Lipoprotein(a) and cardiovascular disease: Evidence, recommendations and emerging therapies
Bibliographic record
Abstract
Lipoprotein(a) (Lp[a]) is a low-density lipoprotein (LDL) like particle which has atherogenic, proinflammatory and prothrombotic properties. Elevated in approximately 1 in 5 persons, increased levels of Lp(a) have been shown by epidemiological, genome wide association studies and Mendelian randomisation studies to be a causal factor for atherosclerotic cardiovascular disease (ASCVD). Lp(a) is primary genetically determined and is more atherogenic than LDL. Current recommendations from Europe, Canada, India and the United States recommend testing at least once in all adults. Persons found to have elevated levels (eg, > 50 mg/dL or > 125 nmol/L) are recommended for more intensive risk factor management, including further LDL-C lowering. With lipoprotein apheresis the only currently approved therapy for lowering Lp(a), several newer antisense oligonucleotide (ASO) and small interfering RNA (siRNA) therapies are in development and may soon provide additional therapeutic options for persons with elevated Lp(a). Several cardiovascular outcomes trials are underway involving these new therapies with the first to read out in 2026. Lp(a) is a key risk factor that warrants greater attention for testing, with further efforts to reduce ASCVD in those found to have elevated levels, especially in higher risk persons.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".