Abstract 16133: Lipoprotein(a) Screening Practices in a Large US Healthcare Dataset
Bibliographic record
Abstract
Introduction/Background: Elevated Lipoprotein(a) [Lp(a)] is an independent, genetically determined, causal risk factor for atherosclerotic cardiovascular disease (ASCVD). European and Canadian guidelines recommend Lp(a) screening in all adults, while US guidelines recognize elevated Lp(a) as a risk enhancer. Research Hypothesis: Although elevated Lp(a) is an important ASCVD risk factor with a high prevalence, testing is infrequent. Aims: To characterize adults screened for Lp(a) and their clinicians using real-world data from the Family Heart Database of >324M US individuals with medical and/or lab data from 2012-2021. Methods: In this retrospective cohort study of > 44 million adults with lab data and medical claims one year before and after initial Lp(a) measurement, screening rates, demographics, ASCVD status, comorbidities, Lp(a) level (median; IQR) and ordering clinician are described. Results: Lp(a) screening rates were 1.1% (n=500,899 of 44,857,734) and 2.0% (n=218,331 of 10,658,820) in all and in those with ASCVD respectively. Among those with any Lp(a) test, median age was 60 (IQR 50-69) years, 55.0% were female,43.6%, 33.0%, 33.9%, and 13.9% had prior ASCVD, hypertension, hyperlipidemia and diabetes respectively. 20% had an Lp(a) level > 139 nmol/L. Lp(a) level was higher in females than males 36 (IQR 11-118) versus 28 (IQR 10-95) nmol/L, and in Blacks versus White and Hispanic populations 73 (IQR 24-170), 29 (IQR 10-102) and 28 (IQR 10-85) nmol/L. A small number of clinicians (n=687 of 41,976; 1.6%) ordered 50% of Lp(a) tests. Conclusions: Measurement of Lp(a) in US adults with and without ASCVD was rare but increased substantially after 2018. Individuals who had Lp(a) assessed were older and frequently had ASCVD and comorbidities. A small number of clinicians were responsible for most Lp(a) orders. Additional research into barriers and facilitators of Lp(a) screening is needed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".