Oral Anticoagulation for the Prevention of Thromboembolic Events in Patients With Anterior ST-Segment Elevation Myocardial Infarction
Bibliographic record
Abstract
OBJECTIVES: The objective is to assess the comparative effectiveness and safety of dual-antiplatelet therapy (DAPT) vs triple therapy (TT) with DAPT + oral anticoagulant (OAC) in patients with anterior ST-segment elevation myocardial infarction (STEMI) and with new-onset anterior/apical wall-motion abnormalities (WMAs) treated with primary percutaneous coronary intervention (PCI). BACKGROUND: Patients with STEMI and new-onset anterior/apical WMA may benefit from the addition of OAC to prevent left ventricular thrombus and cardioembolic events. METHODS: A multicenter, retrospective cohort study was conducted. Patients with a concomitant indication for OAC were excluded. Patients discharged on TT were compared with patients discharged on DAPT using adjusted Cox proportional hazards analysis and inverse probability of treatment weighting. The primary endpoint was the net adverse clinical event (NACE) rate at 6 months (composite of all-cause mortality, non-fatal MI, stroke, or transient ischemic attack, systemic thromboembolism or type 3 or 5 Bleeding Academic Research Consortium [BARC] bleeding). RESULTS: A total of 1666 patients were included, among which 627 were treated with TT and 1039 were treated with DAPT. A NACE occurred in 55 patients (6.03 per 100 patient-years) in the TT group and in 74 patients (7.18 per 100 patient-years) in the DAPT group (adjusted hazard ratio, 0.86; 95% confidence interval, 0.55-1.32). Adjusted risk of the individual components of the primary endpoint, ischemic events, and bleeding events were similar between both groups (P>.05 for all). CONCLUSIONS: The addition of OAC to DAPT in anterior STEMI patients with new-onset WMA treated with PCI was not associated with a significant reduction in NACE.
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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 | 0.005 |
| 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 | 0.000 | 0.000 |
| 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".