An Updated Meta-Analysis of RCTs of Colchicine for Stroke Prevention in Patients with Coronary Artery Disease
Bibliographic record
Abstract
Emerging evidence from randomized controlled clinical trials (RCTs) suggests that colchicine has cardiovascular benefits for patients with coronary disease, including benefits for stroke prevention. We performed an updated systematic review and meta-analysis of all RCTs reporting on stroke outcomes during the follow-up of patients with a history of cardiovascular disease randomized to colchicine treatment or control (placebo or usual care). We identified 6 RCTs including a total of 11,870 patients (mean age 63 years, 83% males) with a mean follow-up of 2 years. Colchicine treatment was associated with a lower risk of stroke during follow-up, compared to that of placebo or usual care (risk ratio = 0.49, 95% confidence interval: 0.31–0.80; p = 0.004), without heterogeneity across the included studies (I2 = 0%, p for Cochran’s Q = 0.52). In the subgroup analysis, no heterogeneity (p = 0.77) was identified in the effect of colchicine on stroke prevention between patients with recent acute (RR = 0.55, 95% CI: 0.15–2.05) or chronic stable (RR = 0.43, 95% CI: 0.21–0.89) coronary artery syndromes. In conclusion, we found that colchicine treatment decreases the stroke risk in patients with a history of atherosclerotic cardiovascular disease.
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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 | 0.022 | 0.067 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.043 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".