Vorapaxar in patients with coronary artery bypass grafting: Findings from the TRA 2°P-TIMI 50 trial
Bibliographic record
Abstract
BACKGROUND: Vorapaxar is a first-in-class protease-activated receptor-1 antagonist indicated for the reduction of cardiovascular death, myocardial infarction, and stroke in stable patients with prior atherothrombosis, who have not had a prior stroke or transient ischemic attack. The aims of this study were to investigate: 1) the role of vorapaxar in patients with severe coronary artery disease treated previously with coronary artery bypass grafting (CABG); and 2) safety in patients undergoing CABG while receiving vorapaxar. METHODS: TRA 2°P-TIMI 50 was a randomized, double-blinded, placebo-controlled trial of vorapaxar in 26,449 stable patients with prior atherothrombosis followed for a median of 30 months. We 1) investigated the efficacy of vorapaxar among patients with a history of CABG prior to randomization ( n=2942); and 2) assessed the safety among 367 patients who underwent a new CABG during the trial. RESULTS: Patients with a prior CABG were at higher risk for cardiovascular death, myocardial infarction, or stroke at three years compared with patients without a prior CABG (13.7% vs. 7.8%, p<0.001). Among patients with a prior CABG, vorapaxar significantly reduced the risk of cardiovascular death, myocardial infarction, or stroke (11.9% vs. 15.6%, hazard ratio 0.71, 95% confidence interval 0.58-0.88, p=0.001; number-needed-to-treat = 27). In patients undergoing CABG while receiving vorapaxar, the rate of Thrombolysis in Myocardial Infarction CABG major bleeding was 6.3% vs. 4.1% with placebo (hazard ratio 1.53, 95% confidence interval 0.58-4.01, p=0.39). CONCLUSIONS: In patients with a prior CABG, vorapaxar significantly reduced the risk of recurrent major cardiovascular events. In patients undergoing CABG while receiving vorapaxar, bleeding risk appeared similar to that seen in the overall trial population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| 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) | 0.000 | 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 teacher head, 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".