Validity of Composite Outcomes in Meta-Analyses of Stroke Prevention Trials: The Case of Aspirin
Bibliographic record
Abstract
BACKGROUND: Aspirin has been reported to be less effective for secondary vascular prevention in patients with ischaemic stroke, compared with other high-risk populations. This contention is largely based on results of meta-analyses that used a composite outcome of vascular death, myocardial infarction and stroke, reporting a 13% relative risk reduction. In this study, we explore whether the summary relative risk reduction for this composite outcome is representative of estimates for each of the individual components of the composite. STUDY SELECTION: All randomised controlled trials comparing aspirin with placebo/control in patients following ischaemic stroke or transient ischaemic attack, beyond the acute period (2 weeks). DATA ANALYSIS: A fixed-effects model was used and summary risk ratios were calculated for each of the outcomes: vascular mortality, recurrent non-fatal stroke, non-fatal myocardial infarction, composite of the latter three outcomes, all-cause mortality and non-vascular mortality. RESULTS: Ten trials (n = 9,168) were included. For the composite of non-fatal stroke, non-fatal myocardial infarction and vascular death, aspirin was associated with a 13% reduction in risk (risk ratio, RR: 0.87; 95% CI: 0.81-0.94). For individual components of the composite, aspirin reduced the risk of non-fatal ischaemic stroke (RR: 0.81; 95% CI: 0.72-0.90) and non-fatal myocardial infarction (RR: 0.68; 95% CI: 0.52-0.87), but not vascular death (RR: 0.97; 95% CI: 0.86-1.1). Aspirin did reduce the risk of non-vascular death (RR: 0.79; 95% CI: 0.66-0.95), though, and had a trend towards a reduced risk of all-cause mortality (RR: 0.91; 95% CI: 0.81-1.01). CONCLUSIONS: Following ischaemic stroke, aspirin does not reduce the risk of vascular death, but provides a significant reduction in non-fatal stroke, myocardial infarction and non-vascular death. Our findings would support presenting the effect of aspirin therapy on individual outcomes rather than a composite including vascular death.
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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 | 0.660 | 0.854 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.021 | 0.042 |
| Bibliometrics | 0.011 | 0.015 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.010 | 0.008 |
| Research integrity | 0.010 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".