Dual Antiplatelet Therapy and Outcomes in Patients With Atrial Fibrillation and Acute Coronary Syndromes Managed Medically Without Revascularization: Insights From the <scp>TRILOGY ACS</scp> Trial
Bibliographic record
Abstract
Associations between atrial fibrillation (AF), outcomes, and response to antiplatelet therapies in patients with acute coronary syndrome (ACS) managed medically without revascularization remain uncertain. We examined these associations for medically managed ACS patients randomized to dual antiplatelet therapy (DAPT) using patient data from the TRILOGY ACS trial. DAPT included aspirin plus clopidogrel 75 mg/d or prasugrel 10 mg/d (5 mg/d for those <60 kg or age ≥75 years). Patients receiving oral anticoagulants were excluded. Cox proportional hazards regression modeling was used to characterize associations between patients with AF (AF+) vs those without (AF-) and risk of ischemic and bleeding events, and to explore effects of randomized treatment on outcomes. Among 9101 patients with baseline AF status, 710 (7.8%) had AF. AF+ patients were older and had more comorbidities. Unadjusted associations of the composite of cardiovascular death/myocardial infarction/stroke were significantly higher among AF patients at 30 months (31.1% vs 18.4%; HR: 1.61, 95% CI: 1.35-1.92, P < 0.001), but differences did not persist after adjustment (HR: 1.16, 95% CI: 0.97-1.39, P = 0.11). When individual components of the composite endpoint were evaluated, 30-month risk of events in AF+ patients was significantly higher. Thirty-month risk of all-cause death was significantly higher in AF+ patients: 18.1% vs 11.1% (HR: 1.62, 95% CI: 1.30-2.02, P < 0.001). There was no significant interaction with randomized treatment and AF for the primary endpoint. Among medically managed high-risk ACS patients receiving DAPT, AF was associated with higher unadjusted risks of ischemic and bleeding outcomes that were similar by treatment group.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".