Abstract 19004: The Impact of Dual Antiplatelet Therapy on Mortality: A Patient-Level Meta-Analysis
Bibliographic record
Abstract
Background: Continuation of clopidogrel therapy beyond 12 months after percutaneous coronary intervention reduces the risk of stent thrombosis and major adverse cardiovascular (CV) and cerebrovascular events, yet was associated with increased non-cardiovascular mortality within the Dual Antiplatelet Therapy (DAPT) Study. Cancer-related, and not bleeding-related mortality accounted for the excess risk associated with continued clopidogrel use. We sought to determine the impact of continued clopidogrel use on mortality and to evaluate bleeding- and cancer-related mortality within a patient-level meta-analysis of randomized clinical trials. Methods: Meta-analytic clinical event rates for all-cause, CV, non-CV, cancer-related, and bleeding-related mortality, myocardial infarction (MI), stroke, fatal and major non-fatal bleeding were generated using patient-level data from 6 randomized trials comparing prolonged clopidogrel therapy to no or short-duration clopidogrel therapy on a background of aspirin. Results: Among 48,817 patients followed for a median of 546 days after randomization, dual-antiplatelet therapy (N=24411) or placebo (N=24406) resulted in comparable all-cause, CV, non-CV, cancer-related mortality (Table). While infrequent, fatal bleeding was more common with continued clopidogrel use, as was major non-fatal bleeding. Rates of ischemic events, including MI and stroke, were significantly lower in patients receiving continued clopidogrel therapy. Conclusions: Extended duration dual antiplatelet therapy with clopidogrel and aspirin does not impact mortality but does reduce rates of MI and stroke and increase rates of fatal and major non-fatal bleeding. These findings highlight the need for careful patient selection for extended duration treatment.
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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 | 0.019 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.060 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".