Vorapaxar, a platelet thrombin-receptor antagonist, in medically managed patients with non-ST-segment elevation acute coronary syndrome: results from the TRACER trial
Bibliographic record
Abstract
BACKGROUND: This study characterized a medically managed population in a non-ST-segment elevation acute coronary syndrome (NSTEACS) cohort and evaluated prognosis and outcomes of vorapaxar vs. placebo. METHODS: In the TRACER study, 12,944 NSTEACS patients were treated with standard care and vorapaxar (a novel platelet protease-activated receptor-1 antagonist) or placebo. Of those, 4194 patients (32.4%) did not undergo revascularization during index hospitalization, and 8750 (67.6%) underwent percutaneous coronary intervention or coronary artery bypass grafting. Patients managed medically were heterogeneous with different risk profiles, including 1137 (27.1%) who did not undergo coronary angiography. Patients who underwent angiography but were selected for medical management included those without evidence of significant coronary artery disease (CAD), with prior CAD but no new significant lesions, and with significant lesions who were not treated with revascularization. RESULTS: Cardiovascular event rates were highest among those without angiography and lowest in the group with angiography but without CAD. In the medically managed cohort, 2-year primary outcome (cardiovascular death, myocardial infarction, stroke, recurrent ischaemia with rehospitalization, urgent coronary revascularization) event rates were 16.3% with vorapaxar and 17.0% with placebo (HR 0.99, 95% CI 0.83-1.17), with no interaction between drug and management strategy (p=0.75). Key secondary endpoint (cardiovascular death, myocardial infarction, stroke) rates were 13.4% with vorapaxar and 14.9% with placebo (HR 0.89, 95% CI 0.74-1.07), with no interaction (p=0.58). Vorapaxar increased GUSTO moderate/severe bleeding numerically in medically managed patients (adjusted HR 1.46, 95% CI 0.99-2.15). CONCLUSIONS: NSTEACS patients who were initially medically managed had a higher risk-factor burden, and one-third had normal coronary arteries. Outcome in the medically managed cohort was significantly related to degree of CAD, highlighting the importance of coronary angiography. Efficacy and safety of vorapaxar appeared consistent with the overall trial results.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".