Abstract WMP104: Effect Of Addition Of Clopidogrel To Aspirin On Stroke Incidence: Meta-analysis Of Randomized Trials
Bibliographic record
Abstract
Introduction: Current guidelines do not support the use of aspirin and clopidogrel for secondary stroke prevention due to a nonsignificant reduction in stroke and a significant increase in life-threatening bleeding. Hypothesis: We assessed the hypothesis that the effect of dual antiplatelet therapy on stroke prevention would be different depending on the trial cohort. Methods: We conducted a meta-analysis of published randomized trials comparing the combination of clopidogrel and aspirin versus aspirin alone that reported stroke incidence. Statistical heterogeneity across trials was evaluated using the I2 index and the Chi-square test for heterogeneity. Results: Thirteen randomized trials were included with a total of 90,433 participants (mean age 63 years; 63% male) with a mean follow up of 1.0 years and 2011 strokes. Stroke was reduced 19% by dual antiplatelet therapy (OR=0.81; 95% CI 0.74-0.89) with no evidence of heterogeneity of effect across different trial populations (I2 index = 5%, p = 0.4 for heterogeneity). Dual antiplatelet therapy reduced ischemic stroke by 23% (OR=0.77; 95% CI 0.70-0.85). The risk of major bleeding was increased by 40% (OR 1.40, 95% CI 1.26-1.55) by dual antiplatelet therapy; there was a nonsignificant 2% increase in intracerebral hemorrhage (OR=1.12, 95% CI 0.86-1.46). Conclusions: Contrary to our hypothesis, this meta-analysis demonstrates a substantial relative risk reduction in stroke by clopidogrel plus aspirin vs. aspirin alone that is consistent across different trial cohorts. Given this findings the strong proscription against the use of clopidogrel plus aspirin for secondary stroke prevention advocated by most current guidelines may warrant reconsideration.
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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 | 0.045 | 0.118 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.061 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".