Lipoprotein(a): what clinicians need to know
Bibliographic record
Abstract
Lipoprotein(a) [Lp(a)] is a plasma particle structurally similar to LDL, distinguished by the presence of apolipoprotein(a), and has evolved from plasminogen. Lp(a) concentration is 90% genetically determined and largely stable throughout life. Black individuals exhibit the highest Lp(a) levels, followed by South Asians, Whites, Hispanics, and East Asians, with a 2- to 4-fold median difference across ancestral groups. Approximately 1.5 billion people worldwide (~20% of the population) have elevated Lp(a) levels (>125 nmol/L or >50 mg/dL). Notably, women experience 17% higher levels than men post-menopause. Mendelian randomization studies have established Lp(a) as a strong cardiovascular disease (CVD) risk factor, implicated in coronary artery disease, peripheral artery disease (PAD), ischemic stroke, heart failure, and aortic stenosis. Risk increases linearly with Lp(a) levels, with concentrations >90 mg/dL (>190 nmol/L) associated with a 1.6-fold higher risk of ischemic stroke, 1.7-fold for heart failure, 2-fold for PAD, and 3-fold for aortic stenosis and myocardial infarction. Lp(a) levels between 130–391 mg/dL (280–849 nmol/L) confer atherosclerotic CVD risk equivalent to familial hypercholesterolemia. Universal screening of once Lp(a) test is now recommended for all adults in guidelines across the US, Europe and Canada. However, Lp(a) testing is severely underutilized with studies showing 0.3% testing frequency amongst 5.5 million US patients. Even in high-risk patients with established ASCVD, only 13.9% are tested for Lp(a). Existing treatment options for elevated Lp(a) include proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and lipoprotein apheresis. Emerging therapies include antisense oligonucleotides such as pelacarsen, small-interfering RNA such as zerlasiran, olpasiran, and lepodisiran, and oral agents such as muvalaplin. These medications have shown a significant reduction in plasma levels up to 80% (pelacarsen), 96.9% (olpasiran), 97% (lepodisiran) and 99% (zerlasiran) in phase 1 and 2 trials, with larger studies ongoing to assess cardiovascular outcomes. With advancing therapies, clinician awareness, early detection, and risk management of Lp(a) are critical to improving outcomes.
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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 | 0.004 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.013 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.012 | 0.014 |
| Insufficient payload (model declined to judge) | 0.031 | 0.023 |
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".