Net Clinical Benefit of Adding Clopidogrel to Aspirin Therapy in Patients With Atrial Fibrillation for Whom Vitamin K Antagonists Are Unsuitable
Bibliographic record
Abstract
BACKGROUND: Adding clopidogrel to aspirin therapy reduces stroke in patients with atrial fibrillation (AF) but increases hemorrhage. OBJECTIVE: To quantify the net benefit of adding clopidogrel to aspirin therapy, accounting for differences in clinical significance between ischemic and hemorrhagic events. DESIGN: Observational cohort study to assign the relative weighting of events and post hoc analysis of randomized trial data to assess net benefit of dual antiplatelet therapy in the ACTIVE (Atrial Fibrillation Clopidogrel Trial with Irbesartan for Prevention of Vascular Events) clinical trials. SETTING: Global randomized clinical trial. PATIENTS: 10,041 patients with AF, 7554 of whom were not candidates for warfarin therapy. MEASUREMENTS: Ischemic events (ischemic stroke or myocardial infarction) and hemorrhagic events (hemorrhagic stroke or subdural or extracranial bleeding), weighted by the hazard ratio for death (or death or disability) after an event relative to death (or death or disability) after ischemic stroke. The net clinical benefit of dual antiplatelet therapy in the ACTIVE A trial participants was defined as the sum of weighted event incidence with dual antiplatelet therapy subtracted from the sum of weighted event incidence on control treatment, expressed as ischemic stroke equivalents prevented per 100 patients years. RESULTS: Adding clopidogrel to aspirin therapy prevented 0.57 ischemic stroke equivalent (95% CI, -0.12 to 1.24) per 100 patient-years of treatment when weighted by hazard for death after ischemia or hemorrhage and 0.67 ischemic stroke equivalent (CI, -0.03 to 1.18) when weighted by death or disability after ischemia or hemorrhage. LIMITATION: No attempt was made to relate deaths used for weighting to events; disability data were missing for more than one half of patients. CONCLUSION: Adding clopidogrel to aspirin therapy resulted in a modest net benefit among patients with AF for whom warfarin was unsuitable. The benefit would probably be clinically relevant for some patients, but estimates could not exclude the possibility of either no benefit or very small harm in this population. PRIMARY FUNDING SOURCE: Bristol-Myers Squibb and sanofi-aventis.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".