Lipoprotein (a): truly a direct prothrombotic factor in cardiovascular disease?
Bibliographic record
Abstract
Elevated plasma concentrations of lipoprotein (a) [Lp(a)] have been determined to be a causal risk factor for coronary heart disease, and may similarly play a role in other atherothrombotic disorders. Lp(a) consists of a lipoprotein moiety indistinguishable from LDL, as well as the plasminogen-related glycoprotein, apo(a). Therefore, the pathogenic role for Lp(a) has traditionally been considered to reflect a dual function of its similarity to LDL, causing atherosclerosis, and its similarity to plasminogen, causing thrombosis through inhibition of fibrinolysis. This postulate remains highly speculative, however, because it has been difficult to separate the prothrombotic/antifibrinolytic functions of Lp(a) from its proatherosclerotic functions. This review surveys the current landscape surrounding these issues: the biochemical basis for procoagulant and antifibrinolytic effects of Lp(a) is summarized and the evidence addressing the role of Lp(a) in both arterial and venous thrombosis is discussed. While elevated Lp(a) appears to be primarily predisposing to thrombotic events in the arterial tree, the fact that most of these are precipitated by underlying atherosclerosis continues to confound our understanding of the true pathogenic roles of Lp(a) and, therefore, the most appropriate therapeutic target through which to mitigate the harmful effects of this lipoprotein.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".