Bivalirudin for Primary Percutaneous Coronary Interventions
Bibliographic record
Abstract
BACKGROUND: Data from randomized trials has demonstrated the superiority of bivalirudin to glycoprotein IIb/IIIa inhibitors plus heparin in patients undergoing primary percutaneous coronary intervention. Real-world performance of bivalirudin in primary percutaneous coronary intervention and the benefit of bivalirudin over heparin remain unknown in an era of routine dual antiplatelet therapy. METHODS AND RESULTS: From July 2004 to December 2010, 2317 consecutive patients were indexed in the University of Ottawa Heart Institute ST-segment-elevation myocardial infarction registry. During this period 748 patients received bivalirudin, 699 patients received glycoprotein IIb/IIIa inhibitors, and 676 patients received unfractionated heparin alone. The primary outcome was the rate of noncoronary artery bypass graft related thrombolysis in myocardial infarction major bleeding. Bivalirudin significantly reduced the primary outcome compared with heparin plus glycoprotein IIb/IIIa inhibitors (2.7% versus 7.3%, adjusted OR 2.96, 95% CI: 1.61-5.45, P<0.001) and the composite end point of death, stroke, reinfarction and major bleed (OR 1.66, 95% CI: 1.12-2.45, P=0.01). Compared with heparin alone, a reduction in major bleeds (OR 1.21, 95% CI: 0.60-2.44, P=0.59) or the composite end point (1.05, 95% CI: 0.68-1.63, P=0.83) with bivalirudin could not be demonstrated. Notably, major bleeding was associated with a 5-fold increase in the risk of mortality both in-hospital (3.5% versus 20.6%) and out to 180 days (5.6% versus 25.8%). CONCLUSIONS: Bivalirudin use compared with glycoprotein IIb/IIIa inhibitors plus heparin as an antithrombotic strategy in primary percutaneous coronary intervention results in less major bleeding in contemporary practice. A benefit of bivalirudin over heparin could not be established with this registry and requires additional investigations to either confirm or refute.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".