Low-Molecular-Weight Heparins in the Treatment of Acute Coronary Syndromes
Bibliographic record
Abstract
Platelet aggregation and activation of coagulation are key events in the development of acute coronary syndromes. Patients with an acute coronary syndrome are at high risk of death or myocardial infarction, and hence there is a strong rationale for the use of antithrombotic agents. Heparin has been shown to reduce the risk of death or myocardial infarction in aspirin-treated patients with acute coronary syndromes, but it has a number of limitations, including the need for regular monitoring and the risk of hemorrhage and thrombocytopenia. Low-molecular-weight heparins offer a number of practical and clinical advantages over unfractionated heparin, such as higher bioavailability and administration by subcutaneous injection. Several low-molecular-weight heparins are available that differ in their biochemical and pharmacologic properties, and it is not possible to predict their clinical efficacy from their pharmacologic profile. The decision regarding the use of a specific low-molecular-weight heparin should be based on the efficacy and safety data available for each product. In clinical trials comparing low-molecular-weight heparin with heparin, only enoxaparin sodium has been shown to reduce the risk of coronary events in patients with non-ST segment elevation acute coronary ischemia.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".