Randomized Comparison of Enoxaparin, a Low-Molecular-Weight Heparin, With Unfractionated Heparin Adjunctive to Recombinant Tissue Plasminogen Activator Thrombolysis and Aspirin
Bibliographic record
Abstract
BACKGROUND: Adjunctive unfractionated heparin (UFH) during thrombolytic therapy for acute myocardial infarction (AMI) promotes the speed and magnitude of coronary artery recanalization and reduces reocclusion. Low-molecular-weight heparins offer practical and potential pharmacological advantages over UFH in multiple applications but have not been systematically studied as adjuncts to fibrinolysis in AMI. METHODS AND RESULTS: Four hundred patients undergoing reperfusion therapy with an accelerated recombinant tissue plasminogen activator regimen and aspirin for AMI were randomly assigned to receive adjunctive therapy for at least 3 days with either enoxaparin or UFH. The study was designed to show noninferiority of enoxaparin versus UFH with regard to infarct-related artery patency. Ninety minutes after starting therapy, patency rates (thrombolysis in myocardial infarction [TIMI] flow grade 2 or 3) were 80.1% and 75.1% in the enoxaparin and UFH groups, respectively. Reocclusion at 5 to 7 days from TIMI grade 2 or 3 to TIMI 0 or 1 flow and TIMI grade 3 to TIMI 0 or 1 flow, respectively, occurred in 5.9% and 3.1% of the enoxaparin group versus 9.8% and 9.1% in the UFH group. Adverse events occurred with similar frequency in both treatment groups. CONCLUSIONS: Enoxaparin was at least as effective as UFH as an adjunct to thrombolysis, with a trend toward higher recanalization rates and less reocclusion at 5 to 7 days.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".