Effect of Addition of Clopidogrel to Aspirin on Stroke Incidence: Meta-Analysis of Randomized Trials
Bibliographic record
Abstract
BACKGROUND: It remains controversial whether dual antiplatelet therapy reduces stroke more than aspirin alone. AIM: We aimed to assess the effects of adding clopidogrel to aspirin on the occurrence of stroke and major haemorrhage in patients with vascular disease. METHODS: Meta-analysis of published randomized trials comparing the combination of clopidogrel and aspirin vs. aspirin alone that reported stroke and major bleeding. 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 (odds ratio = 0·81, 95% confidence interval 0·74-0·89) with no evidence of heterogeneity of effect across different trial populations (I(2) index = 5%, P = 0·4 for heterogeneity). Dual antiplatelet therapy reduced ischemic stroke by 23% (odds ratio = 0·77; 95% confidence interval 0·70-0·85); there was a nonsignificant 12% increase in intracerebral haemorrhage (odds ratio = 1·12, 95% confidence interval 0·86-1·46). Among 1930 participants with recent (<30 days) brain ischemia from four trials, stroke was reduced by 33% (odds ratio = 0·67, 95% confidence interval 0·46-0·97) by dual antiplatelet therapy vs. aspirin alone. The risk of major bleeding was increased by 40% (odds ratio = 1·40, 95% confidence interval 1·26-1·55) by dual antiplatelet therapy. CONCLUSIONS: 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. Major haemorrhage is increased by dual antiplatelet therapy.
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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 | 0.030 | 0.066 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.059 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".