Rationale for the routine screening of Lipoprotein(a) in cardiovascular risk assessment
Bibliographic record
Abstract
Lipoprotein(a) [Lp(a)] is a lipid particle identified by Mendelian randomization studies to be causally associated with the development of atherosclerotic cardiovascular disease and aortic stenosis, across ethnicities. The risk of cardiovascular disease with markedly elevated Lp(a) is equal to that of untreated familial hypercholesterolemia, and yet, up until now, there has been hesitancy in measuring Lp(a) as a routine part of cardiovascular risk assessment. Screening of Lp(a) level in all individuals is now recommended in the European and Canadian Lipid Guidelines and by the National Lipid Association. This review assesses how well measurement of Lp(a) meets accepted criteria for population screening of an analyte, based on established principles used for the selection of a new candidate for inclusion in screening programs. Lp(a) meets the majority of recommended principles for a routine population screening test, based on health, societal, and cost considerations. Incorporating Lp(a) into global assessment and management of cardiovascular risk will result in savings to health care systems, reinforce recommendations from growing numbers of clinical guidelines and consensus statements, and increase implementation of proactive preventive medicine.
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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 | 0.048 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.008 | 0.014 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".