Efficacy and safety of unfractionated heparin versus enoxaparin: a pooled analysis of ASSENT-3 and -3 PLUS data
Bibliographic record
Abstract
BACKGROUND: The optimal antithrombotic therapy to accompany tenecteplase in cases of acute ST-segment elevation myocardial infarction (STEMI) remains unclear. We undertook a prespecified pooled analysis of data from the ASSENT-3 and ASSENT-3 PLUS trials. METHODS: We created a combined database of the 2040 and 818 patients who received enoxaparin in ASSENT-3 and ASSENT-3 PLUS, respectively, and compared them with the 2038 and 821 patients who received unfractionated heparin. RESULTS: The efficacy end point (a composite of 30-day mortality, reinfarction or refractory ischemia) was 12.2% with enoxaparin versus 16.0% with unfractionated heparin (p < 0.001); the combined end point of efficacy plus safety (a composite of 30-day mortality, reinfarction, refractory ischemia, intracranial hemorrhage [ICH] or major systemic bleeding) was 15.0% versus 18.0%, respectively (p = 0.003) [corrected] The 1049 patients urgently revascularized had greater benefit from enoxaparin (15.4% v. 10.1%, p = 0.013), yet the excess in major systemic bleeding evident with enoxaparin (3.3% v. 2.4%, p = 0.01) was largely confined to the 3492 patients without or before revascularization. Although ICH rates in the groups were similar (1.3% v. 0.9%, p = 0.26), an excess of ICH occurred among those administered enoxaparin during the ASSENT-3 PLUS trial (6.7% v. 0.8%, p = 0.013), especially among women over 75 years of age. INTERPRETATION: These data demonstrated the benefit of enoxaparin used in conjunction with tenecteplase, but raised caution about its prehospital use to treat STEMI in elderly women.
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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 | 0.020 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.018 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".