Therapy of unstable angina with the low molecular weight heparins
Bibliographic record
Abstract
Unstable angina is in most cases caused by partial or complete coronary artery occlusion due to the disruption of an atherosclerotic plaque and to thrombus formation. An immediate antithrombotic approach is essential to prevent fatal and non-fatal myocardial infarction, and the combination of aspirin and unfractionated heparin has played a pivotal role in the past years. Low molecular weight heparins have improved pharmacokinetic and pharmacodynamic properties over unfractionated heparin that have resulted in greater efficacy and safety in the field of venous thromboembolism. Low molecular weight heparins can be administered by once or twice daily subcutaneous injections at fixed, weight-adjusted doses without the need for monitoring. Because of their potential, many recent clinical trials have evaluated their efficacy and safety in the management of patients with unstable angina. Three low molecular weight heparins have so far been tested: nadroparin, dalteparin and enoxaparin. The results of the published trials confirm that the newer compounds are at least as safe and effective as unfractionated heparin, and offer considerable therapeutic advantages. Nevertheless, the different properties of the three compounds and perhaps the different designs of the clinical trials have led to not entirely comparable findings.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".