id stringlengths 12 33 | analyte stringlengths 3 66 | loinc stringlengths 6 14 ⌀ | unit stringlengths 1 13 ⌀ | population stringclasses 2
values | sex stringclasses 3
values | age_min int64 5 40 | age_max float64 18 50 ⌀ | measure_type stringclasses 6
values | sa_value stringlengths 14 278 | general_value stringlengths 8 67 ⌀ | direction_of_risk stringclasses 2
values | provenance_tier stringclasses 3
values | evidence_grade stringclasses 2
values | source_labels stringlengths 39 224 | source_urls stringlengths 32 162 | source_refs stringlengths 13 80 ⌀ | source_kinds stringlengths 9 36 | sources_in_registry stringclasses 6
values | overclaim_guard stringlengths 90 261 ⌀ | notes stringlengths 21 203 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
bmi-overweight-category | BMI | PRAJNA-BMI | kg/m2 | south_asian | any | 18 | null | reference_range | overweight_at=23; obese_at=27.5 | overweight_at=25; obese_at=30 | high | guideline-endorsed | null | WHO Expert Consultation — appropriate BMI for Asian populations (Lancet 2004) | https://doi.org/10.1016/S0140-6736(03)15268-3 | DOI:10.1016/S0140-6736(03)15268-3; PMID:14726171 | guideline | true | Lower cutoffs reflect earlier metabolic risk, not a different disease; do not restate as 'South Asians are unhealthy at normal weight'. | Encoded in loinc.yaml as PRAJNA-BMI ref_high 23. Source in evidence registry as who-asian-bmi-2004 (grade A, approved). obese_at corrected 25->27.5 (WHO 2004 Asian high-risk action point; 2026-07-11). |
bmi-diabetes-screening-threshold | BMI (diabetes screening trigger) | PRAJNA-BMI | kg/m2 | south_asian | any | 30 | null | screening_threshold | comparator=>=; value=23 | comparator=>=; value=25 | high | guideline-endorsed | A | Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2024 | Optimum BMI cut points to screen Asian Americans for type 2 diabetes (Araneta/Kanaya, Diabetes Care 2015) | https://doi.org/10.2337/dc24-S002 | https://pubmed.ncbi.nlm.nih.gov/25665815/ | DOI:10.2337/dc24-S002 | PMID:25665815 | guideline | primaryStudy | true | true | A screening trigger is not a diagnosis; a positive trigger means 'test glucose', not 'has diabetes'. | SouthAsianScreeningPack.diabetesScreenBMI23 (v2024.2), fires from age 30. |
diabetes-screening-age | Diabetes screening start age | 1558-6 | year | south_asian | any | 30 | null | screening_age | comparator=>=; value=30 | comparator=>=; value=35 | null | guideline-endorsed | A | ADA Standards of Care 2024 | Araneta/Kanaya, Diabetes Care 2015 | https://doi.org/10.2337/dc24-S002 | https://pubmed.ncbi.nlm.nih.gov/25665815/ | DOI:10.2337/dc24-S002 | PMID:25665815 | guideline | primaryStudy | true | true | null | South Asians develop dysglycaemia ~a decade earlier; screen earlier. |
waist-central-obesity-male | Waist circumference (central obesity) | 56115-9 | cm | south_asian | male | 18 | null | screening_threshold | comparator=>=; value=90 | comparator=>=; value=102 | high | guideline-endorsed | null | IDF consensus worldwide definition of the metabolic syndrome — ethnic-specific waist cutoffs | https://www.idf.org/e-library/consensus-statements/60-idfconsensus-worldwide-definitionof-the-metabolic-syndrome.html | null | consensus | true | null | loinc.yaml 56115-9 ref_high 90 encodes the male SA cut. |
waist-central-obesity-female | Waist circumference (central obesity) | 56115-9 | cm | south_asian | female | 18 | null | screening_threshold | comparator=>=; value=80 | comparator=>=; value=88 | high | guideline-endorsed | null | IDF consensus worldwide definition of the metabolic syndrome | https://www.idf.org/e-library/consensus-statements/60-idfconsensus-worldwide-definitionof-the-metabolic-syndrome.html | null | consensus | true | null | SouthAsianScreeningPack.isCentralObesity female cut = 80 cm. |
waist-to-height-ratio | Waist-to-height ratio | null | ratio | south_asian | any | 18 | null | screening_threshold | comparator=>=; value=0.5 | comparator=>=; value=0.5 | high | study-derived | null | Comparison of obesity indices for CVD risk classification in South Asian adults — The CARRS Study (Patel et al., PLoS One 2017) | https://doi.org/10.1371/journal.pone.0174251 | DOI:10.1371/journal.pone.0174251; PMID:28448582 | primaryStudy | true | WtHR >=0.5 is a general adiposity rule; the South-Asian-specific claim is that it outperforms BMI here, not a distinct cutoff. | Used in SouthAsianScreeningPack.isCentralObesity as a fallback when waist+height on file. Source in evidence registry as carrs-patel-2017 (review_status: proposed — awaiting clinician sign-off). |
hdl-low-female | HDL-C (low threshold) | 2085-9 | mg/dL | south_asian | female | 18 | null | risk_flag | comparator=<; value=50 | comparator=<; value=40 | low | guideline-endorsed | null | IDF metabolic syndrome consensus (2006) | Prevention of ASCVD in South Asians — NLA clinical perspective (2021) | https://www.idf.org/e-library/consensus-statements/60-idfconsensus-worldwide-definitionof-the-metabolic-syndrome.html | https://doi.org/10.1016/j.jacl.2021.03.007 | | DOI:10.1016/j.jacl.2021.03.007 | consensus | consensus | true | true | null | IDF sex-specific low-HDL cut; women flagged at <50. |
hdl-low-male | HDL-C (low threshold) | 2085-9 | mg/dL | south_asian | male | 18 | null | risk_flag | comparator=<; value=40 | comparator=<; value=40 | low | guideline-endorsed | null | IDF metabolic syndrome consensus (2006) | https://www.idf.org/e-library/consensus-statements/60-idfconsensus-worldwide-definitionof-the-metabolic-syndrome.html | null | consensus | true | Male cut equals the general threshold; the SA-specific piece is the female cut and the pattern's weight, not this value. | Included for completeness so the male/female contrast is explicit. |
atherogenic-dyslipidemia-pattern | Atherogenic dyslipidemia (TG-high + HDL-low) | 2571-8 | composite | south_asian | any | 18 | null | risk_flag | triglycerides_mg_dl=>=150; with_low_hdl=True | null | high | study-derived | null | AHA Scientific Statement — ASCVD in South Asians (Volgman 2018) | Lipid Association of India SA lipid targets (Enas 2013) | Risk factors for early MI in South Asians (INTERHEART, JAMA 2007) | https://doi.org/10.1161/CIR.0000000000000580 | https://pmc.ncbi.nlm.nih.gov/articles/PMC3868060/ | https://doi.org/10.1001/jama.297.3.286 | DOI:10.1161/CIR.0000000000000580 | PMCID:PMC3868060 | DOI:10.1001/jama.297.3.286 | guideline | consensus | primaryStudy | true | true | true | A normal LDL-C does not rule out risk when TG is high and HDL low; do not present LDL-C as the sole lipid target for SA users. | The SA-characteristic pattern (small-dense LDL, high ApoB/ApoA-I) that drives risk at normal LDL-C. Component values match general thresholds; the differentiation is the emphasis. |
apob-preferred-marker | ApoB (preferred atherogenic marker) | 1884-6 | mg/dL | south_asian | any | 18 | null | reference_range | low=60; high=90 | low=60; high=90 | high | study-derived | null | NLA — Prevention of ASCVD in South Asians (2021) | AHA Volgman 2018 | https://doi.org/10.1016/j.jacl.2021.03.007 | https://doi.org/10.1161/CIR.0000000000000580 | DOI:10.1016/j.jacl.2021.03.007 | DOI:10.1161/CIR.0000000000000580 | consensus | guideline | true | true | The range is not SA-specific; the SA-specific claim is preference of ApoB over LDL-C, not a different cutoff. | SouthAsianScreeningPack.apobPreferred nudges ApoB when a lipid panel exists but ApoB doesn't. |
lpa-elevated-and-test-once | Lp(a) | 10835-7 | mg/dL | south_asian | any | 18 | null | risk_flag | elevated_at=50; test_frequency=once_in_adulthood | elevated_at=50; test_frequency=once_in_adulthood | high | guideline-endorsed | A | NLA 2024 Lp(a) focused update / AHA 2024 Lp(a) toolkit | 2018 AHA/ACC/Multi-Society Blood Cholesterol Guideline | https://professional.heart.org/en/-/media/PHD-Files/Education/AHA2024_Lpa_Toolkit_Healthcare_Professionals.pdf | https://doi.org/10.1161/CIR.0000000000000625 | | DOI:10.1161/CIR.0000000000000625 | guideline | guideline | true | true | Do NOT claim South Asians universally run high Lp(a): MASALA (Huffman 2019) found no Lp(a)-atherosclerosis signal within the cohort. The rationale is 'genetically fixed + test-once is cheap', plus higher elevated-prevalence, not a proven SA outcome association. | The 'test once' guidance is guideline-endorsed and not SA-specific; it appears here because it is under-done in this population. loinc.yaml Lp(a) mass ref_high 30 mg/dL, molar 43583-7 ref_high 75 nmol/L. |
non-hdl-aggressive-target | Non-HDL-C (treatment target) | PRAJNA-NONHDL | mg/dL | south_asian | any | 18 | null | reference_range | high=130; note=LAI recommends more aggressive non-HDL targets by risk stratum | high=130 | high | study-derived | null | Lipid Association of India SA lipid targets (Enas 2013) | https://pmc.ncbi.nlm.nih.gov/articles/PMC3868060/ | PMCID:PMC3868060 | consensus | true | LAI targets are risk-stratified; do not present a single non-HDL cutoff as applying to all SA users. | Default non-HDL ref_high 130 from loinc.yaml; SA-specific aggressiveness is stratum-dependent — represented qualitatively pending clinician review. |
hba1c-under-read-caveat | HbA1c (interpretation caveat) | 4548-4 | % | south_asian | any | 18 | null | interpretation_caveat | confirm_when=5.7-6.4; confirm_with=fasting glucose or OGTT | reference_range_low=4.0; reference_range_high=5.6 | high | study-derived | null | Isolated HbA1c identifies a different T2D subgroup vs glucose in Asian Indians — CARRS & MASALA (Gujral 2019) | ADA Standards of Care 2024 | https://pubmed.ncbi.nlm.nih.gov/31150721/ | https://doi.org/10.2337/dc24-S002 | PMID:31150721 | DOI:10.2337/dc24-S002 | primaryStudy | guideline | true | true | HbA1c is not universally 'wrong' in SA users; the claim is that it can under- or over-read (iron deficiency, glycation rate), so borderline values warrant glucose confirmation. | The reference range is not changed; this is an interpretation flag on borderline values. |
cac-baseline-age | Coronary artery calcium — baseline discussion age | PRAJNA-CAC | year | south_asian | any | 35 | null | screening_age | comparator=>=; value=35 | comparator=>=; value=40 | null | guideline-endorsed | null | AHA Scientific Statement — ASCVD in South Asians (Volgman 2018) | https://doi.org/10.1161/CIR.0000000000000580 | DOI:10.1161/CIR.0000000000000580 | guideline | true | null | SA develop CAD ~10 years earlier; earlier baseline CAC discussion. In-app, CAC nudges tie to PREVENT 5-<20% band. |
vitamin-d-screening-emphasis | 25-OH Vitamin D (screening emphasis) | 1989-3 | ng/mL | south_asian | any | 18 | null | reference_range | low=30; high=100 | low=30; high=100 | low | study-derived | null | Endocrine Society — Evaluation, Treatment, and Prevention of Vitamin D Deficiency (2011) | https://doi.org/10.1210/jc.2011-0385 | DOI:10.1210/jc.2011-0385 | guideline | true | The reference range is not SA-specific; the SA-relevant point is high deficiency prevalence, warranting screening — not a different normal range. | SouthAsianScreeningPack.vitaminDScreen prompts if not measured within a year. |
fasting-insulin-optional-marker | Fasting insulin (optional early marker) | 1554-5 | uIU/mL | south_asian | any | 30 | null | reference_range | low=2; high=15 | low=2; high=15 | high | study-derived | B | MASALA cardiometabolic profile / HOMA-IR vs MESA (Kanaya 2014) | https://masalastudy.org/publications/ | null | primaryStudy | true | Explicitly NOT guideline-backed; present as an optional/exploratory marker, never as recommended screening. | In-app copy flags this as not guideline-backed. Good example of an honest study-derived row. |
egfr-race-adjustment-deprecated | eGFR (race/ancestry adjustment) | 33914-3 | mL/min/1.73m2 | general | any | 18 | null | deprecated_adjustment | adjust=False; guidance=do NOT apply a race/ancestry coefficient | low=60; high=120 | low | contested-deprecated | null | New Creatinine- and Cystatin C–Based Equations without Race (CKD-EPI 2021, Inker et al., NEJM) | https://doi.org/10.1056/NEJMoa2102953 | DOI:10.1056/NEJMoa2102953; PMID:34554658 | primaryStudy | true | Do NOT ship an ancestry-adjusted eGFR. The 2021 refit removed the race term as a social-not-biological construct that delayed care. This row exists to instruct consumers to NOT stratify eGFR by ancestry. | The credibility showcase row: an adjustment the field is moving away from, included precisely to warn against it. Consistent with loinc.yaml keeping eGFR at real LOINC 33914-3 with no ancestry term. |
prevent-risk-underestimate-caveat | 10-year ASCVD risk (PREVENT) | PRAJNA-PREVENT | % | south_asian | any | 30 | null | interpretation_caveat | adjustment=none available; guidance=treat estimate as a floor; it underestimates SA risk | low=0; high=5 | high | study-derived | null | Development and Validation of the AHA PREVENT Equations (Circulation 2024) | https://doi.org/10.1161/CIRCULATIONAHA.123.067626 | DOI:10.1161/CIRCULATIONAHA.123.067626 | guideline | true | There is no validated SA multiplier in PREVENT; do not invent one. State the limitation ('treat as a floor'), do not apply a made-up adjustment. | Contrast with the eGFR row: here we flag under-estimation but still refuse to fabricate an adjustment. loinc.yaml PRAJNA-PREVENT plain_language already says 'treat it as a floor'. |
triglycerides-risk-enhancer | Triglycerides (risk-enhancer threshold) | 2571-8 | mg/dL | south_asian | any | 18 | null | risk_flag | comparator=>=; value=175 | comparator=>=; value=175 | high | guideline-endorsed | null | 2018 AHA/ACC/Multi-Society Blood Cholesterol Guideline | https://doi.org/10.1161/CIR.0000000000000625 | DOI:10.1161/CIR.0000000000000625 | guideline | true | The 175 mg/dL cut is not SA-specific; the SA-relevant point is that atherogenic dyslipidemia (high TG + low HDL) reaches it often even at a normal LDL-C. | Completes the atherogenic-dyslipidemia composite inputs. TG LOINC 2571-8. |
hscrp-risk-enhancer | hs-CRP (risk-enhancer threshold) | 30522-7 | mg/L | south_asian | any | 18 | null | risk_flag | comparator=>=; value=2 | comparator=>=; value=2 | high | guideline-endorsed | null | 2018 AHA/ACC/Multi-Society Blood Cholesterol Guideline | https://doi.org/10.1161/CIR.0000000000000625 | DOI:10.1161/CIR.0000000000000625 | guideline | true | The >=2 mg/L cut is not SA-specific; SA users more often exceed it due to higher visceral adiposity at the same BMI. | hs-CRP LOINC 30522-7. |
sa-ancestry-ascvd-risk-enhancer | South Asian ancestry (ASCVD risk-enhancing factor) | null | null | south_asian | any | 18 | null | interpretation_caveat | ancestry_is_ascvd_risk_enhancer=True; guidance=The 2018 AHA/ACC guideline lists South Asian ancestry as a formal ASCVD risk-enhancing factor; use it to move borderline/intermediate-risk patients toward the treat decision. | null | high | guideline-endorsed | null | 2018 AHA/ACC/Multi-Society Blood Cholesterol Guideline | https://doi.org/10.1161/CIR.0000000000000625 | DOI:10.1161/CIR.0000000000000625 | guideline | true | A risk-enhancer is not a risk multiplier; it does not by itself diagnose disease or mandate a statin — it shifts the borderline decision. | Explicitly named in the 2018 AHA/ACC Cholesterol Guideline risk-enhancer list. |
sa-very-high-risk-lipid-targets | LDL-C / non-HDL-C (SA very-high-risk targets) | PRAJNA-NONHDL | mg/dL | south_asian | any | 18 | null | interpretation_caveat | ldl_c_target_very_high_risk=<70; non_hdl_target_very_high_risk=<100; guidance=LAI recommends more aggressive LDL-C/non-HDL targets for SA very-high-risk patients. | ldl_c_target_very_high_risk=<70; non_hdl_target_very_high_risk=<130 | high | study-derived | null | Lipid Association of India SA lipid targets (Enas 2013) | NLA — Prevention of ASCVD in South Asians (2021) | https://pmc.ncbi.nlm.nih.gov/articles/PMC3868060/ | https://doi.org/10.1016/j.jacl.2021.03.007 | PMCID:PMC3868060 | DOI:10.1016/j.jacl.2021.03.007 | consensus | consensus | true | true | LAI targets are risk-stratified; do not present a single cutoff as applying to all SA users. LDL-C <70 matches general very-high-risk guidance; the SA-specific piece is the tighter non-HDL target. | Tightens the non-HDL-130 reference row for the very-high-risk stratum. review pending clinician sign-off. |
bmi-masld-screening-threshold | BMI (MASLD / fatty-liver screening trigger) | PRAJNA-BMI | kg/m2 | south_asian | any | 18 | null | screening_threshold | comparator=>=; value=23 | comparator=>=; value=25 | high | guideline-endorsed | null | Multi-society Delphi consensus statement on new fatty liver disease nomenclature (MASLD) (Rinella et al., 2023) | Ectopic fat depots and coronary artery calcium in South Asians vs other ethnic groups (Garg et al., JAHA 2016) | https://doi.org/10.1097/HEP.0000000000000520 | https://pubmed.ncbi.nlm.nih.gov/27856485/ | DOI:10.1097/HEP.0000000000000520 | PMID:27856485 | consensus | primaryStudy | false | false | A lower screening BMI reflects earlier ectopic-fat accumulation, not a different disease; MASLD is diagnosed by imaging/enzymes, not by BMI alone. | SA carry the highest intrahepatic fat of MESA ethnic groups at lower BMI (Garg 2016). MASLD nomenclature (2023) uses BMI >=23 for Asian populations. |
score2-south-asian-multiplier | SCORE2 10-year CVD risk (South Asian multiplier) | PRAJNA-PREVENT | % | south_asian | any | 40 | null | interpretation_caveat | multiplier_indian_bangladeshi=1.3; multiplier_pakistani=1.7; guidance=Multiply the SCORE2 estimate by the ancestry-specific factor before applying risk thresholds. | multiplier=1.0 | high | guideline-endorsed | null | 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice | https://doi.org/10.1093/eurheartj/ehab484 | DOI:10.1093/eurheartj/ehab484 | guideline | false | The multiplier applies to SCORE2 specifically (derived from QRISK3 data); do not transplant it onto PREVENT or the Pooled Cohort Equations, which have no validated SA multiplier. | The only major guideline with a numeric SA correction factor (2021 ESC, Class IIa LOE B). Companion to the PREVENT 'treat as a floor' caveat row. |
cac-south-asian-percentiles | Coronary artery calcium (South Asian age/sex percentiles) | PRAJNA-CAC | Agatston | south_asian | any | 40 | null | reference_range | prevalence_cac_gt0={'age50': {'men': 0.45, 'women': 0.2}, 'age60': {'men': 0.7, 'women': 0.4}, 'age70': {'men': 0.9, 'women': 0.7}}; p75_age60={'men': 186, 'women': 26}; guidance=Use age/sex-specific percentiles, not the raw 100 cutoff, for younger SA patients. | null | high | study-derived | null | South Asian coronary artery calcium age/sex percentiles — MASALA + DILWALE (Tasdighi et al., JACC Advances 2025) | https://pubmed.ncbi.nlm.nih.gov/40402122/ | PMID:40402122 | primaryStudy | false | These are cohort percentiles (MASALA+DILWALE), not a guideline threshold; CAC=0 remains reassuring at age 50 (55% of men, 80% of women) but less so at 70. | First SA-specific CAC percentile table to exist (n=2,743, ASCVD-free). review pending clinician sign-off. |
remnant-cholesterol-sa-marker | Remnant cholesterol (optional atherogenic marker) | PRAJNA-REMNANT | mg/dL | south_asian | any | 18 | null | risk_flag | comparator=>=; value=33 | null | high | study-derived | null | Remnant cholesterol and incident coronary artery calcium in South Asians — MASALA (Manghis et al., J Clin Lipidol 2025) | https://pubmed.ncbi.nlm.nih.gov/41168049/ | PMID:41168049 | primaryStudy | false | Explicitly not a guideline cutoff; the top MASALA quartile (>=~33 mg/dL) was associated with incident CAC, not CAC progression. Present as exploratory. Calculate as total cholesterol - HDL-C - LDL-C. | MASALA: Q4 vs Q1 OR 2.57 for incident CAC over 5y, independent of LDL-C. review pending clinician sign-off. |
apol1-not-south-asian | APOL1 kidney-risk variants (ancestry misattribution) | null | null | general | any | 18 | null | deprecated_adjustment | adjust=False; guidance=Do NOT apply APOL1 G1/G2 kidney-risk stratification to South Asians — these variants are high-frequency only in West-African ancestry (<1% in non-Africans). | null | null | contested-deprecated | null | APOL1 kidney-risk variants are West-African ancestry–specific (review) | https://pmc.ncbi.nlm.nih.gov/articles/PMC5495568/ | PMCID:PMC5495568 | primaryStudy | false | This row exists to instruct consumers NOT to use APOL1 in a South Asian risk model; including it would be a false-ancestry-attribution error. | Credibility-showcase 'do-not-apply' row, in the spirit of the deprecated eGFR row. |
aldh2-adh1b-not-south-asian | ALDH2*2 / ADH1B*2 alcohol-flush variants (ancestry misattribution) | null | null | general | any | 18 | null | deprecated_adjustment | adjust=False; guidance=Do NOT surface alcohol-flush / fast-metabolizer warnings for South Asians based on ALDH2*2 or ADH1B*2 — these are predominantly East Asian (low single-digit % in SA). | null | null | contested-deprecated | null | ALDH2*2 / ADH1B*2 alcohol-metabolism variants are predominantly East Asian (review) | https://pmc.ncbi.nlm.nih.gov/articles/PMC10594868/ | PMCID:PMC10594868 | primaryStudy | false | This row exists to instruct consumers NOT to apply East-Asian alcohol-metabolism genetics to South Asians. | Credibility-showcase 'do-not-apply' row. South Asians more often carry the slower ADH1B*1. |
vitamin-b12-screening-emphasis | Vitamin B12 (screening emphasis) | 2132-9 | pg/mL | south_asian | any | 18 | null | reference_range | low=200; high=900 | low=200; high=900 | low | study-derived | null | Hyperhomocysteinemia & cobalamin (B12) deficiency in Asian Indians (Refsum et al., Am J Clin Nutr 2001) | Vitamin B12 deficiency & hyperhomocysteinemia in rural and urban Indians (Yajnik et al., JAPI 2006) | https://doi.org/10.1093/ajcn/74.2.233 | https://pubmed.ncbi.nlm.nih.gov/17214273/ | DOI:10.1093/ajcn/74.2.233; PMID:11470726 | PMID:17214273 | primaryStudy | primaryStudy | false | false | The reference range is not SA-specific; the SA-relevant point is high deficiency prevalence in vegetarian South Asians, warranting screening — not a different normal range. | Exact parallel to the vitamin-D screening-emphasis row. B12 LOINC 2132-9. |
thalassemia-carrier-screening | Thalassemia / hemoglobinopathy carrier screening | 30428-7 | fL | south_asian | any | 18 | null | interpretation_caveat | mcv_below=80; confirm_with=hemoglobin electrophoresis / HbA2; guidance=Offer carrier screening in South Asian ancestry (higher β-thalassemia, HbE, HbD-Punjab prevalence), especially preconception; low MCV with normal iron warrants electrophoresis. | null | low | guideline-endorsed | null | ACOG Practice Bulletin No. 78: Hemoglobinopathies in Pregnancy (Obstet Gynecol 2007) | https://doi.org/10.1097/00006250-200701000-00055 | DOI:10.1097/00006250-200701000-00055; PMID:17197616 | guideline | false | A carrier trait is not a disease; screening informs reproductive counseling and explains a spuriously altered HbA1c — it is not a diagnosis. | Also the mechanism behind the HbA1c interpretation caveat. MCV LOINC 30428-7. |
normal-alt-masld-caveat | ALT (MASLD interpretation caveat) | 1742-6 | U/L | south_asian | any | 18 | null | interpretation_caveat | guidance=A normal ALT does not exclude MASLD; in SA with metabolic risk, use imaging (ultrasound / hepatic-fat) rather than relying on enzymes. | null | high | study-derived | null | Proportion of NAFLD/MASLD patients with normal ALT: systematic review & meta-analysis (BMC Gastroenterol 2020) | https://doi.org/10.1186/s12876-020-1165-z | DOI:10.1186/s12876-020-1165-z; PMID:31937252; PMCID:PMC6961232 | primaryStudy | false | ALT is not universally unreliable; the point is that a normal value is insufficient to rule out fatty liver in a high-metabolic-risk SA profile. | Pairs with the BMI-23 MASLD screening trigger. ALT LOINC 1742-6. |
benign-ethnic-neutropenia | WBC / neutrophils (benign ethnic neutropenia) | 6690-2 | 10*3/uL | south_asian | any | 18 | null | interpretation_caveat | guidance=A mildly low WBC / absolute neutrophil count can be a normal ancestry-linked variant; do not over-investigate isolated mild neutropenia without other features. | null | low | study-derived | null | Benign ethnic neutropenia (Atallah-Yunes et al., Blood Rev 2019) | https://doi.org/10.1016/j.blre.2019.06.003 | DOI:10.1016/j.blre.2019.06.003; PMID:31255364; PMCID:PMC6702066 | primaryStudy | false | Benign ethnic neutropenia is best-established for African ancestry; the South Asian evidence base is thinner — flag it as a possibility, not a rule. | Included with an explicit evidence-strength caveat. WBC LOINC 6690-2. |
slco1b1-statin-pgx | SLCO1B1 rs4149056 (statin pharmacogenomics) | null | null | south_asian | any | 18 | null | interpretation_caveat | variant=SLCO1B1 rs4149056 (c.521T>C); action=In decreased-function carriers, limit simvastatin dose and prefer rosuvastatin or pravastatin.; frequency_note=C-allele frequency in SA is broadly comparable to White populations (~15-20%). | null | null | guideline-endorsed | null | CPIC Guideline for SLCO1B1/ABCG2/CYP2C9 & statin-associated musculoskeletal symptoms (Clin Pharmacol Ther 2022) | https://doi.org/10.1002/cpt.2557 | DOI:10.1002/cpt.2557; PMID:35152405; PMCID:PMC9035072 | guideline | false | The recommendation is genotype-guided statin selection, not SA-specific dosing; there is no SA-specific dosing table. | CPIC 2022 statin/SLCO1B1 guideline. Default move in SA with statin myalgia: consider genotyping and switch off simvastatin before declaring intolerance. |
pediatric-bmi-iap | Pediatric BMI (IAP South Asian cut-offs) | PRAJNA-BMI | percentile | south_asian | any | 5 | 18 | reference_range | overweight_percentile=75; obese_percentile=95; adult_equivalent=overweight = adult BMI 23, obese = adult BMI 27 at age 18 | overweight_percentile=85; obese_percentile=95 | high | guideline-endorsed | null | Revised IAP 2015 growth charts / BMI cut-offs for 5-18y Indian children (Khadilkar et al., Indian J Endocrinol Metab 2015) | https://doi.org/10.4103/2230-8210.159028 | DOI:10.4103/2230-8210.159028; PMID:26180761; PMCID:PMC4481652 | guideline | false | These are cardiometabolic-risk-adjusted centiles on IAP 2015 charts; under-5 growth still follows WHO international standards regardless of ethnicity. | Plot SA children on CDC and IAP charts; when CDC says normal but IAP says at-risk, treat as at-risk. IAP 2015 (Khadilkar). |
lean-diabetes-phenotype | Diabetes risk at low BMI (lean-diabetes phenotype) | PRAJNA-BMI | kg/m2 | south_asian | any | 18 | null | interpretation_caveat | guidance=Do not gate diabetes-risk screening on BMI>=25 — T2D at BMI<25 is 2-4x more common in Asian Indians. Screen from BMI 23 and use waist-to-height >=0.5. | null | high | study-derived | null | Young-onset diabetes in Asian Indians linked to lower beta-cell function (INSPIRED; Diabetologia 2022) | https://doi.org/10.1007/s00125-022-05671-z | DOI:10.1007/s00125-022-05671-z; PMID:35247066; PMCID:PMC9076730 | primaryStudy | false | Lean diabetes reflects reduced β-cell function / 'thin-fat' body composition, not the absence of metabolic risk; a normal BMI is not reassurance. | INSPIRED study. Reinforces the BMI-23 diabetes-screening trigger. |
gdm-early-screening | Gestational diabetes (early screening in SA) | null | null | south_asian | female | 18 | 50 | interpretation_caveat | early_screen=first-trimester screening for high-risk groups including South Asian ancestry; iadpsg_75g_ogtt_cutoffs=FPG>=92, 1h>=180, 2h>=153 mg/dL (numeric cutoffs unchanged); guidance=SA women develop GDM at lower BMI and earlier in pregnancy; screen earlier, same thresholds. | screen=24-28 weeks | high | guideline-endorsed | null | IADPSG recommendations on diagnosis & classification of hyperglycemia in pregnancy (Diabetes Care 2010) | Diagnosis and Classification of Diabetes: Standards of Care in Diabetes—2024 | https://doi.org/10.2337/dc09-1848 | https://doi.org/10.2337/dc24-S002 | DOI:10.2337/dc09-1848; PMID:20190296; PMCID:PMC2827530 | DOI:10.2337/dc24-S002 | consensus | guideline | false | true | The diagnostic thresholds are unchanged; the SA-specific action is earlier screening, not a different cutoff. | IADPSG 2010; ADA 2024 §15 (Pregnancy); FIGO 2015. |
menopause-age-sa | Age at natural menopause (South Asian women) | null | year | south_asian | female | 40 | null | reference_range | median_age=49; early_or_premature_le45_pct=0.3; guidance=~30% of US SA women experience early/premature menopause (<=45y) vs <7% in other US groups. | median_age=50-51 (US White/Black) | null | study-derived | null | Menopausal experience (hot flashes, urinary incontinence, mood) among South Asian American women — MASALA (Lyu et al., Climacteric 2025) | https://doi.org/10.1080/13697137.2025.2480584 | DOI:10.1080/13697137.2025.2480584; PMID:40177961; PMCID:PMC12353937 | primaryStudy | false | Cohort estimate (n=405); earlier menopause raises cardiometabolic risk earlier but is not itself a disease. | Lyu, Climacteric 2025. New domain: women's health. |
parity-cardiometabolic-sa | Parity (cardiometabolic effect, SA women) | null | null | south_asian | female | 18 | null | interpretation_caveat | high_parity=>=2 live births; effect_over_5y_vs_0_1=SBP +8.9 mmHg, DBP +4.1 mmHg, LDL-C +8.9 mg/dL | null | high | study-derived | null | Association of Parity With ASCVD Risk Factors Among South Asian Women — MASALA (Mehta et al., JACC Advances 2026) | https://doi.org/10.1016/j.jacadv.2026.102647 | DOI:10.1016/j.jacadv.2026.102647 | primaryStudy | false | Association from MASALA (n~415); parity is a risk-context flag, not a screening threshold. | Mehta, JACC Advances 2026. Surface on women's cardiometabolic panels. |
mthfr-not-sa-variant | MTHFR C677T as an 'SA variant' (misattribution) | null | null | general | any | 18 | null | deprecated_adjustment | adjust=False; guidance=Do NOT treat MTHFR C677T as a South Asian homocysteine variant — it is not enriched in SA. Elevated homocysteine here is driven by dietary (vegetarian) B12 deficiency; treat the B12, not the SNP. | null | null | contested-deprecated | null | Hyperhomocysteinemia & cobalamin (B12) deficiency in Asian Indians (Refsum et al., Am J Clin Nutr 2001) | https://doi.org/10.1093/ajcn/74.2.233 | DOI:10.1093/ajcn/74.2.233; PMID:11470726 | primaryStudy | false | Credibility-showcase 'do-not-apply' row: the actionable target is B12 status, not MTHFR genotyping. | Driver evidence: Refsum 2001 (B12 deficiency → hyperhomocysteinemia in Indians). |
apob-apoa1-ratio | ApoB/ApoA-I ratio (lead SA atherogenic metric) | PRAJNA-APOBA1 | ratio | south_asian | any | 18 | null | interpretation_caveat | note=The ApoB/ApoA-I ratio was the strongest single modifiable MI predictor in South Asians (INTERHEART; population-attributable risk ~47%).; guidance=Where available, weight the ApoB/ApoA-I ratio over LDL-C alone for SA risk discussions. | null | high | study-derived | null | Risk factors for early MI in South Asians (INTERHEART, JAMA 2007) | https://doi.org/10.1001/jama.297.3.286 | DOI:10.1001/jama.297.3.286 | primaryStudy | true | No SA-specific numeric ratio cutoff is defined here; the claim is the ratio's predictive weight, not a threshold. | Reuses the INTERHEART citation already in the dataset. PRAJNA-APOBA1. |
hypothyroidism-screening-emphasis | TSH / hypothyroidism (screening emphasis) | 3016-3 | mIU/L | south_asian | any | 18 | null | reference_range | low=0.4; high=4.0; guidance=Reference range unchanged; the SA-relevant point is high hypothyroidism prevalence in Indian adults, supporting a lower threshold to check TSH. | low=0.4; high=4.0 | high | study-derived | null | Prevalence of hypothyroidism in adults: epidemiological study in eight cities of India (Unnikrishnan et al., Indian J Endocrinol Metab 2013) | https://doi.org/10.4103/2230-8210.113755 | DOI:10.4103/2230-8210.113755; PMID:23961480; PMCID:PMC3743364 | primaryStudy | false | Not a redefined range — a prevalence-driven screening emphasis; do not present a different TSH normal range for SA. | Unnikrishnan, Indian thyroid epidemiology. Soft/borderline candidate. TSH LOINC 3016-3. |
Open Masala — Ancestry-Adjusted Health Reference Ranges
The open, machine-readable, cited dataset of South Asian biomarker reference ranges and screening thresholds.
South Asians develop cardiovascular disease and type-2 diabetes earlier, at lower BMI, through different metabolic pathways. The screening thresholds that reflect this — WHO Asian BMI cutoffs, IDF waist limits, earlier diabetes and coronary-calcium screening, Lp(a) prompts — exist, but they're scattered across guideline PDFs and hundreds of papers. Nobody has ever assembled them into one structured, cited, downloadable table. This is that table.
⚠️ v0 / early release. A curation and synthesis of published guidelines and studies — not a primary-data release, and not yet clinician-reviewed for clinical use. Not a medical device or clinical advice. See Disclaimer.
- 🔗 Canonical repo: https://github.com/masalahealth/open-masala
- 🌐 About: https://masalahealth.co/open-masala/
What this is (and isn't)
- Is: a synthesis of published, citable thresholds into a machine-readable table — each row LOINC-coded, evidence-graded, provenance-tiered, and linked to its source.
- Isn't: raw cohort data. The studies these numbers come from (MASALA, GenomeAsia, UK Biobank) are access-controlled for good reasons; we don't re-host them. We encode the published thresholds they produced. This is a curation/synthesis contribution.
Dataset at a glance
- 41 rows (v0.1) spanning cardiometabolic (BMI, waist, HDL, triglycerides / atherogenic pattern, ApoB, ApoB/ApoA-I ratio, Lp(a), non-HDL, remnant cholesterol, hs-CRP, HbA1c, fasting insulin, SCORE2 SA multiplier, CAC screening + South-Asian CAC percentiles, 10-year risk, eGFR), plus women's health (GDM early screening, menopause, parity), pediatric (IAP BMI), hepatic (BMI-23 MASLD, normal-ALT caveat), nutrition (vitamin D, vitamin B12), hematology (thalassemia carrier screening, benign ethnic neutropenia), endocrine (hypothyroidism), and pharmacogenomics (SLCO1B1 statins).
- Each South Asian value is paired with its general-population counterpart, so the ancestry delta is visible in a single row.
- Provenance tiers: 18
guideline-endorsed· 19study-derived· 4contested-deprecated(do-not-apply showcases: eGFR race adjustment, APOL1, ALDH2/ADH1B, MTHFR-as-SA-variant). - Citation completeness: 100% — all 35 unique sources carry a resolvable identifier (DOI / PMID / PMCID / URL).
- ⚠️ 20 rows added in v0.1 are
review_status: proposed— pending clinician sign-off; full provenance + overclaim guards, not yet promoted toapproved.
Files
| Path | Format | For |
|---|---|---|
data/ancestry-reference-ranges.v0.csv |
CSV (powers the viewer above) | Tabular / ML use. |
data/ancestry-reference-ranges.v0.json |
JSON (canonical) | Full nested sources + overclaim guards. |
data/ancestry-reference-ranges.fhir.json |
FHIR R4 Bundle | Health systems — ObservationDefinition.qualifiedInterval per row. |
The provenance model (why you can trust a row)
Every row carries a provenance_tier — the single most important field:
| Tier | Meaning |
|---|---|
guideline-endorsed |
A named body recommends this exact cutoff for this population (WHO Asian BMI, IDF waist, ADA SA screening). Highest confidence. |
study-derived |
A real, cited effect estimate not yet codified into a guideline cutoff (e.g. the HbA1c under-read). Use with care; not settled practice. |
contested-deprecated |
An adjustment the field is moving away from (the eGFR race coefficient, retired 2021). Included precisely so you can tell you must not apply it. |
Every row also carries an overclaim_guard: the claim you must not make from it. If you're training or building on this data, honor those guards — they're designed to stop confidently-wrong ancestry statements.
Columns
| Column | Meaning |
|---|---|
id |
Stable row key. |
analyte |
Biomarker / measure name. |
loinc |
LOINC code (synthetic PRAJNA-* for computed metrics). |
unit |
Unit (UCUM-preferred). |
population |
south_asian or general — the stratification dimension. |
sex, age_min, age_max |
Strata the row applies to. |
measure_type |
reference_range / screening_threshold / screening_age / interpretation_caveat / risk_flag / deprecated_adjustment. |
sa_value, general_value |
The South Asian value and the general-population value it replaces. |
direction_of_risk |
Which way is concerning (high / low / n/a). |
provenance_tier, evidence_grade |
Credibility fields. |
source_labels, source_urls, source_refs, source_kinds |
Citations (pipe-separated where multiple). |
overclaim_guard |
The claim you must not make from the row. |
notes |
Anything else needed. |
Usage
from datasets import load_dataset
ds = load_dataset("masalahealthco/open-masala", split="reference_ranges")
row = next(r for r in ds if r["id"] == "bmi-diabetes-screening-threshold")
print(row["sa_value"], "vs general", row["general_value"])
# comparator=>=; value=23 vs general comparator=>=; value=25
The JSON (with nested sources) and the FHIR Bundle are in data/ for consumers that need the full structure.
Citation
See CITATION.cff. Please also cite the primary sources named in each row — the original authors did the underlying work. A DOI-minted release (Zenodo) is on the roadmap.
License
CC-BY-4.0 — use freely, with attribution and the per-row citations preserved.
Disclaimer
Open Masala is a reference dataset for research and product development. It is not a medical device, not clinical advice, and not a substitute for a clinician's judgment. Reference ranges vary by lab and method; screening decisions require individual clinical context. This is a v0 release and has not yet undergone clinical sign-off.
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