,486,567] 0.1124 26 PASS 13.05 37.1 FAIL 42 330 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg4 NA NA NA NA NA NA NA all inf g/l 99.98 {g/l:99.98,form:0.02} 2503 9778 [0.119,0.2164,0.3326,0.4408,0.58,0.7958,1.1,1.69,2.93] [0.11,0.209,0.31,0.439,0.59,0.787,1.06,1.56,2.623] 0.02386 0.6934 FAIL 4.122 4.413 FAIL 0.01 1.209 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-igm NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 2460 38211 [0.4,0.6,0.76,0.94,1,1.2,1.58,2.29,5.028] [0.26,0.4,0.56,0.7,0.88,1.09,1.35,1.8,3.34] 0.1456 42.47 PASS 2.462 1.858 FAIL 0.12 1.44 PASS PASS PASS_at_KS_(2/3) +unambiguous l-nlt NA NA NA NA NA NA NA all inf % 100 {%:100} 2422 7143 [16,28,38,45,52,59,65,72,81] [25,38,46,53,59,65,70,76,83] 0.1145 20.38 PASS -11.13 27.64 FAIL 7 45 PASS PASS PASS_at_KS_(2/3) +unambiguous s-iga NA NA NA NA NA NA NA all inf g/l 100 {g/l:100,mg/l:0} 2410 35623 [0.99,1.32,1.55,1.8,2.05,2.33,2.69,3.27,4.331] [1.05,1.34,1.56,1.77,1.99,2.23,2.53,2.93,3.66] 0.05965 6.697 PASS 6.321 9.512 FAIL 0.06 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous s-van NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 2406 34483 [7.3,9,10.5,11.7,13,14.1,15.6,17.8,21.4] [6.9,8.6,10,11.1,12.4,13.7,15,17,19.8] 0.04717 4.062 PASS 5.626 7.692 FAIL 0.6 10.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-cea NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100,<5:0} 2353 87770 [1.1,1.3,1.6,1.9,2.2,2.7,3.5,4.66,7.3] [1.1,1.4,1.7,2,2.4,3.1,4.1,6.3,17.4] 0.07905 12.18 PASS -16.63 61.01 FAIL 0.2 3.3 PASS PASS PASS_at_KS_(2/3) +unambiguous zb-be NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 2350 2420 [-6.1,-4.1,-3.2,-2.6,-2,-1.5,-1.2,-0.7,-0.4] [0.4,0.8,1.2,1.7,2.2,2.9,3.8,4.9,7.4] 1 300 FAIL -70.65 300 FAIL 4.2 4.2 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-crp-hy NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 2326 6913 [7,10,13,18,24,33,46,66,101.5] [6,8,11,15,21,29,41,59,91] 0.06881 6.886 PASS 4.653 5.47 FAIL 3 42 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-trfesat NA NA NA NA NA NA NA all inf % 100 {%:100} 2313 88543 [8,11,14,17,20,24,28,34,41.8] [9,13,16,19,22,25,28,33,40] 0.08891 15.23 PASS -2.173 1.525 FAIL 2 24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-k NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,mml/l:0} 2255 138249 [3.8,3.9,4.1,4.1,4.2,4.3,4.3,4.4,4.6] [3.8,4,4.1,4.2,4.2,4.3,4.4,4.5,4.6] 0.05636 5.841 PASS -4.525 5.198 FAIL 0 0.6 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-laktaat NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 2205 299118 [0.9,1,1.1,1.2,1.4,1.6,1.8,2.2,3] [0.5,0.7,0.8,0.9,1,1.2,1.4,1.7,2.3] 0.2916 164.6 PASS 13.23 37.77 FAIL 0.4 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous pf-eryt NA NA NA NA NA NA NA all inf e6/l 99.86 {e6/l:99.86,e9/l:0.14} 2155 3474 [300,700,1121,1900,3200,5600,1.11e+04,2.434e+04,7.96e+04] [300,800,1740,3300,6000,1.04e+04,2e+04,4.594e+04,1.3e+05] 0.1203 16.49 PASS -1.241 0.6679 PASS 2800 1.694e+04 PASS PASS PASS_at_KS_(3/3) +unambiguous vb-happamuusaste NA NA NA NA NA NA NA all inf 1 100 {1:100} 2150 59 [7.31,7.34,7.36,7.37,7.388,7.4,7.41,7.43,7.45] [7.288,7.35,7.38,7.39,7.4,7.41,7.426,7.434,7.452] 0.1619 1.058 FAIL -1.075 0.5427 PASS 0.012 0.09 PASS PASS PASS_at_T_(2/3) +unambiguous pf-leuk NA NA NA NA NA NA NA all inf e6/l 99.02 {e6/l:99.02,e9/l:0.98} 2145 4958 [143.8,262.8,405.6,585,804,1129,1638,2613,4980] [123.7,230,367,548.8,780.5,1120,1674,2547,4805] 0.0346 1.268 FAIL 1.1 0.5666 PASS 23.5 1804 PASS PASS PASS_at_T_(2/3) +unambiguous pt-gfre-md NA NA NA NA NA NA NA all inf ml/min/173m2 99.94 {ml/min/173m2:99.94,form:0.06} 2116 26941 [34,44,51,56,60,69,77,85,96] [34,45,52,57,61,72,81,90,101] 0.0529 4.485 PASS -4.037 4.253 FAIL 1 54 PASS PASS PASS_at_KS_(2/3) +unambiguous u-lieriö NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 2104 5122 [0,0,0,0,0.11,0.11,0.23,0.34,0.81] [0,0,0,0,0,0,0,0.1,1] 0.3671 178.8 FAIL -2.826 2.326 FAIL 0.11 0 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous l-myel NA NA NA NA NA NA NA all inf % 100 {%:100} 2051 13362 [0,0,0,0,0,1,1,2,4] [0,0,0,0,1,1,1,2,4] 0.06706 6.669 PASS -0.8266 0.3888 PASS 1 3 PASS PASS PASS_at_KS_(3/3) unambiguous s-tfr NA NA NA NA NA NA NA all inf mg/l 99.99 {mg/l:99.99,mg:0.01} 2018 75736 [1.8,2.2,2.6,3.1,3.6,4.2,5.1,6.3,8.1] [1,1.2,1.5,1.9,2.4,2.8,3.3,4.1,5.6] 0.2886 144.8 PASS 20.34 83.32 FAIL 1.2 3.3 PASS PASS PASS_at_KS_(2/3) +unambiguous b-tacro NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 1993 43350 [4.3,5.1,6,6.8,7.5,8.5,9.8,11,13] [4.5,5.3,6,6.6,7.2,8,8.8,9.9,11.7] 0.09282 14.01 PASS 5.29 6.871 FAIL 0.3 5.4 PASS PASS PASS_at_KS_(2/3) +unambiguous s-trigly NA NA NA NA NA NA NA all inf mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,mmol:0} 1993 30438 [0.62,0.76,0.87,0.99,1.11,1.27,1.484,1.736,2.19] [0.7,0.8,0.95,1.1,1.2,1.4,1.6,1.9,2.5] 0.09324 13.88 PASS -8.974 18.25 FAIL 0.09 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg1 NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,form:0.04} 1991 4826 [4.27,4.96,5.5,5.97,6.55,7.08,7.72,8.66,10.1] [3.7,4.5,5.08,5.6,6.14,6.7,7.31,8.2,9.73] 0.08725 9.061 PASS 5.43 7.219 FAIL 0.41 4.32 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg2 NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,form:0.04} 1988 4814 [1.42,1.854,2.14,2.41,2.67,3.01,3.35,3.9,4.64] [1.27,1.72,2.08,2.39,2.69,3.06,3.43,4,4.89] 0.04364 2.043 PASS -0.7587 0.3487 PASS 0.02 2.61 PASS PASS PASS_at_KS_(3/3) +unambiguous l-nst NA NA NA NA NA NA NA all inf % 100 {%:100} 1987 7096 [0,0,0,0,1,1,1,2,5] [0,0,0,0,1,1,1,2,5] 0.009132 0.0002801 FAIL 0.05908 0.02096 PASS 0 3 PASS PASS PASS_at_T_(2/3) +unambiguous s-kol-hdl NA NA NA NA NA NA NA all inf mmol/l 99.99 {mmol/l:99.99,mmol/:0.01,mmol/mol:0} 1987 33871 [0.99,1.12,1.22,1.31,1.39,1.49,1.6,1.74,1.94] [1,1.1,1.2,1.3,1.4,1.5,1.6,1.79,2] 0.03836 2.11 PASS -4.253 4.66 FAIL 0.01 0.78 PASS PASS PASS_at_KS_(2/3) +unambiguous s-dnanab. NA NA NA NA NA NA NA all inf kiu/l 100 {kiu/l:100} 1975 1572 [0.6,0.8,0.9,1.1,1.3,1.7,2.3,3.2,5] [0.7,0.9,1.3,2.2,6.55,14,22,37,76] 0.4659 171.5 FAIL -18.91 71.35 FAIL 5.25 17.85 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-luakptt NA NA NA NA NA NA NA all inf ratio 99.45 {ratio:99.45,form:0.55} 1952 1258 [0.97,1,1.01,1.03,1.04,1.06,1.08,1.11,1.17] [0.98,1,1.02,1.04,1.05,1.07,1.1,1.13,1.2] 0.07757 3.729 PASS -2.819 2.315 FAIL 0.01 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous s-igg3 NA NA NA NA NA NA NA all inf g/l 99.96 {g/l:99.96,form:0.04} 1951 4826 [0.13,0.17,0.2,0.24,0.27,0.31,0.37,0.45,0.58] [0.13,0.18,0.22,0.26,0.31,0.36,0.44,0.55,0.72] 0.09618 10.91 PASS -7.247 12.32 FAIL 0.04 0.39 PASS PASS PASS_at_KS_(2/3) +unambiguous p-fsh NA NA NA NA NA NA NA all inf u/l 100 {u/l:100} 1935 8372 [3.3,4.6,5.7,6.9,8.4,13,23.74,45,71] [3.41,4.8,5.9,7.2,9.4,15,30,52,73] 0.04243 2.172 PASS -2.927 2.462 FAIL 1 17.7 PASS PASS PASS_at_KS_(2/3) +unambiguous p-luakrvv NA NA NA NA NA NA NA all inf ratio 99.45 {ratio:99.45,form:0.55} 1926 1256 [0.89,0.92,0.94,0.96,0.98,1,1.03,1.06,1.14] [0.89,0.93,0.95,0.97,0.99,1.01,1.04,1.08,1.18] 0.06371 2.404 PASS -2.024 1.366 FAIL 0.01 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous p-prl NA NA NA NA NA NA NA all inf mu/l 99.81 {mu/l:99.81,nmol/l:0.19} 1914 8542 [150,186,222,261.2,306,364,439.1,550,784] [138.1,185,224,261,306,361,436,572,938.9] 0.03245 1.14 FAIL -5.431 7.242 FAIL 0 372 PASS PASS PASS_at_MAD_(1/3) +unambiguous l-bas NA NA NA NA NA NA NA all inf % 100 {%:100} 1904 7218 [0.2,0.3,0.4,0.4,0.5,0.6,0.7,0.8,1] [0.1,0.2,0.3,0.4,0.4,0.5,0.6,0.7,0.9] 0.1096 15.48 PASS 7.773 13.97 FAIL 0.1 0.6 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-crp-hy NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1836 10332 [1.8,3.2,5,7,9,13,19.5,34,61] [4.7,7,10,14,20,29,42,62,95] 0.2423 80.31 PASS -17.14 62.17 FAIL 11 42 PASS PASS PASS_at_KS_(2/3) +unambiguous p-haptog NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1821 18301 [0.65,0.9,1.09,1.3,1.5,1.69,1.96,2.26,2.78] [0.41,0.7,0.92,1.12,1.33,1.54,1.8,2.14,2.66] 0.09576 12.94 PASS 7.152 11.94 FAIL 0.17 1.68 PASS PASS PASS_at_KS_(2/3) +unambiguous ab-t NA NA NA NA NA NA NA all inf °c 100 {°c:100} 1813 1617 [36.2,36.5,36.7,36.9,37,37,37.1,37.4,37.8] [36.3,36.5,36.8,37,37,37,37.3,37.5,38] 0.0633 2.698 PASS -2.93 2.467 FAIL 0 1.2 PASS PASS PASS_at_KS_(2/3) +unambiguous p-aptt NA NA NA NA NA NA NA all inf s 100 {s:100} 1806 143489 [24,25,26,27,29,30,32,35,39] [25,26,27,28.5,30,31,33,36,46] 0.09448 13.59 PASS -13.92 41.3 FAIL 1 12 PASS PASS PASS_at_KS_(2/3) +unambiguous p-prealb NA NA NA NA NA NA NA all inf g/l 98.99 {g/l:98.99,mg/l:1.01} 1802 17703 [0.13,0.16,0.19,0.2,0.22,0.24,0.27,0.31,138.8] [0.09,0.13,0.16,0.18,0.2,0.22,0.24,0.26,0.29] 0.1505 32.11 PASS 16.05 53.57 FAIL 0.02 0.15 PASS PASS PASS_at_KS_(2/3) +unambiguous s-kol-ldl NA NA NA NA NA NA NA all inf mmol/l 99.99 {mmol/l:99.99,mmool/l:0,mmol/:0} 1798 30028 [1.6,2.1,2.4,2.7,2.9,3.3,3.6,3.9,4.5] [1.8,2.2,2.4,2.7,2.9,3.1,3.4,3.7,4.1] 0.09459 12.93 PASS 4.63 5.409 FAIL 0 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous cu-alb NA NA NA NA NA NA NA all inf ug/min 99.93 {ug/min:99.93,mg:0.07} 1778 5389 [3,5,8,15,26,47,85,173.2,428.6] [4,6,10,18,29,48.8,84,161,427.4] 0.04503 2.07 PASS 0.05861 0.02079 PASS 3 75 PASS PASS PASS_at_KS_(3/3) +unambiguous b-retind NA NA NA NA NA NA NA all inf osuus 100 {osuus:100} 1744 9157 [0.4,0.5,0.6,0.7,0.8,0.9,1,1.2,1.5] [0.4,0.5,0.7,0.8,0.9,1,1.2,1.5,1.9] 0.1196 17.99 PASS -10.57 24.99 FAIL 0.1 0.9 PASS PASS PASS_at_KS_(2/3) +unambiguous cp-gluk-po NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1737 782 [4.7,5.9,7,8.1,9.2,10.6,12.4,14.68,18.3] [4.6,5.82,7.3,8.4,9.4,10.7,12,14.18,17.49] 0.03385 0.2577 FAIL 0.504 0.2116 PASS 0.2 9.75 PASS PASS PASS_at_T_(2/3) +unambiguous f-elast1 NA NA NA NA NA NA NA all inf ug/g 99.93 {ug/g:99.93,âug/g:0.07} 1732 10975 [61.1,124,185,235,292,348,398.7,448,494.9] [48,95,144.2,197,248,302.4,357,412,470] 0.0885 9.918 PASS 7.52 13.11 FAIL 44 396 PASS PASS PASS_at_KS_(2/3) +unambiguous l-prom NA NA NA NA NA NA NA all inf % 100 {%:100} 1731 9986 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,1] 0.02093 0.276 FAIL -2.235 1.594 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous e-erytrosyytit,kokojakauma NA NA NA NA NA NA NA all inf % 100 {%:100} 1729 117212 [14,15,15,15,16,16,17,18,19] [13,13,13,13,14,14,15,16,17] 0.5122 300 FAIL 37.93 230.7 FAIL 2 3 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-mkomp-2 NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1703 27016 [0,0,0,0,0,0,0,0,0.3] [0,0,0,0,0,0,0,0,0] 0.0506 3.277 PASS 4.632 5.413 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous ly-t-cd4/8 NA NA NA NA NA NA NA all inf ratio 100 {ratio:100} 1701 115 [0.5,0.8,1.1,1.3,1.5,1.8,2.1,2.6,3.6] [0.6,0.8,1,1.26,1.6,1.84,2.08,2.42,3.16] 0.05797 0.07576 FAIL 1.434 0.8134 PASS 0.1 2.1 PASS PASS PASS_at_T_(2/3) +unambiguous l-metam NA NA NA NA NA NA NA all inf % 100 {%:100} 1617 7291 [0,0,0,0,0,1,1,1,2] [0,0,0,0,0,1,1,2,3] 0.06055 3.936 PASS -5.99 8.629 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous s-crp NA NA NA NA NA NA NA all inf mg/l 99.97 {mg/l:99.97,form:0.03,mg/ml:0} 1601 153116 [2.1,6,8,11,14,19,28,43,77] [1,2,5,7,10,14,20,32,58] 0.1583 34.43 PASS 7.877 14.22 FAIL 4 24.3 PASS PASS PASS_at_KS_(2/3) +unambiguous b-peth NA NA NA NA NA NA NA all inf umol/l 99.99 {umol/l:99.99,umol/:0.01} 1586 18209 [0.07,0.12,0.18,0.27,0.36,0.5,0.69,0.98,1.52] [0.06,0.09,0.14,0.2,0.29,0.41,0.59,0.88,1.41] 0.0811 8.068 PASS 4.388 4.917 FAIL 0.07 0.63 PASS PASS PASS_at_KS_(2/3) +unambiguous l-bla NA NA NA NA NA NA NA all inf % 100 {%:100} 1582 9301 [0,0,0,0,0,0,0,0,1] [0,0,0,0,0,0,0,0,0] 0.05241 2.943 PASS 1.476 0.8539 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous s-igg NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1567 20871 [5.912,7.672,8.67,9.5,10.27,11.1,12,13.61,17.09] [5.59,7.17,8.2,9.1,9.9,10.8,11.8,13.2,16] 0.05565 3.639 PASS 4.038 4.25 FAIL 0.37 6.9 PASS PASS PASS_at_KS_(2/3) +unambiguous p-glukpoc NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1562 957 [5.9,6.5,7,7.6,8.3,9.1,9.8,11.1,13.1] [6.06,6.7,7.3,7.8,8.4,9.2,10.2,11.2,12.94] 0.0537 1.205 FAIL -3.181 2.822 FAIL 0.1 5.1 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-mkomp-3 NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1542 25589 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.003735 -0 FAIL 1.195 0.6341 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous nu-alb NA NA NA NA NA NA NA all inf ug/min 100 {ug/min:100} 1512 442 [1,2.2,4,8,20,33,54,100.8,231.8] [3,6.2,8.3,12,15,18,26,72,195.4] 0.1773 9.15 PASS 2.014 1.354 FAIL 5 27 PASS PASS PASS_at_KS_(2/3) +unambiguous cu-alb-mi NA NA NA NA NA NA NA all inf ug/min 100 {ug/min:100} 1510 5748 [2,4,8,19,31.05,54,96,164.2,347.7] [2,3,4,6,9.9,17,34.39,79,218] 0.2215 51.18 PASS 1.206 0.6418 PASS 21.15 23.7 PASS PASS PASS_at_KS_(3/3) +unambiguous s-korsol NA NA NA NA NA NA NA all inf nmol/l 99.99 {nmol/l:99.99,nmol/:0,umol/l:0} 1508 43706 [80.7,202.4,273,322,370.5,414,471.9,542.6,663.6] [138,244,308,360,409,460,517,589,699] 0.09016 10.04 PASS -7.142 11.86 FAIL 38.5 408 PASS PASS PASS_at_KS_(2/3) +unambiguous b-inrpika NA NA NA NA NA NA NA all inf inr 100 {inr:100} 1503 1540 [2,2.2,2.4,2.5,2.6,2.8,2.9,3.2,3.5] [2,2.1,2.3,2.4,2.6,2.7,2.9,3.1,3.4] 0.04325 0.9526 FAIL 2.358 1.734 FAIL 0 1.2 PASS PASS PASS_at_MAD_(1/3) +unambiguous myel NA NA NA NA NA NA NA all inf % 100 {%:100} 1491 4482 [0,0,0,0,0,0,1,1,3.5] [0,0,0,0,0,0,1,1,3] 0.0565 2.823 PASS 1.955 1.295 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous prom NA NA NA NA NA NA NA all inf % 100 {%:100} 1475 4479 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.02467 0.3016 FAIL 3.061 2.652 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +unambiguous u-epipien NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 1465 16238 [0,0.1,0.44,0.9,1.5,2.3,3.4,5.1,8.7] [0.1,0.2,0.4,0.6,0.8,1,1.6,2.5,4.8] 0.2005 47.09 PASS 8.468 16.24 FAIL 0.7 1.8 PASS PASS PASS_at_KS_(2/3) +unambiguous happamuusaste,kapillaariveri NA NA NA NA NA NA NA all inf ph 100 {ph:100} 1457 122 [7.33,7.36,7.38,7.39,7.4,7.42,7.43,7.44,7.46] [7.35,7.38,7.39,7.41,7.42,7.43,7.44,7.45,7.48] 0.1377 1.599 PASS -3.045 2.558 FAIL 0.02 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous bla NA NA NA NA NA NA NA all inf % 100 {%:100} 1446 3320 [0,0,0,0,0,0,0,0,1] [0,0,0,0,0,0,0,0,0] 0.03304 0.6665 FAIL -1.082 0.5537 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous u-leuk-bv NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 1442 17865 [1,1.6,2.43,3.7,5.95,12.12,34.37,128.6,621] [0.9,1.7,2.7,4.2,7.3,14.04,34.2,115.4,596.2] 0.0376 1.349 PASS -0.1062 0.03837 PASS 1.35 19.2 PASS PASS PASS_at_KS_(3/3) +unambiguous fs-sappih NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 1438 3976 [2,2.5,3,4,4.8,6,6.9,8.2,12.2] [1.6,2,2.4,3,3.7,4.5,5.7,7.6,13.3] 0.1293 15.12 PASS -0.9085 0.4393 PASS 1.1 5.1 PASS PASS PASS_at_KS_(3/3) unambiguous s-mkomp-4 NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1434 25572 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.000743 -0 FAIL -1.039 0.5247 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous s-igg-sum NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1434 477 [7.15,8.28,9.149,9.91,10.74,11.57,12.7,14.21,17.21] [6.898,8.282,9.118,9.748,10.9,11.91,13.04,14.71,18.14] 0.03981 0.219 FAIL -0.4105 0.1665 PASS 0.16 7.14 PASS PASS PASS_at_T_(2/3) +unambiguous i-statcrea NA NA NA NA NA NA NA all inf umol/l 98.17 {umol/l:98.17,mmol/l:1.83} 1433 161 [55,65,71,79,88,98,110.4,129,166.6] [54,61,66,72,82,88,95,108,121] 0.1425 2.304 PASS 4.047 4.162 FAIL 6 63 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ige NA NA NA NA NA NA NA all inf u/ml 99.97 {u/ml:99.97,u/l:0.03} 1427 34187 [8,14.92,24,35,57.3,93.04,149,250.8,536.4] [8,15,23.7,36,54.7,84,137,248,607] 0.02957 0.7485 FAIL -1.366 0.764 PASS 2.6 134.1 PASS PASS PASS_at_T_(2/3) +unambiguous nlt NA NA NA NA NA NA NA all inf % 100 {%:100} 1410 4470 [15,24,35,43,49,54,60,68,76] [25,40,48,53,57.75,62,67,73,80] 0.1787 29.65 PASS -11.72 30.23 FAIL 8.75 38.25 PASS PASS PASS_at_KS_(2/3) +unambiguous p-k-vt NA NA NA NA NA NA NA all inf mmol/l 98.21 {mmol/l:98.21,1:1.79} 1404 2199 [3.4,3.6,3.7,3.8,3.9,4,4.1,4.3,4.5] [3.4,3.6,3.8,3.9,4,4,4.2,4.3,4.5] 0.02996 0.3822 FAIL -0.1062 0.03836 PASS 0.1 0.9 PASS PASS PASS_at_T_(2/3) +unambiguous metam NA NA NA NA NA NA NA all inf % 100 {%:100} 1398 3264 [0,0,0,0,0,0,0,1,3] [0,0,0,0,0,0,1,1,3] 0.1022 8.638 PASS 0.008348 0.002902 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +unambiguous nst NA NA NA NA NA NA NA all inf % 100 {%:100} 1385 3292 [0,0,0,0,0,1,1,2,5] [0,0,0,0,1,1,1,2,5] 0.08924 6.481 PASS -2.057 1.401 FAIL 1 3 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-glukoosi NA NA NA NA NA NA NA all inf mmol/l 99.93 {mmol/l:99.93,nmol/l:0.07} 1356 21503 [6.1,6.2,6.4,6.6,6.8,7,7.4,7.9,9.2] [5.1,5.3,5.5,5.7,5.9,6.1,6.5,7,8] 0.5693 300 FAIL 19.53 75 FAIL 0.9 1.8 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-igf1sds NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100} 1323 85 [-2.4,-1.5,-0.9,-0.6,-0.2,0.3,0.8,1.3,2.2] [0.4,0.6,0.82,0.96,1.2,1.4,1.5,2.3,2.72] 0.5314 20.76 FAIL -9.756 15.71 FAIL 1.4 1.5 PASS PASS PASS_at_MAD_(1/3) +unambiguous tromboplastiiniaika,inr-tulostus,plasmasta NA NA NA NA NA NA NA all inf inr 99.91 {inr:99.91,1:0.09} 1310 15979 [1,1.1,1.2,1.5,2,2.2,2.4,2.7,3] [1,1,1.1,1.4,1.9,2.2,2.5,2.7,3.1] 0.055 2.898 PASS 0.1715 0.06354 PASS 0.1 2.4 PASS PASS PASS_at_KS_(3/3) +unambiguous b-ba/abs NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 1306 797 [0.02,0.02,0.03,0.03,0.03,0.04,0.05,0.05,0.07] [0.02,0.02,0.03,0.03,0.04,0.04,0.05,0.05,0.06] 0.06841 1.737 PASS 1.33 0.7357 PASS 0.01 0.03 PASS PASS PASS_at_KS_(3/3) +unambiguous b-mo/abs NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 1306 797 [0.37,0.43,0.48,0.53,0.57,0.63,0.69,0.77,0.91] [0.36,0.43,0.49,0.54,0.58,0.65,0.71,0.79,0.93] 0.03945 0.3865 FAIL -0.2467 0.09411 PASS 0.01 0.42 PASS PASS PASS_at_T_(2/3) +unambiguous b-ly/abs NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 1306 797 [1.08,1.32,1.54,1.71,1.89,2.08,2.24,2.53,2.95] [0.916,1.15,1.35,1.53,1.75,1.93,2.14,2.418,3.028] 0.1056 4.535 PASS 2.854 2.359 FAIL 0.14 1.56 PASS PASS PASS_at_KS_(2/3) +unambiguous b-hb-vt NA NA NA NA NA NA NA all inf g/l 99.66 {g/l:99.66,hb:0.34} 1301 2922 [98,111,119,124,129,134,140,146,154] [106,116,122,127,131,135,140,146,154] 0.07122 3.694 PASS -3.499 3.322 FAIL 2 36 PASS PASS PASS_at_KS_(2/3) +unambiguous u-epilevy NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 1298 14634 [0.1,0.3,0.7,1.3,2.2,3.7,7.2,12.36,25.2] [0,0.1,0.3,0.5,0.9,1.3,2.2,4.3,10.4] 0.2038 43.16 PASS 9.13 18.63 FAIL 1.3 2.4 PASS PASS PASS_at_KS_(2/3) +unambiguous u-a1miglo NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1294 344 [7.1,9.5,12.09,15.52,19.5,25.6,33.31,43.44,64.98] [6.03,7.5,9.49,12,16,24.48,37.1,55.08,97.23] 0.1196 3.123 PASS -2.659 2.09 FAIL 3.5 29.7 PASS PASS PASS_at_KS_(2/3) +unambiguous emäsylimäärä,laskimoveri NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1291 2438 [-7.8,-5.5,-4,-3.2,-2.4,-1.7,-1.2,-0.8,-0.4] [0.5,1.2,1.7,2.3,2.9,3.5,4.3,5.3,6.9] 0.9852 300 FAIL -59.48 300 FAIL 5.3 4.8 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous du-ca NA NA NA NA NA NA NA all inf mmol 98.36 {mmol:98.36,mmol/24h:1.59,*sai:0.05} 1285 12333 [1.7,2.8,3.728,4.54,5.67,6.588,7.682,8.782,10.3] [1.77,2.74,3.61,4.5,5.39,6.3,7.4,8.7,10.76] 0.03778 1.153 FAIL -0.2523 0.09644 PASS 0.28 7.08 PASS PASS PASS_at_T_(2/3) +unambiguous crp(vo:nyhteydessäotettu),tth NA NA NA NA NA NA NA all inf mg/l 99.37 {mg/l:99.37,alle:0.63} 1267 158 [5,5,5,8,8,8,13,22,44] [5,5,5,6,8,9,13.9,18,37.9] 0.09585 0.8513 FAIL 1.094 0.5602 PASS 0 9 PASS PASS PASS_at_T_(2/3) +unambiguous pika-crp NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1257 3592 [6,8.92,12,19,26,35,50,69.8,101.4] [6,8,11,15,21,30,42,61,93] 0.06889 3.564 PASS 3.121 2.738 FAIL 5 42 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-hb NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1251 15173 [94,105,112,119,124,130,135,142,152] [98,107,115,122,128,134,140,147,157] 0.08193 6.471 PASS -5.985 8.565 FAIL 4 48 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ana NA NA NA NA NA NA NA all inf titre 99.99 {titre:99.99,mmol/mol:0.01} 1248 16685 [80,160,320,320,320,320,640,640,1280] [80,160,160,320,320,320,400,640,1280] 0.1359 18.43 PASS 2.543 1.955 FAIL 0 480 PASS PASS PASS_at_KS_(2/3) +unambiguous cb-po2 NA NA NA NA NA NA NA all inf kpa 100 {kpa:100} 1248 47686 [6.3,7.1,7.9,8.5,9.2,10,10.8,11.7,12.83] [6.3,7,7.6,8.2,8.7,9.3,10,10.8,11.9] 0.1074 11.93 PASS 7.035 11.49 FAIL 0.5 4.5 PASS PASS PASS_at_KS_(2/3) +unambiguous p-fibr NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1233 38558 [2,2.3,2.6,2.9,3.1,3.4,3.8,4.3,5.18] [1.7,2.2,2.5,2.8,3.2,3.5,4,4.6,5.6] 0.06094 3.573 PASS -3.062 2.65 FAIL 0.1 2.91 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ca-i7.4 NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1232 45578 [1.18,1.21,1.23,1.25,1.26,1.27,1.29,1.3,1.33] [1.17,1.2,1.22,1.24,1.25,1.27,1.28,1.3,1.34] 0.05625 3.015 PASS 3.286 2.982 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +unambiguous i-statna NA NA NA NA NA NA NA all inf mmol/l 98.26 {mmol/l:98.26,mmol/:1.16,umol/l:0.58} 1231 169 [132,135,137,138,139,140,141,142,143] [134,136,137,139,140,140,141,142,143] 0.0551 0.1344 FAIL -0.9083 0.438 PASS 1 6 PASS PASS PASS_at_T_(2/3) +unambiguous i-statk NA NA NA NA NA NA NA all inf mmol/l 98.81 {mmol/l:98.81,umol/l:0.6,mmol/:0.6} 1230 166 [3.3,3.6,3.7,3.8,3.9,4,4.2,4.3,4.6] [3.3,3.5,3.6,3.8,3.9,4,4.2,4.3,4.5] 0.06251 0.2274 FAIL -0.9169 0.4431 PASS 0 0.9 PASS PASS PASS_at_T_(2/3) +unambiguous p-gfreepi NA NA NA NA NA NA NA all inf ml/min/173m2 100 {ml/min/173m2:100} 1212 6373 [18.72,36.14,45.36,51.5,55.85,59.66,65.24,69.9,76.9] [23.24,37.04,43.5,48.7,53,56.3,59.6,65.8,73.1] 0.1066 9.811 PASS 3.509 3.335 FAIL 2.85 33.6 PASS PASS PASS_at_KS_(2/3) +unambiguous p-omagluk NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1212 255 [5.4,5.9,6.4,6.8,7.3,7.9,8.4,9.5,12.1] [5.8,6.2,6.6,6.9,7.3,7.8,8.7,9.6,11.36] 0.07709 0.8125 FAIL 0.3778 0.1514 PASS 0 3.6 PASS PASS PASS_at_T_(2/3) +unambiguous li-igg/alb NA NA NA NA NA NA NA all inf osuus 99.76 {osuus:99.76,ratio:0.24} 1212 823 [0.09,0.1,0.11,0.13,0.14,0.15,0.17,0.2,0.28] [0.09,0.1,0.11,0.12,0.13,0.14,0.15,0.17,0.238] 0.08623 2.899 PASS 2.772 2.249 FAIL 0.01 0.09 PASS PASS PASS_at_KS_(2/3) +unambiguous p-kreatiniini NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 1210 116933 [59,98,104,110,117,127,143,166,209] [55,61,66,71,77,83,91,103,130] 0.5727 300 FAIL 20.52 79.93 FAIL 40 45 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-hcg-tot NA NA NA NA NA NA NA all inf iu/l 100 {iu/l:100} 1197 3737 [4.8,11.8,27.38,66.42,147.2,352,1044,3432,1.564e+04] [4,10.32,28.4,72.58,183.5,425.9,1037,3053,1.542e+04] 0.03315 0.5771 FAIL -0.2025 0.07594 PASS 36.3 540.9 PASS PASS PASS_at_T_(2/3) +unambiguous s-shbg NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100,g/l:0} 1192 28134 [15,20,24,28,33,37,44,52,64] [17,21,25,29,33,38,44,52,65] 0.04081 1.366 PASS -0.7427 0.3393 PASS 0 33 PASS PASS PASS_at_KS_(3/3) +unambiguous u-sakka,eryt NA NA NA NA NA NA NA all inf u/field 100 {u/field:100} 1161 85 [0,0,0,0,1,1,2,3,8] [0,1,1,1,1,2,2.8,4,7] 0.3415 8.008 FAIL -0.516 0.2169 PASS 0 3 PASS PASS PASS_at_T_(2/3) +unambiguous u-alb-mi NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1149 6339 [1,3,4,6,8,11,18,40,143] [3,4,5.5,7.576,11,18.48,35.4,84.52,321] 0.1507 19.01 PASS -3.853 3.919 FAIL 3 24 PASS PASS PASS_at_KS_(2/3) +unambiguous s-haptog NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 1142 10330 [0.68,0.97,1,1.064,1.345,1.65,2,2.05,2.93] [0.47,0.7,0.9,1.13,1.31,1.54,1.8,2.18,2.7] 0.1397 17.24 PASS 3.316 3.028 FAIL 0.035 1.65 PASS PASS PASS_at_KS_(2/3) +unambiguous s-alb NA NA NA NA NA NA NA all inf g/l 99.91 {g/l:99.91,%:0.05,mg/g:0.03} 1141 23178 [32,35,36.4,37.5,38.6,39.6,40.9,42,44] [34,36.9,38,39,40,41,42,43,45] 0.191 34.48 PASS -9.29 19.17 FAIL 1.4 9 PASS PASS PASS_at_KS_(2/3) +unambiguous gluk-pika NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1140 727 [5.5,6.1,6.5,7.1,7.7,8.5,9.4,10.7,12.8] [5,5.5,5.9,6.2,6.6,7.2,7.9,9.08,11.4] 0.1982 15.02 PASS 5.046 6.295 FAIL 1.1 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous crppika NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1122 869 [6,9,13,19.4,27,37,51,74.8,111] [6,7,10,13,18,26,39,56,88.2] 0.126 6.51 PASS 5.477 7.312 FAIL 9 36 PASS PASS PASS_at_KS_(2/3) +unambiguous vb-hco3-st NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1122 104777 [18,20,21,23,23,24,25,26,28] [20,21,22,23,24,25,25,26,28] 0.092 7.899 PASS -4.621 5.371 FAIL 1 6 PASS PASS PASS_at_KS_(2/3) +unambiguous s-pölyer NA NA NA NA NA NA NA all inf u/ml 99.02 {u/ml:99.02,form:0.79,estimate:0.19} 1120 7301 [0.03,0.05,0.09,0.216,0.575,1.624,3.573,8.788,22.06] [0.03,0.04,0.05,0.09,0.19,0.54,1.84,5.68,16.4] 0.1304 14.12 PASS 3.206 2.861 FAIL 0.385 0.51 PASS PASS PASS_at_KS_(2/3) +unambiguous b-gluk/pi NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 1119 295 [5.3,5.8,6.3,6.7,7.4,8.1,9.2,10.4,12.84] [4.9,5.4,5.8,6.2,6.6,7.2,7.8,9.22,12.54] 0.1551 4.644 PASS 2.703 2.148 FAIL 0.8 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous s-t3-v NA NA NA NA NA NA NA all inf pmol/l 99.99 {pmol/l:99.99,pmol/:0.01} 1116 18326 [3.5,3.8,4,4.2,4.4,4.6,4.8,5.2,5.8] [3.7,4.1,4.3,4.5,4.7,4.9,5.1,5.4,6.095] 0.1496 20.28 PASS -8.972 18.04 FAIL 0.3 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous s-mpoabg NA NA NA NA NA NA NA all inf iu/ml 98.8 {iu/ml:98.8,u/ml:1.2} 1105 1315 [4.2,5.6,7.2,9.1,11,16,23,35,57] [3.6,4.8,6.2,7.7,9.7,13,18.8,28.2,49] 0.08196 3.236 PASS 2.755 2.228 FAIL 1.3 16.8 PASS PASS PASS_at_KS_(2/3) unambiguous b-crp-pik NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1059 353 [7,10,14,19,25,34,46,60,97] [9,13,17,23,30,40,51.8,72,105.8] 0.08782 1.486 PASS -2.634 2.061 FAIL 5 54 PASS PASS PASS_at_KS_(2/3) +unambiguous b-pvk+tkd,leuk NA NA NA NA NA NA NA all inf e9/l 100 {e9/l:100} 1051 3390 [4.4,5.1,5.6,6.1,6.7,7.4,8,8.7,10.2] [4.6,5.3,5.9,6.5,7.1,7.7,8.4,9.4,10.9] 0.06786 2.933 PASS -4.69 5.535 FAIL 0.4 4.8 PASS PASS PASS_at_KS_(2/3) +unambiguous s-sappih NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 1039 9064 [2,3,3,4,4.4,5.1,7,10,18] [2,2.9,3.5,4.4,6,7.6,10.7,17,32.07] 0.1419 16.11 PASS -3.752 3.738 FAIL 1.6 10.5 PASS PASS PASS_at_KS_(2/3) +unambiguous fs-c-pept NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100} 1029 14049 [0.2316,0.4,0.543,0.66,0.778,0.9108,1.08,1.329,1.705] [0.23,0.4,0.54,0.67,0.79,0.9318,1.13,1.4,1.95] 0.04121 1.126 FAIL -4.433 4.998 FAIL 0.012 1.11 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-lzm NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 1022 24683 [5.21,7.42,8.73,10,11,12,13.2,15,18.28] [1.8,8,10,11,12,13.2,14.9,16,19] 0.1322 14.68 PASS -2.802 2.287 FAIL 1 9 PASS PASS PASS_at_KS_(2/3) +unambiguous u-sakka,leuk NA NA NA NA NA NA NA all inf u/field 100 {u/field:100} 1002 85 [0,0,0,0,0,1,2,5,11.9] [0,0,0,0,0,1,1,2,5] 0.1061 0.4997 FAIL 1.483 0.8506 PASS 0 0 PASS PASS PASS_at_T_(2/3) +unambiguous s-infli NA NA NA NA NA NA NA all inf mg/l 98.47 {mg/l:98.47,ug/l:1.41,âug/ml:0.11} 998 4322 [2,3.6,5.046,6.2,7.68,8.88,10.92,13.8,18] [2.4,4.2,5.76,7.2,8.76,10.56,12.36,15,19.68] 0.09631 6.274 PASS -5.465 7.272 FAIL 1.08 12.42 PASS PASS PASS_at_KS_(2/3) +unambiguous emäsylimäärä,kapillaariveri NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 991 3926 [-8.7,-6.9,-5.1,-4,-3.2,-2.5,-1.8,-1.3,-0.7] [-5.3,-2.5,-0.5,0.6,1.6,2.6,4.1,6,9.2] 0.6661 300 FAIL -40.74 275.6 FAIL 4.8 9.6 PASS PASS PASS_at_MAD_(1/3) +unambiguous b-hba1c/pika NA NA NA NA NA NA NA all inf mmol/mol 100 {mmol/mol:100} 980 452 [39,42,45,49,52,55,60,65,74] [39,42,44,46,49.5,52,55,60,67] 0.1206 3.658 PASS 3.882 3.96 FAIL 2.5 19.5 PASS PASS PASS_at_KS_(2/3) +unambiguous pt-gfre-cg NA NA NA NA NA NA NA all inf ml/min/173m2 100 {ml/min/173m2:100} 967 10063 [40.88,49.9,56.98,62,67,73.96,81.7,90.28,106.2] [66,74,80,84.4,89,94,98,102,108] 0.4095 133.5 FAIL -20.03 75.1 FAIL 22 33 PASS PASS PASS_at_MAD_(1/3) +unambiguous c-reaktiivinenproteiini,pikatesti,veri NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 949 170 [6.88,10,13,19,28,39,52.6,73,108.2] [6,7,9,10.6,16.5,22.4,36,53.2,95] 0.1756 3.634 PASS 2.61 2.016 FAIL 11.5 31.5 PASS PASS PASS_at_KS_(2/3) +unambiguous p-psagen NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 935 36 [0.017,0.04,0.0772,0.1444,0.27,0.634,2.58,5.7,7.478] [0.043,0.09,0.135,0.21,0.325,1.36,6.91,8.74,11.7] 0.1932 0.8855 FAIL -1.625 0.9464 PASS 0.055 0.9525 PASS PASS PASS_at_T_(2/3) +unambiguous p-lh NA NA NA NA NA NA NA all inf u/l 100 {u/l:100} 927 4717 [2.76,3.9,5,5.8,6.9,8.1,10.02,15,27] [2.7,4,5,6,7.2,8.7,11,17,31] 0.03709 0.6375 FAIL -1.983 1.323 FAIL 0.3 10.5 PASS PASS PASS_at_MAD_(1/3) +unambiguous u-kemseul NA NA NA NA NA NA NA all inf form 98.04 {form:98.04,nken:0.98,leu/ul:0.98} 912 100 [0,1.01,1.015,1.02,1.022,5,5.5,6,6.5] [0,1.01,1.013,1.015,1.025,5,5,5.04,6.55] 0.2036 3.029 PASS -1 0.4952 PASS 0.0025 3.075 PASS PASS PASS_at_KS_(3/3) +unambiguous e-punasolujenkokojakauma NA NA NA NA NA NA NA all inf % 100 {%:100,1:0} 897 196955 [15,15,16,16,16,16,17,18,20] [12,13,13,13,14,14,14,15,16] 0.7021 300 FAIL 10.41 23.3 FAIL 2 3 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-rnpab NA NA NA NA NA NA NA all inf u/ml 99.79 {u/ml:99.79,titre:0.21} 871 2847 [1,1.2,1.4,1.6,1.9,2,2.6,3.3,6] [1,1.3,1.9,2,2,3,4,7,22] 0.2087 25.21 PASS -8.793 17.61 FAIL 0.1 3 PASS PASS PASS_at_KS_(2/3) +unambiguous -s.yht. NA NA NA NA NA NA NA all inf e6 100 {e6:100} 845 660 [1.44e+06,7.92e+06,1.8e+07,3.676e+07,5.8e+07,8.4e+07,1.19e+08,1.575e+08,2.325e+08] [1.89,13.28,34.35,60,84.5,110.7,146.5,212.2,288.8] 0.9278 300 FAIL 23.2 91.76 FAIL 5.8e+07 207.8 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous as-leuk NA NA NA NA NA NA NA all inf e6/l 99.9 {e6/l:99.9,e9/l:0.1} 844 2089 [89.3,136.6,190,260,354,496.2,754.1,1241,3053] [54,91,133,184,255,357,502.8,880,1893] 0.1183 7.059 PASS -1.079 0.5521 PASS 99 540 PASS PASS PASS_at_KS_(3/3) +unambiguous vb-o2sat NA NA NA NA NA NA NA all inf % 100 {%:100} 834 36026 [35.73,44.06,51.1,58.52,64.9,71.7,77.7,84.14,90.97] [41.1,54.1,61.4,66.5,70.7,75.2,80.3,87.8,94.7] 0.1483 15.38 PASS -7.379 12.43 FAIL 5.8 38.4 PASS PASS PASS_at_KS_(2/3) +unambiguous nu-albkre NA NA NA NA NA NA NA all inf mg/mmol 100 {mg/mmol:100} 830 438 [0.4,0.5,0.7,0.9,1.2,1.8,2.9,6.42,19] [0.3,0.5,0.6,0.9,1.3,2.02,4.09,8.4,22.59] 0.05622 0.5085 FAIL -1.258 0.6801 PASS 0.1 2.7 PASS PASS PASS_at_T_(2/3) +unambiguous as-eryt NA NA NA NA NA NA NA all inf e6/l 99.84 {e6/l:99.84,e9/l:0.16} 828 1263 [100,213.2,400,642.4,1000,1700,2714,5620,1.76e+04] [44.2,133.8,300,528,960,1412,2500,4560,1.318e+04] 0.09147 3.371 PASS 0.9835 0.4875 PASS 40 2655 PASS PASS PASS_at_KS_(3/3) +unambiguous u-bakt NA NA NA NA NA NA NA all inf e6/l 99.54 {e6/l:99.54,estimate:0.36,u/field:0.08} 821 12886 [0,0,0,0,0,0,0,0,0] [1,2,4,6,13,30,94,551,5237] 0.8832 300 FAIL -28.33 170.4 FAIL 13 36 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-igm NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 817 10860 [0.32,0.482,0.66,0.824,1,1.2,1.492,2.298,5.16] [0.3,0.47,0.62,0.77,0.93,1.11,1.36,1.72,2.531] 0.08061 4.016 PASS 5.405 7.075 FAIL 0.07 1.32 PASS PASS PASS_at_KS_(2/3) +unambiguous b-gluk NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 806 623 [5.1,5.5,5.8,6.2,6.7,7.4,8.4,10.1,13.35] [5,5.4,5.7,6.1,6.5,7.2,8.14,9.4,11.98] 0.05152 0.5296 FAIL 2.202 1.555 FAIL 0.2 3.6 PASS PASS PASS_at_MAD_(1/3) +unambiguous fs-pi NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 803 1919 [0.93,0.998,1.05,1.1,1.14,1.19,1.23,1.28,1.36] [0.9,0.99,1.05,1.1,1.14,1.19,1.24,1.31,1.4] 0.0568 1.306 PASS -1.103 0.5685 PASS 0 0.39 PASS PASS PASS_at_KS_(3/3) +unambiguous b-crp-pika NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 798 2088 [6,8,11,15,21,30,43,63,94.3] [6,8,11,15,21,30,44,64,102] 0.04682 0.8151 FAIL -0.7583 0.3483 PASS 0 43.5 PASS PASS PASS_at_T_(2/3) +unambiguous cu-tilav NA NA NA NA NA NA NA all inf ml 100 {ml:100} 792 2543 [320,430,500,580,667.5,760,870,988,1260] [340,440,550,630,710,800,950,1100,1350] 0.08097 3.169 PASS -4.234 4.617 FAIL 42.5 780 PASS PASS PASS_at_KS_(2/3) +unambiguous p-tpoab NA NA NA NA NA NA NA all inf u/ml 99.62 {u/ml:99.62,iu/ml:0.38} 790 2613 [7,8,10,11,13,16,36,91.4,229] [11,16,19,30,57,97,150,228,337] 0.3897 82.19 FAIL -10.57 24.93 FAIL 44 138 PASS PASS PASS_at_MAD_(1/3) +unambiguous cu-kesto NA NA NA NA NA NA NA all inf min 100 {min:100} 785 2606 [399.4,435,460,479.6,498,517.4,540,567,614] [417,447,473,491,510,532,548,575,619] 0.07564 2.725 PASS -3.683 3.621 FAIL 12 150 PASS PASS PASS_at_KS_(2/3) +unambiguous p-crppika NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 784 947 [6,8.6,12,17,25,36,51,75.4,118] [7,9,12,18,24,33,45,59.8,90] 0.06372 1.236 FAIL 3.284 2.979 FAIL 1 48 PASS PASS PASS_at_MAD_(1/3) +unambiguous b-pvk+tkd NA NA NA NA NA NA NA all inf % 98.44 {%:98.44,e9/l:0.87,pg:0.69} 782 567 [1,1,1,1,1,1,1,1,1] [7.16,8.6,10.9,25.3,32.1,38,46.48,52,59.38] 1 300 FAIL -35.92 147.4 FAIL 31.1 62.7 PASS PASS PASS_at_MAD_(1/3) +unambiguous fp-nh4-ion NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 782 22888 [19,24,30,37,45.5,56,65,79,102] [17,23,27,32,38,45,54,69,93] 0.1278 10.49 PASS 4.248 4.619 FAIL 7.5 48 PASS PASS PASS_at_KS_(2/3) +unambiguous s-ferrit NA NA NA NA NA NA NA all inf ug/l 99.98 {ug/l:99.98,umol/l:0.01,μg/l:0} 771 228321 [6,8,10,15,27,70,145,228,382] [14,22,30,39,49.7,63.4,83.9,117.7,192] 0.3013 61.63 FAIL 4.055 4.258 FAIL 22.7 87.9 PASS PASS PASS_at_MAD_(1/3) +unambiguous pt-gfreep NA NA NA NA NA NA NA all inf ml/min/173m2 100 {ml/min/173m2:100} 770 12674 [48,58,66,72,78,82,87,92.2,100] [43,54,62,68,74,80,85,90,96] 0.07235 3.024 PASS 5.294 6.82 FAIL 4 42 PASS PASS PASS_at_KS_(2/3) +unambiguous s-kysc NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 766 5489 [0.895,1.06,1.21,1.34,1.52,1.74,1.94,2.26,2.935] [0.81,0.9,0.98,1.06,1.17,1.32,1.52,1.81,2.33] 0.2412 34.15 PASS 8.276 15.33 FAIL 0.35 0.9 PASS PASS PASS_at_KS_(2/3) +unambiguous p-crp-p NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 763 188 [4.34,6,9,13,18,25.2,37,53.6,88.6] [1.2,2.4,4.51,8.38,15,21,30,45.6,67.9] 0.2116 5.68 PASS 2.473 1.857 FAIL 3 39.3 PASS PASS PASS_at_KS_(2/3) +unambiguous p-na-vt NA NA NA NA NA NA NA all inf mmol/l 98.62 {mmol/l:98.62,1:1.38} 755 2849 [132,135,136,138,139,140,141,142,144] [134,137,138,139,140,141,142,143,144] 0.1129 6.354 PASS -4.246 4.627 FAIL 1 6 PASS PASS PASS_at_KS_(2/3) +unambiguous s-e2 NA NA NA NA NA NA NA all inf nmol/l 99.99 {nmol/l:99.99,nmol/:0.01} 749 9705 [0.06,0.08,0.1,0.1206,0.15,0.19,0.2562,0.3482,0.562] [0.07,0.1,0.13,0.16,0.2,0.27,0.3794,0.55,0.99] 0.1326 10.39 PASS -8.29 15.57 FAIL 0.05 0.336 PASS PASS PASS_at_KS_(2/3) +unambiguous s-alat NA NA NA NA NA NA NA all inf u/l 99.92 {u/l:99.92,iu/l:0.08,u/i:0} 749 323438 [14,17,21,24,27,33.8,40,49,67] [14,17,20,23,26,30,35,43,57] 0.07972 3.85 PASS 3.27 2.949 FAIL 1 27 PASS PASS PASS_at_KS_(2/3) +unambiguous pd-leuk NA NA NA NA NA NA NA all inf e6/l 99.94 {e6/l:99.94,%:0.06} 745 1688 [9,17,38,84.6,157,368.6,720.8,1786,4461] [10,24,47,79,145.5,280,593.6,1324,3906] 0.049 0.7948 FAIL -0.2935 0.114 PASS 11.5 406.5 PASS PASS PASS_at_T_(2/3) +unambiguous s-cmvavi NA NA NA NA NA NA NA all inf index 100 {index:100} 742 119 [0.6,9.76,71,80.64,84,87,89,91,94] [0.086,0.34,0.4858,0.55,0.594,0.624,0.66,0.69,0.73] 0.8288 74.23 FAIL 49.4 236 FAIL 83.41 0.288 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous cu-vm NA NA NA NA NA NA NA all inf ml 100 {ml:100} 733 2761 [283.6,375.4,448,516.6,596,673.2,788.4,938,1165] [298,375,450,524,605,683,783,909,1100] 0.02735 0.1155 FAIL 1.485 0.8602 PASS 9 615 PASS PASS PASS_at_T_(2/3) +unambiguous happamuusaste,valtimoveri NA NA NA NA NA NA NA all inf ph 100 {ph:100} 725 55 [7.31,7.35,7.38,7.4,7.41,7.42,7.43,7.45,7.47] [7.344,7.378,7.39,7.4,7.42,7.42,7.43,7.442,7.466] 0.1057 0.2374 FAIL -1.264 0.6769 PASS 0.01 0.09 PASS PASS PASS_at_T_(2/3) +unambiguous p-shbg NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100} 720 790 [17,22,26,31,35,41,47,56,71] [18,23,27,30,34,38,43.3,51,64] 0.07611 1.624 PASS 2.647 2.086 FAIL 1 30 PASS PASS PASS_at_KS_(2/3) +unambiguous p-myogl NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 715 34478 [34,45.8,60,80,109,145.4,223,363.8,936.8] [35,48,66.81,93,136,212,361,694,1847] 0.101 5.942 PASS -13.18 38.4 FAIL 27 297 PASS PASS PASS_at_KS_(2/3) +unambiguous p-c3 NA NA NA NA NA NA NA all inf g/l 99.99 {g/l:99.99,form:0.01} 708 14270 [0.797,0.88,0.96,1.018,1.1,1.15,1.23,1.33,1.48] [0.75,0.87,0.95,1.02,1.1,1.18,1.26,1.35,1.49] 0.04087 0.6904 FAIL 0.04098 0.01443 PASS 0 0.6 PASS PASS PASS_at_T_(2/3) unambiguous s-psa-suh NA NA NA NA NA NA NA all inf % 99.24 {%:99.24,ug/l:0.75,ug:0.01} 699 15340 [0.33,7.684,10,11,13,14,15,20,28] [11,14.18,17,19,21,24,26.95,30.83,37] 0.4731 137.3 FAIL -23.09 89.42 FAIL 8 18 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-hcgbv NA NA NA NA NA NA NA all inf ug/l 99.79 {ug/l:99.79,pmol/l:0.21} 691 3397 [26.5,34.6,42.5,49.7,57.7,66,79.4,95.3,122] [23,32.8,41.4,49.2,58.1,68.06,80.12,99,128.4] 0.04573 0.7577 FAIL -0.4514 0.1859 PASS 0.4 71.7 PASS PASS PASS_at_T_(2/3) +unambiguous mb-be NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 691 1371 [-5.1,-3.5,-2.7,-2.2,-1.7,-1.3,-1,-0.7,-0.4] [0,0.3,0.6,1,1.4,1.8,2.5,3.2,4.3] 0.9104 300 FAIL -36.05 204.5 FAIL 3.1 3.3 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-gt NA NA NA NA NA NA NA all inf u/l 99.87 {u/l:99.87,iu/l:0.12,u/i:0} 690 178336 [12,16,19,22,27,31,43,57.2,98.3] [13,16,19,22,27,33,41,55,86] 0.03053 0.2726 FAIL 2.44 1.826 FAIL 0 36 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-fidd-o NA NA NA NA NA NA NA all inf mg/l 99.64 {mg/l:99.64,form:0.36} 670 13692 [0.2,0.2,0.3,0.3,0.4,0.5,0.7,0.9,1.6] [0.1,0.2,0.2,0.2,0.3,0.3,0.4,0.6,1] 0.2459 33.78 PASS 7.556 12.93 FAIL 0.1 0.3 PASS PASS PASS_at_KS_(2/3) +unambiguous p-c4 NA NA NA NA NA NA NA all inf g/l 99.99 {g/l:99.99,form:0.01} 663 13878 [0.1,0.14,0.16,0.188,0.2,0.23,0.25,0.28,0.32] [0.1,0.13,0.16,0.18,0.2,0.22,0.24,0.27,0.31] 0.03463 0.3724 FAIL 1.638 0.9924 PASS 0 0.18 PASS PASS PASS_at_T_(2/3) +unambiguous vb-be-vt NA NA NA NA NA NA NA all inf mmol/l 99.15 {mmol/l:99.15,1:0.85} 644 350 [-3.27,-2,-1.2,-0.6,-0.2,0.4,1.2,1.8,3.2] [-2,0,0.4,1,1.25,2,2.7,3.62,5] 0.3721 27.77 FAIL -8.151 14.82 FAIL 1.45 3.75 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-koivue NA NA NA NA NA NA NA all inf u/ml 99.97 {u/ml:99.97,form:0.03} 642 6644 [0.01,0.102,0.39,1.01,2.11,4.248,8.665,16.28,35.74] [0.01,0.03,0.15,0.52,1.39,3.288,6.98,15,34.47] 0.07874 2.879 PASS 0.1735 0.06434 PASS 0.72 4.14 PASS PASS PASS_at_KS_(3/3) +unambiguous s-d-1,25 NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100} 632 695 [55,72,84,94,103,114.6,127,142.8,169.8] [54.4,70,82,89,101,110,124,138,163] 0.04486 0.3021 FAIL 1.387 0.7804 PASS 2 81 PASS PASS PASS_at_T_(2/3) +unambiguous s-afos NA NA NA NA NA NA NA all inf u/l 99.62 {u/l:99.62,iu/l:0.38,iu/i:0} 631 62974 [68,104,114,124,133,142,153,179,243] [49,57,63,68,74,81,90,104,130] 0.5984 213.6 FAIL 11.45 27.01 FAIL 59 51 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous u-na NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 627 8849 [27,36,43,52,61,69,78,93,111] [25,32,40,48,57,68,82,99,129] 0.05533 1.274 FAIL -1.844 1.183 PASS 4 75 PASS PASS PASS_at_T_(2/3) +unambiguous hb-pika NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 619 1803 [95,111.6,120.4,126,130,135,140,146,155] [98,110,116,122,128,132,138,144,153] 0.07493 1.974 PASS 0.9116 0.4411 PASS 2 42 PASS PASS PASS_at_KS_(3/3) +unambiguous s-psa-v/t NA NA NA NA NA NA NA all inf % 100 {%:100} 617 13330 [9,12,14.98,17,20,23,26,29.88,36] [10,13,15,18,20,23,26,30,37] 0.0252 0.07657 FAIL -0.9926 0.4931 PASS 0 21 PASS PASS PASS_at_T_(2/3) +unambiguous s-ace NA NA NA NA NA NA NA all inf u/l 100 {u/l:100} 610 2199 [22,31,35,39,43,47,52,58,66] [20,28,34,38,43,48,54,61,75] 0.05903 1.165 FAIL -2.455 1.847 FAIL 0 39 PASS PASS PASS_at_MAD_(1/3) +unambiguous s-dnaab NA NA NA NA NA NA NA all inf iu/ml 100 {iu/ml:100} 609 733 [12,14,18,22,27,35,46,58,79] [11,14,18,24,31,40,56,73,109] 0.08283 1.714 PASS -4.837 5.826 FAIL 4 54 PASS PASS PASS_at_KS_(2/3) +unambiguous s-testovl NA NA NA NA NA NA NA all inf pmol/l 100 {pmol/l:100} 607 14452 [73.8,125.2,151,174,193,215,235.2,276,344.6] [80,127,152,173,195,217,243,281,360] 0.02711 0.1111 FAIL -0.4877 0.2035 PASS 2 177 PASS PASS PASS_at_T_(2/3) +unambiguous p-pc NA NA NA NA NA NA NA all inf % 99.83 {%:99.83,form:0.17} 599 7136 [85.8,98,105.4,111,117,123,131,140,156] [82,96,103,110,117,123,130,139,152] 0.03729 0.382 FAIL 0.7975 0.3712 PASS 0 51 PASS PASS PASS_at_T_(2/3) +unambiguous s-timotee NA NA NA NA NA NA NA all inf u/ml 99.9 {u/ml:99.9,form:0.08,umol/l:0.02} 594 5945 [0.02,0.14,0.378,0.73,1.15,1.938,3.472,6.654,17.45] [0.01,0.04,0.16,0.37,0.72,1.5,3.04,6.072,15] 0.1067 5.081 PASS 1.611 0.9684 PASS 0.43 2.13 PASS PASS PASS_at_KS_(3/3) +unambiguous p-hco3 NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 592 267727 [20.21,22.02,23.5,25,25.9,27.1,28.47,30.68,34.2] [20,22,23,24,25,26,27,28,30] 0.1674 14.23 PASS 7.046 11.29 FAIL 0.9 6 PASS PASS PASS_at_KS_(2/3) +unambiguous b-pco2 NA NA NA NA NA NA NA all inf kpa 100 {kpa:100} 580 34914 [4.2,4.5,4.7,4.9,5.1,5.4,5.7,6.2,6.9] [4.2,4.5,4.7,4.9,5.1,5.3,5.6,5.9,6.6] 0.06258 1.66 PASS 2.451 1.838 FAIL 0 1.5 PASS PASS PASS_at_KS_(2/3) +unambiguous b-po2 NA NA NA NA NA NA NA all inf kpa 100 {kpa:100} 579 35207 [6.18,6.8,7.2,7.6,8,8.4,8.9,9.5,10.3] [6.2,7,7.6,8,8.5,8.9,9.5,10.2,11.3] 0.1205 6.94 PASS -6.349 9.371 FAIL 0.5 3.6 PASS PASS PASS_at_KS_(2/3) +unambiguous crpvieri NA NA NA NA NA NA NA all inf mg/l 100 {mg/l:100} 575 4875 [1.3,1.78,2.4,3.16,4.3,5.6,7.38,9.3,28.6] [4,6,10,14,20,28,42,62,94] 0.5386 138.3 FAIL -20.37 76.12 FAIL 15.7 45 PASS PASS PASS_at_MAD_(1/3) +unambiguous i-statcl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 574 46 [96,99,100,101,102,103,104,105,107] [97,99,99.5,101,103,104,105,105,106.5] 0.06454 0.004833 FAIL -0.9852 0.485 PASS 1 6 PASS PASS PASS_at_T_(2/3) +unambiguous fp-kolesteroli NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 574 14065 [5.1,5.2,5.3,5.5,5.6,5.8,6,6.2,6.6] [3,3.4,3.7,4,4.3,4.6,4.9,5.3,5.9] 0.6939 264.8 FAIL 44.52 205.2 FAIL 1.3 2.4 PASS PASS PASS_at_MAD_(1/3) +unambiguous i-statglu NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 573 45 [5.3,5.64,5.96,6.28,6.6,6.9,7.5,8.4,10] [4.9,5.38,5.62,5.9,6.1,6.84,7.1,8.52,10.58] 0.1443 0.4984 FAIL 1.46 0.83 PASS 0.5 2.7 PASS PASS PASS_at_T_(2/3) +unambiguous b-co NA NA NA NA NA NA NA all inf ug/l 100 {ug/l:100} 571 3759 [1,1.2,1.4,1.9,2.4,3.1,4.1,5.6,8.5] [0.6,0.8,1,1.3,1.8,2.656,4.1,6.5,11] 0.2505 27.12 PASS -1.361 0.76 PASS 0.6 3.6 PASS PASS PASS_at_KS_(3/3) +unambiguous p-osmol NA NA NA NA NA NA NA all inf mosm/kgh2o 100 {mosm/kgh2o:100} 568 493 [251,261,268,277,283,289,293,297,306] [265.2,278.4,287,291.8,296,299.2,305,316,334] 0.2712 16.86 PASS -10.64 24.36 FAIL 13 39 PASS PASS PASS_at_KS_(2/3) +unambiguous b-laktevt NA NA NA NA NA NA NA all inf mmol/l 99.03 {mmol/l:99.03,1:0.97} 567 408 [0.726,0.872,1,1.15,1.33,1.54,1.74,2.112,2.844] [0.74,0.85,1,1.168,1.345,1.534,1.77,2.2,2.895] 0.03316 0.02394 FAIL -0.2293 0.08689 PASS 0.015 1.425 PASS PASS PASS_at_T_(2/3) +unambiguous pt-gfrekys NA NA NA NA NA NA NA all inf ml/min/173m2 100 {ml/min/173m2:100} 567 6725 [22,32,39,48,55,62,70,78,93] [12,16,20,25,32,38,47,59,78] 0.3228 48.19 FAIL 15.24 44.48 FAIL 23 48 PASS PASS PASS_at_MAD_(1/3) +unambiguous u-hyalier NA NA NA NA NA NA NA all inf e6/l 99.14 {e6/l:99.14,u/field:0.86} 565 11469 [0,0,0,0,0,0,0,0,0.3] [0,0,0,0,0,0.1,0.1,0.3,0.6] 0.2489 29.13 PASS -2.641 2.076 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous b-cr NA NA NA NA NA NA NA all inf ug/l 99.91 {ug/l:99.91,umol/l:0.09} 564 3296 [1,1.2,1.3,1.6,1.9,2.2,2.81,3.4,4.9] [0.7,1,1.2,1.4,1.7,2.1,2.7,3.7,5.6] 0.1733 12.39 PASS -0.5174 0.2182 PASS 0.2 2.4 PASS PASS PASS_at_KS_(3/3) +unambiguous s-smab NA NA NA NA NA NA NA all inf u/ml 99.82 {u/ml:99.82,form:0.18} 560 1653 [1,1,1.2,1.4,1.7,2,2,2.82,4] [1,1,1,1.5,2,2,2.2,3,10] 0.1243 5.37 PASS -2.97 2.519 FAIL 0.3 3 PASS PASS PASS_at_KS_(2/3) +unambiguous p-alaniiniaminotransferaasi NA NA NA NA NA NA NA all inf u/l 100 {u/l:100} 560 56147 [38,41,47,52,57,63,71,84,118] [13,16,18,21,23,27,31,39,54] 0.7524 300 FAIL 9.624 19.68 FAIL 34 24 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous inrpika NA NA NA NA NA NA NA all inf inr 100 {inr:100} 558 227 [1.8,1.9,2.1,2.2,2.3,2.5,2.6,2.8,3.1] [1,1,1,1,1.1,1.1,1.1,1.2,1.74] 0.8452 119.5 FAIL 3.253 2.917 FAIL 1.2 0.3 FAIL FAIL FAIL_at_MAD_(0/3) +unambiguous s-antitry NA NA NA NA NA NA NA all inf g/l 100 {g/l:100} 549 6546 [1,1.15,1.294,1.3,1.4,1.5,1.6,1.8,2] [1.11,1.23,1.3,1.4,1.45,1.5,1.6,1.73,1.97] 0.09968 4.108 PASS -2.698 2.145 FAIL 0.05 0.57 PASS PASS PASS_at_KS_(2/3) +unambiguous u-muulier NA NA NA NA NA NA NA all inf e6/l 100 {e6/l:100} 541 11537 [0,0,0,0,0,0,0,0,0.13] [0,0,0,0,0,0,0.13,0.14,0.41] 0.2081 19.39 PASS -4.755 5.692 FAIL 0 0 PASS PASS PASS_at_KS_(2/3) +unambiguous fp-c-pept NA NA NA NA NA NA NA all inf nmol/l 100 {nmol/l:100} 531 3064 [0.25,0.39,0.52,0.67,0.83,1,1.3,1.5,2] [0.293,0.46,0.58,0.7,0.83,0.98,1.13,1.38,1.8] 0.07173 1.746 PASS 0.8511 0.4034 PASS 0 1.05 PASS PASS PASS_at_KS_(3/3) +unambiguous b-fosfatidyylietanoli NA NA NA NA NA NA NA all inf umol/l 100 {umol/l:100} 530 4781 [0.08,0.13,0.197,0.3,0.435,0.6,0.82,1.22,1.95] [0.06,0.1,0.15,0.22,0.3,0.44,0.64,0.94,1.59] 0.1098 4.744 PASS 4.028 4.199 FAIL 0.135 0.66 PASS PASS PASS_at_KS_(2/3) +unambiguous s-anaab NA NA NA NA NA NA NA all inf titre 100 {titre:100} 512 701 [80,80,80,80,320,320,320,1280,1280] [80,80,80,320,320,320,320,640,1280] 0.1873 8.83 PASS 0.3732 0.1493 PASS 0 720 PASS PASS PASS_at_KS_(3/3) +unambiguous fs-fe NA NA NA NA NA NA NA all inf umol/l 99.99 {umol/l:99.99,ug/l:0,mmol/l:0} 511 41742 [4.9,6.9,8.6,10,12,13.4,15,18,23.1] [5,7.2,9,11,13,15,17,20,24] 0.09457 3.655 PASS -2.078 1.418 FAIL 1 15 PASS PASS PASS_at_KS_(2/3) +unambiguous li-igg NA NA NA NA NA NA NA all inf mg/l 99.07 {mg/l:99.07,g/l:0.93} 510 3921 [0.02,0.026,0.035,0.054,0.136,18,26.62,36.44,51.46] [14,18,22,26,30.3,36,44,55,80] 0.5196 112.3 FAIL -8.79 16.94 FAIL 30.16 36.9 PASS PASS PASS_at_MAD_(1/3) +unambiguous p-reninm NA NA NA NA NA NA NA all inf mu/l 99.93 {mu/l:99.93,µiu/ml:0.07} 510 7339 [3,5.1,8,14,19.7,27.94,42.71,84.44,191.3] [3,5.9,9.8,15,21,31.7,48.76,84,184.3] 0.05585 1.009 FAIL 0.8063 0.3763 PASS 1.3 50.7 PASS PASS PASS_at_T_(2/3) +unambiguous cb-emäsylimäärä NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 510 10576 [-7.8,-5.7,-4.03,-3.1,-2.5,-1.8,-1.3,-0.7,-0.2] [-4.7,-2.3,-0.8,0.1,0.9,1.8,2.8,4.3,6.8] 0.5633 145.6 FAIL -22.2 78.76 FAIL 3.4 7.5 PASS PASS PASS_at_MAD_(1/3) +unambiguous li-gluk NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 509 13371 [3,3.1,3.2,3.4,3.5,3.7,4,4.1,4.82] [2.9,3.1,3.3,3.4,3.5,3.7,3.8,4.1,4.8] 0.05553 1.028 FAIL 0.382 0.1533 PASS 0 1.2 PASS PASS PASS_at_T_(2/3) +unambiguous ca++/ph7.4 NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100} 507 18482 [1.08,1.12,1.13,1.14,1.15,1.16,1.21,1.26,1.34] [1.11,1.15,1.18,1.2,1.22,1.23,1.25,1.27,1.31] 0.3842 65.24 FAIL -7.092 11.37 FAIL 0.07 0.15 PASS PASS PASS_at_MAD_(1/3) +unambiguous fs-krea NA NA NA NA NA NA NA all inf umol/l 99.99 {umol/l:99.99,umol:0.01,mmol/l:0} 504 277757 [63,66,70,73,76,80,84,89,96.7] [57,62,66,69,73,77,81,87,95] 0.1243 6.511 PASS 4.432 4.942 FAIL 3 30 PASS PASS PASS_at_KS_(2/3) unambiguous p-cl NA NA NA NA NA NA NA all inf mmol/l 100 {mmol/l:100,%:0,kpa:0} 503 441201 [96.2,100,102,104,105,106,107,108,110] [98,101,103,104,105,107,108,109,111] 0.07716 2.32 PASS -3.598 3.453 FAIL 0 9 PASS PASS PASS_at_KS_(2/3) ambiguous b-hkr split_by_score 0.8595 0.9783 0 0.1094 0.04121 0.6232 low 0.8595 osuus 46.72 {%:53.16,osuus:46.72,fl:0.08} 1558906 4240703 [0.32,0.35,0.37,0.386,0.4,0.41,0.42,0.44,0.46] [0.31,0.34,0.36,0.38,0.39,0.41,0.42,0.44,0.46] 0.03919 300 PASS 10.5 25.04 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) ambiguous b-hkr split_by_score 0.8595 0.9783 0 0.1094 0.04121 0.6232 high inf % 53.16 {%:53.16,osuus:46.72,fl:0.08} 191557 4824770 [32,34,37,38,39,41,42,43,45] [30,33,36,38,39,41,42,43,45] 0.05765 300 PASS 53.64 300 FAIL 0 12 PASS PASS PASS_at_KS_(2/3) @@ -20,3 +423,108 @@ ambiguous p-tsh skipped NA NA NA 0.03165 0.1393 -3.401 all inf mu/l 97.24 {mu/l: ambiguous b-ly skipped NA NA NA 0.05066 0.4815 -8.504 all inf e9/l 97.41 {e9/l:97.41,%:2.59} 335323 784182 [0.8,1.07,1.28,1.48,1.67,1.89,2.13,2.44,2.97] [0.9,1.16,1.38,1.56,1.74,1.94,2.18,2.48,2.94] 0.05066 300 PASS -1.136 0.592 PASS 0.07 1.56 PASS PASS PASS_at_KS_(3/3) ambiguous u-suhti skipped NA NA NA 0.08946 0.09035 -0.01002 all inf kg/l 91.82 {kg/l:91.82,g/ml:6.83,ratio:1.26} 261486 41398 [1.01,1.013,1.015,1.015,1.018,1.02,1.02,1.024,1.026] [1.01,1.01,1.013,1.015,1.015,1.02,1.02,1.021,1.025] 0.1232 300 PASS -0.627 0.2752 PASS 0.003 0.015 PASS PASS PASS_at_KS_(3/3) ambiguous u-keto-o skipped NA NA NA 0.00291 0.00291 -2.615e-05 all inf estimate 94.61 {estimate:94.61,l:4.7,form:0.69} 49568 133623 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.00291 0.03687 FAIL 5.854 8.315 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-ph-o skipped NA NA NA 0.1243 0.2773 -1.23 all inf N 52.17 {N:52.17,form:47.78,70:0.03} 48516 2076 [5,5.5,6,6,6,6.5,7,7,7.5] [5.5,6,6,6,6.5,7,7,7,7.5] 0.151 39.36 PASS -16.11 54.73 FAIL 0.5 1.5 PASS PASS PASS_at_KS_(2/3) +ambiguous b-ghb-a1c skipped NA NA NA 0.1436 0.132 0.0803 all inf % 95.93 {%:95.93,mmol/mol:4.07} 39036 48557 [5.2,5.5,5.6,5.8,6.1,6.3,6.7,7.4,8.5] [5.2,5.4,5.5,5.7,5.8,6,6.3,6.8,7.8] 0.1436 300 PASS 28 170.3 FAIL 0.3 1.2 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tromboplastiiniaika,inr-tulostus skipped NA NA NA 0.1638 0.2432 -0.4845 all inf inr 57.5 {inr:57.5,1:40,form:2.5} 38382 92 [1.1,1.4,1.9,2.1,2.3,2.5,2.7,2.9,3.3] [1.8,2.1,2.2,2.3,2.5,2.66,2.7,2.9,3.1] 0.1638 1.899 PASS -2.477 1.821 FAIL 0.2 0.9 PASS PASS PASS_at_KS_(2/3) +ambiguous mono split_by_score 2.627 0.7429 0 0.4638 0.1053 0.7729 low 2.627 e9/l 15.13 {%:84.87,e9/l:15.13} 17003 7454 [0.39,0.45,0.5,0.57,0.62,0.7,0.78,0.88,1] [0.36,0.42,0.47,0.52,0.57,0.62,0.68,0.74,0.86] 0.148 98.76 PASS 22.25 107.5 FAIL 0.05 0.39 PASS PASS PASS_at_KS_(2/3) +ambiguous mono split_by_score 2.627 0.7429 0 0.4638 0.1053 0.7729 high inf % 84.87 {%:84.87,e9/l:15.13} 13637 41798 [6,7,8,8,9,10,11,12,14] [5.1,7,7.7,8,9,10,10.4,12,13.9] 0.05219 24.05 PASS 9.37 20.1 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +ambiguous baso skipped NA NA NA 0.3044 0.3402 -0.1176 all inf e9/l 13.73 {%:86.27,e9/l:13.73} 30199 8002 [0,0.02,0.03,0.04,0.05,0.08,1,1,1] [0.02,0.02,0.03,0.04,0.04,0.05,0.06,0.07,0.08] 0.3413 300 FAIL 103 300 FAIL 0.01 0.06 PASS PASS PASS_at_MAD_(1/3) +ambiguous lymf split_by_score 7.03 0.7018 0 0.4628 0.06494 0.8597 low 7.03 e9/l 13.98 {%:86.02,e9/l:13.98} 12928 7619 [0.95,1.16,1.35,1.54,1.75,1.96,2.19,2.51,3.04] [1.06,1.34,1.51,1.68,1.84,2.03,2.23,2.5,2.92] 0.09616 38.31 PASS -2.645 2.087 FAIL 0.09 1.35 PASS PASS PASS_at_KS_(2/3) +ambiguous lymf split_by_score 7.03 0.7018 0 0.4628 0.06494 0.8597 high inf % 86.02 {%:86.02,e9/l:13.98} 13769 46895 [14,18,22,25,28,31,34,38,45] [13,18,22,25,28,31,34,37,43] 0.03562 11.45 PASS 11.49 29.71 FAIL 0 24 PASS PASS PASS_at_KS_(2/3) +ambiguous s-tsh skipped NA NA NA 0.05581 0.1729 -2.098 all inf mu/l 72.2 {mu/l:72.2,miu/l:27.73,u/l:0.04} 26229 248419 [0.41,0.863,1.17,1.42,1.7,2.04,2.46,3.1,4.41] [0.62,0.91,1.13,1.39,1.6,1.84,2.2,2.62,3.5] 0.0714 104.9 PASS 8.223 15.68 FAIL 0.1 1.92 PASS PASS PASS_at_KS_(2/3) +ambiguous b-lymfos skipped NA NA NA 0.09359 0.4998 -4.34 all inf e9/l 96.27 {e9/l:96.27,%:3.73} 19817 4466 [0.89,1.12,1.3,1.48,1.65,1.83,2.05,2.34,2.83] [1.02,1.29,1.46,1.63,1.81,2,2.22,2.53,3.01] 0.09359 27.51 PASS -0.4248 0.1733 PASS 0.16 1.44 PASS PASS PASS_at_KS_(3/3) +ambiguous b-neutr skipped NA NA NA 0.07016 0.5006 -6.136 all inf e9/l 76.51 {e9/l:76.51,%:23.49} 19426 7723 [2.07,2.6,3.02,3.43,3.85,4.32,4.9,5.73,7.24] [1.9,2.34,2.756,3.158,3.59,4.07,4.67,5.41,6.87] 0.07016 23.37 PASS 4.47 5.104 FAIL 0.26 3.57 PASS PASS PASS_at_KS_(2/3) +ambiguous b-hb-a1c skipped NA NA NA 0.05016 0.3337 -5.652 all inf % 85.06 {%:85.06,mmol/mol:14.85,%/mmol:0.06} 18914 43586 [5.4,5.5,5.6,5.8,6,6.2,6.5,7.2,8.1] [5.3,5.4,5.6,5.8,5.9,6.1,6.4,6.9,7.7] 0.05016 28.55 PASS 7.633 13.63 FAIL 0.1 1.5 PASS PASS PASS_at_KS_(2/3) +ambiguous u-suhteellinentiheys skipped NA NA NA NA NA NA all inf 1 78.44 {1:78.44,kg/l:21.56} 17548 262 [1.01,1.012,1.015,1.015,1.017,1.02,1.02,1.023,1.025] [1.01,1.015,1.015,1.015,1.02,1.02,1.02,1.025,1.025] 0.1136 2.631 PASS -0.06127 0.02174 PASS 0.003 0.015 PASS PASS PASS_at_KS_(3/3) +ambiguous eos skipped NA NA NA 0.03345 0.4656 -12.92 all inf % 91.96 {%:91.96,e9/l:8.04} 14491 49739 [0,1,2,2,3,3,4,5,7] [0,1,2,2,3,3,4,5,6] 0.03345 10.61 PASS 5.809 8.197 FAIL 0 6 PASS PASS PASS_at_KS_(2/3) +ambiguous s-ttgaba skipped NA NA NA 0.01981 0.1744 -7.805 all inf u/ml 91.82 {u/ml:91.82,eliau/ml:7.73,form:0.44} 13768 32224 [0.2,0.3,0.4,0.5,0.6,0.7,0.8,1.1,1.9] [0.2,0.3,0.4,0.5,0.6,0.7,0.8,1.1,1.9] 0.01981 2.992 PASS -4.377 4.917 FAIL 0 0.9 PASS PASS PASS_at_KS_(2/3) +ambiguous neut skipped NA NA NA 0.03737 0.4535 -11.14 all inf % 93.42 {%:93.42,e9/l:6.58} 12259 61798 [42,48,52,55,58,61,64,68,74] [43.1,49,52.8,56,59,62,65,69.4,75.4] 0.03737 12.12 PASS -8.523 16.78 FAIL 1 24 PASS PASS PASS_at_KS_(2/3) +ambiguous fp-pth skipped NA NA NA 0.2661 0.2357 0.1139 all inf ng/l 80.05 {ng/l:80.05,pmol/l:19.95} 11194 122007 [7,15,36,50,63,77,92,116,169] [35,51,66,84,106,135,179,253,408] 0.2661 300 PASS -67.71 300 FAIL 43 177 PASS PASS PASS_at_KS_(2/3) +ambiguous b-erytrosyytit,tilavuusosuus skipped NA NA NA 0.1015 0.1017 -0.0023 all inf osuus 77.47 {osuus:77.47,%:22.53,1:0} 10999 292478 [0.34,0.37,0.38,0.4,0.41,0.42,0.43,0.44,0.46] [0.31,0.34,0.37,0.38,0.4,0.41,0.42,0.44,0.46] 0.1015 94.72 PASS -0.7254 0.3295 PASS 0.01 0.12 PASS PASS PASS_at_KS_(3/3) +ambiguous p-antifxa skipped NA NA NA 0.04087 0.2483 -5.077 all inf iu/ml 56.03 {iu/ml:56.03,u/ml:43.91,umol/l:0.06} 10859 13789 [0.13,0.17,0.21,0.26,0.31,0.38,0.45,0.54,0.7] [0.13,0.16,0.21,0.25,0.3,0.36,0.42,0.51,0.68] 0.04087 8.526 PASS 4.094 4.371 FAIL 0.01 0.39 PASS PASS PASS_at_KS_(2/3) +ambiguous fs-trfesat skipped NA NA NA 0.03586 0.0439 -0.2241 all inf % 80.03 {%:80.03,osuus:18.85,1:1.13} 10835 1915 [0.09,0.13,0.16,0.19,0.22,0.25,0.29,0.34,0.42] [7,11,14,17,20,23,27,32,39] 0.9897 300 FAIL -65.58 300 FAIL 19.78 24 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-happamuusaste bimodal_cautious 6.205 0.1646 0 0.395 0.5763 -0.4589 low 6.205 1 91.97 {1:91.97,5170:7.63,form:0.4} 2901 229 [5,5.5,5.5,5.5,6,6,6,6,6] [5.5,6,6,6,6,6,6.5,6.5,7] 0.3319 20.58 FAIL -13.77 31.58 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-happamuusaste bimodal_cautious 6.205 0.1646 0 0.395 0.5763 -0.4589 high inf 1 91.97 {1:91.97,5170:7.63,form:0.4} 7722 229 [6.5,6.5,7,7,7,7,7.5,7.5,8] [5.5,6,6,6,6,6,6.5,6.5,7] 0.6681 97.2 FAIL 24.78 67.43 FAIL 1 0 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous p-tromboplastiiniaika,inr-tulos skipped NA NA NA 0.02462 0.372 -14.11 all inf inr 52.05 {inr:52.05,1:47.95} 8123 6341 [1.7,2,2.2,2.3,2.5,2.6,2.8,3,3.4] [1,1.1,1.1,1.3,1.9,2.2,2.4,2.7,3.1] 0.3644 300 FAIL 44.74 300 FAIL 0.6 2.4 PASS PASS PASS_at_MAD_(1/3) +ambiguous b-pvk+t skipped NA NA NA 0.5945 0.5969 -0.003928 all inf % 43.01 {%:43.01,e9/l:23.04,g/l:13.71} 7646 8614 [1,1,1,1,1,1,1,1,1] [6,10,12,13,14,28,39,52,62] 0.9975 300 FAIL 1.556 0.9216 PASS 13 27 PASS PASS PASS_at_T_(2/3) +ambiguous s-ccpab skipped NA NA NA 0.06054 0.1375 -1.272 all inf u/ml 83.24 {u/ml:83.24,eliau/ml:15.54,form:1.22} 7611 30305 [0.6,0.7,0.9,1,1.1,1.3,1.5,1.8,5] [0.6,0.8,0.9,1,1.2,1.4,1.6,2.2,21] 0.06054 19.1 PASS -8.189 15.55 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) +ambiguous l-mono skipped NA NA NA 0.07021 0.1202 -0.7127 all inf % 97.66 {%:97.66,e9/l:2.34} 7071 58379 [2.6,5,6.9,7.6,8.1,9,10,11.3,13] [4.6,6,7,8,9,9.3,10,11.7,14] 0.07021 26.75 PASS -8.86 18.02 FAIL 0.9 6 PASS PASS PASS_at_KS_(2/3) +ambiguous l-ly split_by_score 6.662 0.7783 0 0.2055 0.05513 0.7318 low 6.662 e9/l 2.01 {%:97.98,e9/l:2.01,osuus:0} 1408 2846 [1.097,1.38,1.59,1.76,1.93,2.1,2.31,2.59,2.98] [1.1,1.3,1.5,1.7,1.83,2,2.2,2.5,2.9] 0.07858 4.785 PASS 2.455 1.849 FAIL 0.1 1.29 PASS PASS PASS_at_KS_(2/3) +ambiguous l-ly split_by_score 6.662 0.7783 0 0.2055 0.05513 0.7318 high inf % 97.98 {%:97.98,e9/l:2.01,osuus:0} 5054 138412 [15.63,19.6,23,25.9,28.2,31,34,37.7,43.57] [13,18,22,25.1,28.1,31.2,34.9,38.9,45] 0.04859 9.719 PASS 1.478 0.8553 PASS 0.1 24.3 PASS PASS PASS_at_KS_(3/3) +ambiguous p-rf skipped NA NA NA 0.2662 0.4652 -0.7473 all inf iu/ml 92.76 {iu/ml:92.76,u/ml:7.21,iu/l:0.03} 6213 10583 [5,6,7,9,11,14,20,34,86] [7,10,11,12.7,15,19,27,48.3,105] 0.2662 244.7 PASS -6.241 9.351 FAIL 4 18 PASS PASS PASS_at_KS_(2/3) +ambiguous s-fsh skipped NA NA NA 0.03077 0.4035 -12.12 all inf iu/l 51.12 {iu/l:51.12,u/l:48.88} 6137 14866 [3.1,4.6,5.9,7.1,8.9,13,23.6,44.08,69.4] [3.3,4.7,6,7.6,10.1,17.2,33.1,51.9,72.9] 0.05693 11.95 PASS -5.692 7.89 FAIL 1.2 20.7 PASS PASS PASS_at_KS_(2/3) +ambiguous u-osmoest skipped NA NA NA 0.02943 0.4084 -12.88 all inf mosm/kgh2o 60.17 {mosm/kgh2o:60.17,mosm/l:34.05,e6/l:5.78} 5941 25256 [340,440,520,550,630,700,740,850,960] [330,440,520,550,630,700,740,850,1000] 0.02943 3.326 PASS -5.525 7.464 FAIL 0 450 PASS PASS PASS_at_KS_(2/3) +ambiguous neutrofiilit bimodal 53.09 0.6531 0 0.4699 0.505 -0.0748 low 53.09 % 70.69 {%:70.69,e9/l:29.31,52%:0} 2762 25265 [1,3,5,7,11,16,23,31,42] [43,48,52,56,59,62,65,69,75] 0.8126 300 FAIL -138.2 300 FAIL 48 24 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous neutrofiilit bimodal 53.09 0.6531 0 0.4699 0.505 -0.0748 high inf % 70.69 {%:70.69,e9/l:29.31,52%:0} 1797 25265 [60,67,73,78,82,85,89,91,94] [43,48,52,56,59,62,65,69,75] 0.5689 300 FAIL 69.36 300 FAIL 23 24 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-klotsa split_by_score 35.23 0.9066 0 0.1707 0.0597 0.6502 low 35.23 nmol/l 79.87 {nmol/l:79.87,umol/l:20.06,âumol/l:0.07} 733 37623 [0.644,1,1.1,1.4,1.6,1.9,2,2.3,2.78] [586,870,1100,1312,1520,1740,1986,2304,2797] 0.9978 300 FAIL -340.1 300 FAIL 1518 1704 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-klotsa split_by_score 35.23 0.9066 0 0.1707 0.0597 0.6502 high inf nmol/l 79.87 {nmol/l:79.87,umol/l:20.06,âumol/l:0.07} 3675 37623 [526,787.4,1014,1237,1458,1687,1930,2238,2697] [586,870,1100,1312,1520,1740,1986,2304,2797] 0.04005 4.375 PASS -4.016 4.221 FAIL 62 1704 PASS PASS PASS_at_KS_(2/3) +ambiguous s-digoks skipped NA NA NA 0.03224 0.184 -4.707 all inf nmol/l 96.59 {nmol/l:96.59,ug/l:3.41} 3559 18447 [0.5,0.6,0.6,0.7,0.8,0.9,1,1.1,1.3] [0.4,0.5,0.6,0.7,0.8,0.9,1,1.1,1.4] 0.03224 2.401 PASS -3.499 3.327 FAIL 0 0.6 PASS PASS PASS_at_KS_(2/3) +ambiguous s-tshrab skipped NA NA NA 0.1548 0.2543 -0.6425 all inf iu/l 84.17 {iu/l:84.17,u/l:15.54,iu/ml:0.2} 3513 6615 [1.7,2.5,3,3.5,4.1,4.9,6.3,9,16] [1.7,2,2.4,2.9,3.3,3.9,5,7.3,14] 0.1548 47.72 PASS 5.067 6.382 FAIL 0.8 4.2 PASS PASS PASS_at_KS_(2/3) +ambiguous na skipped NA NA NA 0.5017 0.5639 -0.124 all inf mmol/l 19.19 {mmol/l:19.19,%:15.12,e9/l:14.7} 3419 8463 [1.7,2,2.1,2.3,2.4,2.6,2.9,3.2,4.4] [1.3,2,3.1,3.8,4.1,4.82,6,11.7,139] 0.5017 300 FAIL 1.791 1.134 PASS 1.7 6 PASS PASS PASS_at_T_(2/3) +ambiguous b-hba1cvt skipped NA NA NA 0.2325 0.5238 -1.252 all inf mmol/mol 58.36 {mmol/mol:58.36,%:41.64} 3196 10683 [46,51,55,58,61,64,68,74,82] [41,45,48,51,54,57,61,66,75] 0.2325 116.7 PASS 18.64 73.96 FAIL 7 24 PASS PASS PASS_at_KS_(2/3) +ambiguous s-prealb split_by_score 6.265 0.9397 0 0.3007 0.05444 0.819 low 6.265 g/l 46.45 {mg/l:53.55,g/l:46.45} 2235 33018 [0.1,0.13,0.16,0.18,0.2,0.22,0.24,0.26,0.3] [0.09,0.12,0.16,0.18,0.2,0.22,0.24,0.26,0.29] 0.03626 2.1 PASS -0.5916 0.2564 PASS 0 0.18 PASS PASS PASS_at_KS_(3/3) +ambiguous s-prealb split_by_score 6.265 0.9397 0 0.3007 0.05444 0.819 high inf mg/l 53.55 {mg/l:53.55,g/l:46.45} 955 38068 [98.4,139,161.2,188,207,229,247,269,294] [122,158,184,205,224,241,260,281,312] 0.09698 7.354 PASS -6.33 9.431 FAIL 17 147 PASS PASS PASS_at_KS_(2/3) +ambiguous s-rf skipped NA NA NA 0.03602 0.2922 -7.111 all inf iu/ml 72.43 {iu/ml:72.43,kiu/l:25.76,u/ml:1.74} 3025 11352 [5,6,7,8,9,10,11,15,40.6] [8,9,10,11,11.1,12,14,21,52.98] 0.3576 273.2 FAIL -2.897 2.423 FAIL 2.1 6.3 PASS PASS PASS_at_MAD_(1/3) +ambiguous p-inr-pika skipped NA NA NA 0.08404 0.4409 -4.247 all inf % 96.06 {%:96.06,inr:3.94} 2999 829 [1.9,2.1,2.3,2.4,2.6,2.7,2.9,3.2,3.6] [1.8,2.1,2.2,2.4,2.5,2.6,2.8,3,3.3] 0.08404 3.716 PASS 4.052 4.269 FAIL 0.1 1.2 PASS PASS PASS_at_KS_(2/3) +ambiguous s-prl skipped NA NA NA 0.101 0.2868 -1.839 all inf mu/l 94.27 {mu/l:94.27,miu/l:5.51,nmol/l:0.19} 2987 28193 [137,180,218,259,308,369,452,588.8,900.6] [115,152.1,185,220,262,314,389,522.6,840] 0.101 23.73 PASS -0.08868 0.03183 PASS 46 342 PASS PASS PASS_at_KS_(3/3) +ambiguous s-mypnabg split_by_score 26.53 0.6575 0 0.3707 0.07466 0.7986 low 26.53 eiu 82.35 {eiu:82.35,au/ml:12.74,ru/ml:4.32} 1163 7323 [0.5,0.9,1.4,2,2.7,3.7,5.3,7.5,13.18] [51,65,79,95,113,135,160,200,259.8] 0.9771 300 FAIL -129.9 300 FAIL 110.3 144 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-mypnabg split_by_score 26.53 0.6575 0 0.3707 0.07466 0.7986 high inf eiu 82.35 {eiu:82.35,au/ml:12.74,ru/ml:4.32} 1764 7323 [51,63,77,92.68,108,131,155,191,246.4] [51,65,79,95,113,135,160,200,259.8] 0.0287 0.7263 FAIL -1.654 1.008 PASS 5 144 PASS PASS PASS_at_T_(2/3) +ambiguous u-osmol skipped NA NA NA 0.01897 0.4316 -21.75 all inf mosm/kgh2o 95.64 {mosm/kgh2o:95.64,mo/kgh2o:3.88,form:0.35} 2913 7279 [175,233.4,281,323,368,412,464,534,638] [171,228,276,320,367,417,474,544,645] 0.01897 0.3605 FAIL -0.5542 0.237 PASS 1 375 PASS PASS PASS_at_T_(2/3) +ambiguous li-igg-ind skipped NA NA NA 0.1172 0.2758 -1.353 all inf osuus 80.28 {osuus:80.28,index:10.18,ratio:8.34} 2901 741 [0.41,0.44,0.47,0.49,0.51,0.54,0.59,0.69,0.99] [0.44,0.47,0.48,0.49,0.5,0.52,0.55,0.61,0.83] 0.1172 6.8 PASS 3.409 3.18 FAIL 0.01 0.12 PASS PASS PASS_at_KS_(2/3) +ambiguous b-mono skipped NA NA NA 0.1804 0.1604 0.1112 all inf e9/l 93.53 {e9/l:93.53,%:6.47} 2899 66813 [0.4,0.5,0.5,0.6,0.6,0.7,0.83,0.92,1.1] [0.32,0.4,0.48,0.5,0.59,0.61,0.7,0.8,0.92] 0.1804 78.87 PASS 10.97 26.73 FAIL 0.01 0.45 PASS PASS PASS_at_KS_(2/3) +ambiguous p-cmvnh skipped NA NA NA 0.07093 0.2561 -2.61 all inf iu/ml 82.84 {iu/ml:82.84,u/ml:17.16} 2630 7076 [45,64,90.7,130,180,270,530,1100,4600] [41,54,72,101,153,234,410.5,849,2735] 0.07093 8.109 PASS 3.115 2.73 FAIL 27 327 PASS PASS PASS_at_KS_(2/3) +ambiguous u-veri-o skipped NA NA NA 0.01783 0.01783 0 all inf form 97.62 {form:97.62,u/field:2.38} 2524 41 [0,0,0,0,0,0,0,0,0] [0,0,0,0,0,0,0,0,0] 0.01783 -0 FAIL 2.933 2.469 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-tpoab skipped NA NA NA 0.1186 0.4801 -3.048 all inf iu/ml 58.56 {iu/ml:58.56,u/ml:41.28,form:0.11} 2449 7169 [0.4,6,13.74,37,70,140.9,250,418.2,695.4] [4,8,13,31,41,64,140,271.4,546] 0.1186 22.1 PASS 7.955 14.63 FAIL 29 108 PASS PASS PASS_at_KS_(2/3) +ambiguous p-tni split_by_score 0.3025 0.3568 0 0.2752 0.1191 0.5671 low 0.3025 ng/l 89.7 {ng/l:89.7,ug/l:10.3} 520 218179 [0,0.006,0.0197,0.04,0.05,0.06,0.07,0.1,0.15] [4,5,7,10,15,24,46,119,764] 1 300 FAIL -49.15 300 FAIL 14.95 33 PASS PASS PASS_at_MAD_(1/3) +ambiguous p-tni split_by_score 0.3025 0.3568 0 0.2752 0.1191 0.5671 high inf ng/l 89.7 {ng/l:89.7,ug/l:10.3} 1889 218179 [3,4,6,9,13,23,36.6,73,201.4] [4,5,7,10,15,24,46,119,764] 0.09576 14.67 PASS -14.21 43.5 FAIL 2 33 PASS PASS PASS_at_KS_(2/3) +ambiguous u-prot split_by_score 11.23 0.6347 0 0.2275 0.1665 0.2681 low 11.23 mg/l 55.44 {mg/l:55.44,g/l:44.55,mg/dl:0} 2060 14966 [0,0.09,0.1,0.2,0.3,0.4,0.7,1,1.807] [65,82,99,119,144,181,241,386,961] 0.9994 300 FAIL -23.1 115.3 FAIL 143.7 207 PASS PASS PASS_at_MAD_(1/3) +ambiguous u-prot split_by_score 11.23 0.6347 0 0.2275 0.1665 0.2681 high inf mg/l 55.44 {mg/l:55.44,g/l:44.55,mg/dl:0} 259 14966 [34,50,71.4,76.2,89,101.8,131,196.2,412.4] [65,82,99,119,144,181,241,386,961] 0.292 19.04 PASS -7.437 12.28 FAIL 55 207 PASS PASS PASS_at_KS_(2/3) +ambiguous s-hcg-b-v skipped NA NA NA 0.01979 0.3981 -19.11 all inf ug/l 93.46 {ug/l:93.46,pmol/l:6.48,iu/l:0.02} 2184 15974 [21,30,37,45,53,63,76,95,127.4] [22.69,30.8,38,45.3,54,63.9,76,93,123] 0.01979 0.3631 FAIL 1.734 1.08 PASS 1 69 PASS PASS PASS_at_T_(2/3) +ambiguous s-mypnabm skipped NA NA NA 0.1865 0.3576 -0.9176 all inf index 56.62 {index:56.62,s/co:42.67,form:0.63} 2145 1445 [1,1.58,2,2.5,3,3.5,4.5,5.8,8.16] [1.5,2.2,2.8,3.4,4.2,5.2,6.6,8.4,11] 0.1865 25.99 PASS -11.33 28.4 FAIL 1.2 6.3 PASS PASS PASS_at_KS_(2/3) +ambiguous l-mon skipped NA NA NA 0.5543 0.7387 -0.3327 all inf % 88.17 {%:88.17,e9/l:11.83} 2104 12735 [4,8,11,12,12,13,14,15,16] [6,7,7.5,8,8.7,9,10,10.7,12] 0.5543 300 FAIL 24.12 114.2 FAIL 3.3 4.8 PASS PASS PASS_at_MAD_(1/3) +ambiguous pt-ekg-12 skipped NA NA NA 0.3239 0.3516 -0.08572 all inf form 80.56 {form:80.56,tehtu:16.67,u:2.78} 2052 58 [0,0,0,0,0,0,1,1,1] [0,0,0,0,0,0,48.5,1.029e+05,2.109e+05] 0.3239 5.039 FAIL -3.733 3.359 FAIL 0 0 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-enaab skipped NA NA NA 0.05344 0.1531 -1.865 all inf u/ml 87.7 {u/ml:87.7,ratio:12.2,titre:0.1} 1973 1690 [0.1,0.1,0.16,0.2,0.2,0.2,0.3,0.4,0.7] [0.1,0.1,0.2,0.2,0.2,0.2,0.3,0.4,1.2] 0.05344 1.978 PASS -3.039 2.622 FAIL 0 0.3 PASS PASS PASS_at_KS_(2/3) +ambiguous s-dmklots split_by_score 22.05 0.9235 0 0.266 0.1124 0.5773 low 22.05 nmol/l 61.43 {nmol/l:61.43,umol/l:38.41,âumol/l:0.14} 516 13627 [0.4,0.5,0.69,0.8,0.9,1,1,1.2,1.4] [349,489.2,603,718,842,973,1127,1319,1617] 0.9991 300 FAIL -210 300 FAIL 841.1 981 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-dmklots split_by_score 22.05 0.9235 0 0.266 0.1124 0.5773 high inf nmol/l 61.43 {nmol/l:61.43,umol/l:38.41,âumol/l:0.14} 1421 13627 [386,542,698,816,928,1061,1226,1420,1707] [349,489.2,603,718,842,973,1127,1319,1617] 0.0867 8.139 PASS 5.861 8.258 FAIL 86 981 PASS PASS PASS_at_KS_(2/3) +ambiguous p-pct skipped NA NA NA 0.2222 0.401 -0.8045 all inf ug/l 93.91 {ug/l:93.91,ng/ml:6.09} 1917 23100 [0.05,0.07,0.09,0.11,0.14,0.18,0.28,0.51,1.33] [0.07,0.1,0.14,0.2,0.28,0.42,0.72,1.5,5.461] 0.2222 76.53 PASS -1.105 0.5702 PASS 0.14 0.6 PASS PASS PASS_at_KS_(3/3) +ambiguous s-pr3ab skipped NA NA NA 0.04796 0.4704 -8.809 all inf iu/ml 75.45 {iu/ml:75.45,u/ml:23.28,kiu/l:1.27} 1866 2324 [2.55,3.6,5,6.9,9.85,15,26,39,66] [2.5,4.1,6.1,8.7,13,19,27,41,73] 0.07762 5.149 PASS -2.413 1.799 FAIL 3.15 29.1 PASS PASS PASS_at_KS_(2/3) +ambiguous s-crp-o skipped NA NA NA 0.05621 0.3942 -6.012 all inf mg/l 88.8 {mg/l:88.8,form:10.67,u/ml:0.35} 1736 2521 [5,7,10.05,14,19,28,38,57,94] [5,5,5.6,8,10,15,22,35,64] 0.2009 36.05 PASS 10.38 24.11 FAIL 9 15 PASS PASS PASS_at_KS_(2/3) +ambiguous b-tbifng skipped NA NA NA 0.0544 0.2592 -3.765 all inf iu/ml 96.03 {iu/ml:96.03,iu/l:3.93,form:0.03} 1724 2858 [0,0,0,0,0.01,0.01,0.02,0.04,0.36] [0,0,0,0,0,0.01,0.01,0.03,0.09] 0.1051 10.07 PASS 3.322 3.043 FAIL 0.01 0 FAIL PASS PASS_at_KS_(1/3) +ambiguous du-prot split_by_score 15.1 0.6975 0 0.4669 0.128 0.7258 low 15.1 mg 65.4 {mg:65.4,g:32.31,mg/24h:1.32} 915 9936 [0.13,0.2,0.3,0.436,0.6,0.8,1.1,1.71,3] [98,151,250,415,666,1040,1630,2570,4429] 0.997 300 FAIL -65.65 300 FAIL 665.4 1659 PASS PASS PASS_at_MAD_(1/3) +ambiguous du-prot split_by_score 15.1 0.6975 0 0.4669 0.128 0.7258 high inf mg 65.4 {mg:65.4,g:32.31,mg/24h:1.32} 802 9936 [101,155.2,243.9,362,500,688.4,1027,1782,3480] [98,151,250,415,666,1040,1630,2570,4429] 0.1102 7.577 PASS -5.619 7.608 FAIL 166 1659 PASS PASS PASS_at_KS_(2/3) +ambiguous s-chpnabm bimodal 0.9363 0.6431 0 0.5095 0.6149 -0.2067 low 0.9363 index 96.11 {index:96.11,u/ml:2.63,titre:0.69} 682 841 [0.08,0.102,0.13,0.144,0.17,0.2,0.25,0.298,0.37] [0.05,0.07,0.08,0.1,0.12,0.14,0.17,0.21,0.29] 0.2482 20.15 PASS -0.676 0.3017 PASS 0.05 0.15 PASS PASS PASS_at_KS_(3/3) +ambiguous s-chpnabm bimodal 0.9363 0.6431 0 0.5095 0.6149 -0.2067 high inf index 96.11 {index:96.11,u/ml:2.63,titre:0.69} 672 841 [2.3,3,3.5,4,4.5,5.2,6.2,7.5,9.99] [0.05,0.07,0.08,0.1,0.12,0.14,0.17,0.21,0.29] 0.9869 300 FAIL 19.23 65.74 FAIL 4.38 0.15 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous b-b-cd19 skipped NA NA NA 0.02213 0.1969 -7.895 all inf e9/l 66.67 {e9/l:66.67,e6/l:33.33} 1316 1826 [0,0,0,0.02,0.065,0.13,0.2,0.31,0.46] [0,0,0,0.01,0.06,0.13,0.2,0.29,0.47] 0.02213 0.07716 FAIL -2.042 1.384 FAIL 0.005 0.18 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-hepyabg skipped NA NA NA 0.3368 0.5047 -0.4986 all inf u/ml 81.11 {u/ml:81.11,index:11,eiu:4.08} 1308 4091 [0.927,2.812,10,14,30,76.2,166.5,410,1600] [0.1,0.1,0.4,10,10.7,11.6,13.8,22.9,83] 0.3368 99.57 FAIL 12.38 32.66 FAIL 19.3 30.9 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-chpnabg skipped NA NA NA 0.2142 0.2368 -0.1056 all inf eiu 42.53 {eiu:42.53,u/ml:35.3,bu/ml:10.86} 1294 1829 [4.2,7.8,10.2,12.5,15.8,32,64,81.8,128] [45,52,60,70,82,95,114,141,184] 0.5852 240.5 FAIL -23.19 108.3 FAIL 66.2 90 PASS PASS PASS_at_MAD_(1/3) +ambiguous i-stathct bimodal 0.8089 0.9655 0 0.8234 0.8337 -0.01254 low 0.8089 %pcv 60.91 {%pcv:60.91,%:35.45,mmol/l:1.82} 1018 67 [0.33,0.36,0.39,0.4,0.41,0.43,0.44,0.46,0.49] [34.6,37,38,40,41,42,44,46,46.4] 1 107.6 FAIL -53.01 55.1 FAIL 40.59 12 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous i-stathct bimodal 0.8089 0.9655 0 0.8234 0.8337 -0.01254 high inf %pcv 60.91 {%pcv:60.91,%:35.45,mmol/l:1.82} 222 67 [32,35.2,38,40,41,42,44,46,47] [34.6,37,38,40,41,42,44,46,46.4] 0.0712 0.0288 FAIL -0.7825 0.3611 PASS 0 12 PASS PASS PASS_at_T_(2/3) +ambiguous u-epitel bimodal 1.004 0.7048 0 0.3115 0.3384 -0.08642 low 1.004 /sunf 95.22 {/sunf:95.22,sunf:4.78} 902 1316 [0,0,0,0,0,1,1,1,1] [0,0,0,0,0,0,0,1,2] 0.2103 20.48 PASS -1.413 0.8017 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +ambiguous u-epitel bimodal 1.004 0.7048 0 0.3115 0.3384 -0.08642 high inf /sunf 95.22 {/sunf:95.22,sunf:4.78} 218 1316 [2,2,2,2,2,3,3,4,5] [0,0,0,0,0,0,0,1,2] 0.8685 154 FAIL 19.8 52.93 FAIL 2 0 FAIL FAIL FAIL_at_MAD_(0/3) +ambiguous c-reaktiivinenproteiini,vieritutkimus,plasmasta skipped NA NA NA 0.1044 0.5 -3.789 all inf mg/l 95 {mg/l:95,1:5} 1118 38 [3.2,6,9.01,14,20,29,41,62,95] [5.85,6.64,8.47,11,15,22.8,56.2,59.6,94.4] 0.1044 0.1088 FAIL 0.1372 0.04983 PASS 5 27.75 PASS PASS PASS_at_T_(2/3) +ambiguous s-gadab skipped NA NA NA 0.2763 0.4557 -0.6491 all inf iu/ml 77.97 {iu/ml:77.97,ru:20.5,u/ml:1.16} 1035 1685 [0.1,0.1,1,1,1,1,3.8,22.2,136] [1,1,1,1,1,2,11.8,55,207.6] 0.2763 42.88 PASS -1.673 1.025 PASS 0 0 PASS PASS PASS_at_KS_(3/3) +ambiguous s-hbsab skipped NA NA NA 0.0578 0.4865 -7.417 all inf miu/ml 70.21 {miu/ml:70.21,iu/l:16.15,u/l:12.92} 1022 6885 [15.87,27,43,69.72,100.1,153.2,230,330.8,560] [19,32,50,77,122,186,280,418,638.6] 0.05887 2.398 PASS -3.896 3.99 FAIL 21.9 294 PASS PASS PASS_at_KS_(2/3) +ambiguous s-epo skipped NA NA NA 0.06366 0.1866 -1.932 all inf u/l 69.26 {u/l:69.26,iu/l:30.18,pmol/l:0.57} 963 5377 [4.636,6.7,8.46,10.2,11.9,13.8,17,22.42,39.4] [4.442,6.49,8.1,9.9,11.9,14.5,19,29.6,61] 0.06366 2.596 PASS -4.672 5.506 FAIL 0 17.4 PASS PASS PASS_at_KS_(2/3) +ambiguous b-leuk-vt skipped NA NA NA 0.06559 0.4512 -5.879 all inf e9/l 94.85 {e9/l:94.85,ng/l:5.15} 902 2468 [5.1,5.8,6.6,7.216,7.9,8.6,9.5,10.6,12.5] [4.8,5.6,6.2,6.8,7.4,8,8.9,10,11.6] 0.08759 4.137 PASS 3.35 3.078 FAIL 0.5 5.1 PASS PASS PASS_at_KS_(2/3) +ambiguous s-osmol skipped NA NA NA 0.1024 0.3786 -2.699 all inf mosm/kgh2o 95.25 {mosm/kgh2o:95.25,mo/kgh2o:4.25,form:0.37} 886 4890 [253,260,266,272,277,284,289,293,298] [255,265,273,280,285,289,292,296,302] 0.1391 12.39 PASS -6.134 8.939 FAIL 8 33 PASS PASS PASS_at_KS_(2/3) +ambiguous hb(päiv.hoitaja) skipped NA NA NA 0.08663 0.4351 -4.022 all inf g/l 94.55 {g/l:94.55,mg/l:3.64,\':1.82} 816 52 [101,112,119,125,131,135,139,146,152] [107.2,115.2,117.6,125.2,134,136.6,143.7,147.8,158] 0.08663 0.08402 FAIL -0.4867 0.2018 PASS 3 45 PASS PASS PASS_at_T_(2/3) +ambiguous p-hcg skipped NA NA NA 0.06667 0.4737 -6.105 all inf u/l 93.13 {u/l:93.13,iu/l:6.87} 807 11637 [2,12,34,92.4,261,801,2803,7190,3.203e+04] [0,1.42,5,22,93.1,327,1061,3574,1.861e+04] 0.1679 18.36 PASS 2.548 1.958 FAIL 167.9 279.3 PASS PASS PASS_at_KS_(2/3) +ambiguous s-afp skipped NA NA NA 0.08914 0.1688 -0.894 all inf u/ml 87.73 {u/ml:87.73,ug/l:12.27} 783 17947 [2,2,3,3,4,4,5,6.3,9.86] [1.8,2.1,2.6,3,3.6,4.3,5.6,7.7,22.24] 0.08914 4.909 PASS -6.246 9.365 FAIL 0.4 4.8 PASS PASS PASS_at_KS_(2/3) +ambiguous p-krea-vt skipped NA NA NA 0.1401 0.3778 -1.697 all inf umol/l 97.09 {umol/l:97.09,mmol/l:1.52,1:1.39} 749 2804 [53,61,70,77,84,93.8,105,122,153.4] [50,58,64,69,75,82,91,104,137] 0.1401 9.855 PASS 3.337 3.059 FAIL 9 51 PASS PASS PASS_at_KS_(2/3) +ambiguous s-borrabm skipped NA NA NA 0.08807 0.4195 -3.763 all inf au/ml 40.04 {au/ml:40.04,responseequivalent/ml:32.93,ru/ml:26.71} 721 3380 [9,10,11,13,14,16,18,23,30] [3.2,4.7,6.4,8.3,12,19,25,37,57.33] 0.3548 66.44 FAIL -7.063 11.64 FAIL 2 25.2 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-etoh skipped NA NA NA 0.6116 0.659 -0.0776 all inf promille 89.71 {promille:89.71,g/l:5.5,mmol/l:4.78} 713 1369 [0,0,0,0,0,0,0,0,1] [0,0,0.1,0.584,1.4,1.9,2.4,2.8,3.5] 0.6116 163.9 FAIL -24.04 111.7 FAIL 1.4 3.9 PASS PASS PASS_at_MAD_(1/3) +ambiguous c-reaktiivinenproteiini skipped NA NA NA 0.02736 0.496 -17.13 all inf mg/l 89.59 {mg/l:89.59,1:10.41} 691 7963 [6,9,11,17,24,37,52,73,106] [4,6,9,14,23,35,52,78,126] 0.1274 8.726 PASS -3.097 2.696 FAIL 1 54 PASS PASS PASS_at_KS_(2/3) +ambiguous vb-pco2-vt skipped NA NA NA 0.08151 0.09709 -0.1911 all inf kpa 97.67 {kpa:97.67,1:2.33} 686 336 [4.35,4.73,5.05,5.32,5.54,5.73,6.03,6.42,7.125] [4.29,4.68,4.945,5.23,5.405,5.6,5.89,6.12,6.605] 0.08151 1.03 FAIL 2.307 1.67 FAIL 0.135 1.755 PASS PASS PASS_at_MAD_(1/3) +ambiguous s-lh skipped NA NA NA 0.07821 0.4403 -4.629 all inf u/l 55.18 {u/l:55.18,iu/l:44.82} 684 7086 [1.9,3,3.8,4.9,5.95,7.7,9.9,15.2,24.8] [2.1,3.2,4,4.8,5.7,6.8,8.3,11.1,20] 0.07821 3.041 PASS 1.675 1.026 PASS 0.25 7.8 PASS PASS PASS_at_KS_(3/3) +ambiguous s-chpnaba skipped NA NA NA 0.576 0.6875 -0.1936 all inf u/ml 83.03 {u/ml:83.03,eiu:16.52,au/ml:0.45} 677 1649 [2.2,2.6,3.1,3.5,4,4.7,5.4,6.4,8.5] [0.1,5.8,7.6,9.92,12.5,16.1,20.26,29,44.02] 0.576 147.6 FAIL -20.72 85.09 FAIL 8.5 21 PASS PASS PASS_at_MAD_(1/3) +ambiguous b-6-me-mp skipped NA NA NA 0.06799 0.5076 -6.466 all inf pmol/02ml 75.82 {pmol/02ml:75.82,umol/l:24.18} 637 345 [110.8,228.4,357.8,556,865,1420,2366,3990,7698] [148.6,253.4,413.6,652.4,943,1476,2268,3870,6949] 0.06799 0.6233 FAIL 0.2731 0.1052 PASS 78 2286 PASS PASS PASS_at_T_(2/3) +ambiguous s-hcg skipped NA NA NA 0.08149 0.4631 -4.683 all inf u/l 75.96 {u/l:75.96,iu/l:24.04} 630 5922 [8,18,39.4,108.9,305.1,882.7,3133,9862,3.876e+04] [6,20.1,67,173,365,665.6,1493,4279,1.685e+04] 0.08149 3.011 PASS 3.185 2.821 FAIL 59.95 1074 PASS PASS PASS_at_KS_(2/3) +ambiguous glukoosi(päiv.hoitaja) skipped NA NA NA 0.1072 0.3436 -2.207 all inf mmol/l 94.83 {mmol/l:94.83,mg/l:1.72,mmol/mol:1.72} 611 55 [4.8,5.3,5.6,6,6.5,7.1,8.1,9.3,12] [4.64,5.56,6,6.42,6.9,7.68,8.68,10.92,12.3] 0.1072 0.2451 FAIL -0.2648 0.1013 PASS 0.4 4.5 PASS PASS PASS_at_T_(2/3) +ambiguous b-6-tgn skipped NA NA NA 0.04105 0.4988 -11.15 all inf pmol/02ml 76.99 {pmol/02ml:76.99,umol/l:23.01} 609 368 [75,109.6,128.4,151.2,180,208.8,233,280,373.4] [77.7,103,129,148.8,176,201.2,226,270.6,361.6] 0.04105 0.08917 FAIL 1.002 0.4993 PASS 4 192 PASS PASS PASS_at_T_(2/3) +ambiguous p-bkvnh skipped NA NA NA 0.1023 0.3688 -2.607 all inf iu/ml 63.26 {iu/ml:63.26,u/ml:36.74} 608 260 [37,75,170,310,590,1300,3590,1.56e+04,6.26e+04] [33.9,51.8,97,203,457,1040,2660,6988,2.86e+04] 0.1023 1.39 PASS 2.359 1.73 FAIL 133 1278 PASS PASS PASS_at_KS_(2/3) +ambiguous u-hb-o skipped NA NA NA 0.4009 0.4216 -0.05158 all inf form 77.38 {form:77.38,A:22.62} 584 65 [0,0,0,0,1,1,1,2,3] [0,0,0,0,0,0,0,0,1] 0.4009 8.226 FAIL -0.9449 0.4581 PASS 1 0 FAIL PASS PASS_at_T_(1/3) +ambiguous s-dnanab skipped NA NA NA 0.1624 0.3624 -1.231 all inf iu/ml 49.21 {iu/ml:49.21,u/ml:32.3,kiu/l:17.77} 584 3166 [1.13,2,6,12,15.5,22,32,44.4,64] [1,2,3,4.9,9,13,19,30,59] 0.1624 11.11 PASS 1.767 1.111 PASS 6.5 23.1 PASS PASS PASS_at_KS_(3/3) +ambiguous s-hepyaba skipped NA NA NA 0.2831 0.3522 -0.2439 all inf u/ml 97.89 {u/ml:97.89,responseequivalent:1.35,form:0.73} 551 4131 [10,10.9,11.9,13,16,20.4,28,44,69] [0.1,3.7,10.1,10.5,11.1,12,13.8,18,34] 0.2848 34.61 PASS 8.281 15.17 FAIL 4.9 13.5 PASS PASS PASS_at_KS_(2/3) +ambiguous pt-fibrosis-4indeksi skipped NA NA NA 0.1764 0.5468 -2.101 all inf 1 54.1 {1:54.1,u/l:45.9} 550 33 [0.64,0.79,0.94,1.096,1.24,1.41,1.613,1.982,2.591] [0.796,1.01,1.124,1.31,1.38,1.466,1.61,1.732,2.068] 0.1764 0.5916 FAIL 0.8331 0.3883 PASS 0.14 0.99 PASS PASS PASS_at_T_(2/3) +ambiguous i-staturea skipped NA NA NA 0.1905 0.5058 -1.655 all inf mmol/l 97.5 {mmol/l:97.5,\':2.5} 522 39 [3.7,4.5,5.23,6.1,6.9,7.8,8.8,10.5,13.49] [4.82,5.32,5.54,6.22,6.9,7.78,8.56,10.28,11.14] 0.1905 0.9034 FAIL 1.581 0.9314 PASS 0 5.1 PASS PASS PASS_at_T_(2/3) +ambiguous s-dgpabg skipped NA NA NA 0.05991 0.4106 -5.854 all inf au 28.01 {eliau/ml:48.32,au:28.01,u/ml:23.62} 506 593 [2,3,6,9,12,17,23,33,74] [2,3,6,8,12,15.2,20,26,49.4] 0.05991 0.5738 FAIL 2.222 1.575 FAIL 0 27 PASS PASS PASS_at_MAD_(1/3) diff --git a/scripts/injection/data/plot_data.json b/scripts/injection/data/plot_data.json index 22d1239..cdc2344 100644 --- a/scripts/injection/data/plot_data.json +++ b/scripts/injection/data/plot_data.json @@ -1 +1 @@ -{"b-eryt": {"outcome": "PASS", "decided_by": "KS", "prevalence": "{e12/l:99.99,%:0.01,e9/l:0}", "n_candidate": 2702234, "n_target": 8026175, "ecdf": {"c_x": [-10.0, 2.52, 2.69, 2.8, 2.89, 2.9699999999999998, 3.03, 3.1, 3.15, 3.2, 3.26, 3.3, 3.34, 3.39, 3.42, 3.46, 3.5, 3.5300000000000002, 3.57, 3.6, 3.63, 3.66, 3.7, 3.7199999999999998, 3.74, 3.77, 3.8, 3.82, 3.85, 3.87, 3.9, 3.91, 3.94, 3.96, 3.99, 4.0, 4.02, 4.05, 4.07, 4.09, 4.1, 4.12, 4.14, 4.16, 4.18, 4.2, 4.21, 4.23, 4.25, 4.27, 4.29, 4.3, 4.31, 4.33, 4.35, 4.37, 4.39, 4.4, 4.41, 4.43, 4.45, 4.47, 4.49, 4.5, 4.5, 4.52, 4.54, 4.5600000000000005, 4.58, 4.6, 4.61, 4.63, 4.65, 4.67, 4.6899999999999995, 4.7, 4.71, 4.74, 4.76, 4.78, 4.8, 4.82, 4.84, 4.87, 4.9, 4.91, 4.9399999999999995, 4.98, 5.0, 5.04, 5.08, 5.11, 5.16, 5.2, 5.26, 5.32, 5.4, 5.52, 5.7, 10.0], "c_y": [2e-05, 0.01012, 0.02022, 0.03032, 0.04042, 0.05052, 0.06062, 0.07072, 0.08082, 0.09092, 0.10102, 0.11112, 0.12122, 0.13132, 0.14142, 0.15152, 0.16162, 0.17172, 0.18182, 0.19192, 0.20202, 0.21212, 0.22222, 0.23232, 0.24242, 0.25254, 0.26264, 0.27274, 0.28284, 0.29294, 0.30304, 0.31314, 0.32324, 0.33334, 0.34344, 0.35354, 0.36364, 0.37374, 0.38384, 0.39394, 0.40404, 0.41414, 0.42424, 0.43434, 0.44444, 0.45454, 0.46464, 0.47474, 0.48484, 0.49494, 0.50506, 0.51516, 0.52526, 0.53536, 0.54546, 0.55556, 0.56566, 0.57576, 0.58586, 0.59596, 0.60606, 0.61616, 0.62626, 0.63636, 0.64646, 0.65656, 0.66666, 0.67676, 0.68686, 0.69696, 0.70706, 0.71716, 0.72726, 0.73736, 0.74746, 0.75758, 0.76768, 0.77778, 0.78788, 0.79798, 0.80808, 0.81818, 0.82828, 0.83838, 0.84848, 0.85858, 0.86868, 0.87878, 0.88888, 0.89898, 0.90908, 0.91918, 0.92928, 0.93938, 0.94948, 0.95958, 0.96968, 0.97978, 0.98988, 1.0], "t_x": [1.1400000000000001, 2.6, 2.77, 2.89, 2.98, 3.04, 3.1, 3.19, 3.22, 3.3, 3.33, 3.39, 3.42, 3.48, 3.5, 3.55, 3.6, 3.61, 3.66, 3.7, 3.71, 3.75, 3.8, 3.8, 3.84, 3.88, 3.9, 3.91, 3.94, 3.98, 4.0, 4.0, 4.03, 4.06, 4.1, 4.1, 4.11, 4.14, 4.16, 4.19, 4.2, 4.2, 4.22, 4.25, 4.27, 4.29, 4.3, 4.3, 4.32, 4.34, 4.37, 4.39, 4.4, 4.4, 4.42, 4.44, 4.46, 4.48, 4.5, 4.5, 4.51, 4.53, 4.55, 4.57, 4.59, 4.6, 4.6, 4.62, 4.64, 4.66, 4.6899999999999995, 4.7, 4.7, 4.71, 4.74, 4.77, 4.79, 4.8, 4.8, 4.83, 4.86, 4.89, 4.9, 4.91, 4.9399999999999995, 4.98, 5.0, 5.01, 5.05, 5.1, 5.1, 5.16, 5.2, 5.23, 5.3, 5.36, 5.42, 5.53, 5.7, 9.2], "t_y": [2e-05, 0.01012, 0.02022, 0.03032, 0.04042, 0.05052, 0.06062, 0.07072, 0.08082, 0.09092, 0.10102, 0.11112, 0.12122, 0.13132, 0.14142, 0.15152, 0.16162, 0.17172, 0.18182, 0.19192, 0.20202, 0.21212, 0.22222, 0.23232, 0.24242, 0.25254, 0.26264, 0.27274, 0.28284, 0.29294, 0.30304, 0.31314, 0.32324, 0.33334, 0.34344, 0.35354, 0.36364, 0.37374, 0.38384, 0.39394, 0.40404, 0.41414, 0.42424, 0.43434, 0.44444, 0.45454, 0.46464, 0.47474, 0.48484, 0.49494, 0.50506, 0.51516, 0.52526, 0.53536, 0.54546, 0.55556, 0.56566, 0.57576, 0.58586, 0.59596, 0.60606, 0.61616, 0.62626, 0.63636, 0.64646, 0.65656, 0.66666, 0.67676, 0.68686, 0.69696, 0.70706, 0.71716, 0.72726, 0.73736, 0.74746, 0.75758, 0.76768, 0.77778, 0.78788, 0.79798, 0.80808, 0.81818, 0.82828, 0.83838, 0.84848, 0.85858, 0.86868, 0.87878, 0.88888, 0.89898, 0.90908, 0.91918, 0.92928, 0.93938, 0.94948, 0.95958, 0.96968, 0.97978, 0.98988, 1.0], "ks_marker": {"x": 4.09, "y_lo": 0.34, "y_hi": 0.4}, "ks": {"stat": 0.05101436343880278, "mlogp": 300.0, "passed": true}}, "kde_linear": {"c_x": [-10.0, -9.746835443037975, -9.49367088607595, -9.240506329113924, -8.987341772151899, -8.734177215189874, -8.481012658227847, -8.227848101265822, -7.974683544303797, -7.7215189873417724, -7.468354430379747, -7.215189873417721, -6.962025316455696, -6.708860759493671, -6.455696202531645, -6.20253164556962, -5.949367088607595, -5.69620253164557, -5.443037974683544, -5.189873417721518, -4.936708860759493, -4.6835443037974684, -4.430379746835443, -4.177215189873417, -3.924050632911392, -3.670886075949367, -3.4177215189873413, -3.1645569620253156, 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b/scripts/injection/html/index.html index f6671f1..c25f724 100644 --- a/scripts/injection/html/index.html +++ b/scripts/injection/html/index.html @@ -39,9 +39,9 @@

Unit injection results

-
Scatter: TEST_NAMEs by count and prevalence
+
Scatter: TEST_NAMEs by count and prevalence
-

Category summary

Active threshold: 98% — min count: 1,000 — 542 TEST_NAMEs, 31,839,159 measurements

+

Category summary

Active threshold: 98% — min count: 500 — 715 TEST_NAMEs, 31,962,504 measurements

@@ -57,43 +57,43 @@

Unit injection results

- - - - - - + + + + + + - - - - - - + + + + + + - - - - - - + + + + + + - - - - - - + + + + + + - + @@ -107,8 +107,8 @@

Unit injection results

UNAMBIGUOUS AMBIGUOUS NO_DATA TOTAL names meas names meas names meas names meas ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- -All 10/10 2,874,565/2,874,565 10/10 5,300,918/5,300,918 26/140 284,033/1,062,191 46/160 8,459,516/9,237,674 -OMOP-mapped 10/10 2,874,565/2,874,565 10/10 5,300,918/5,300,918 26/61 284,033/797,892 46/81 8,459,516/8,973,375 +All 10/10 2,800,937/2,800,937 10/10 5,300,918/5,300,918 28/202 285,698/1,108,898 48/222 8,387,553/9,210,753 +OMOP-mapped 9/9 2,800,434/2,800,434 10/10 5,300,918/5,300,918 28/66 285,698/802,091 47/85 8,387,050/8,903,443 ------ ------------------- ------ ------------------- ------ ------------------- ------ ------------------- @@ -119,8 +119,8 @@

Unit injection results
95%342 (63.1%)26,444,780 (83.1%)60 (11.1%)4,332,188 (13.6%)140 (25.8%)1,062,191 (3.3%)434 (60.7%)26,508,342 (82.9%)79 (11.0%)4,345,264 (13.6%)202 (28.3%)1,108,898 (3.5%)
98% *326 (60.1%)24,919,426 (78.3%)76 (14.0%)5,857,542 (18.4%)140 (25.8%)1,062,191 (3.3%)413 (57.8%)24,979,594 (78.2%)100 (14.0%)5,874,012 (18.4%)202 (28.3%)1,108,898 (3.5%)
99%309 (57.0%)22,898,275 (71.9%)93 (17.2%)7,878,693 (24.7%)140 (25.8%)1,062,191 (3.3%)392 (54.8%)22,954,996 (71.8%)121 (16.9%)7,898,610 (24.7%)202 (28.3%)1,108,898 (3.5%)
100%220 (40.6%)12,707,871 (39.9%)182 (33.6%)18,069,097 (56.8%)140 (25.8%)1,062,191 (3.3%)275 (38.5%)12,745,902 (39.9%)238 (33.3%)18,107,704 (56.7%)202 (28.3%)1,108,898 (3.5%)
TOTAL542715
- - + +
Test nameTypeOutcomeUnitUnit prev (%)N candN targetKS statKS −log10pKS passT statT −log10pT passMAD distMAD thrMAD passNotesBEST_UNIT
Test nameTypeCutoffOutcomeUnitUnit prev (%)N candN targetKS statKS −log10pKS passT statT −log10pT passMAD distMAD thrMAD passNotes
@@ -130,10 +130,10 @@

Unit injection results