Statin Use and Sex-Specific Stroke Outcomes in Patients With Vascular Disease
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although statins reduce the risk of stroke in patients with coronary heart disease, possible differing effects of statins on stroke outcomes based on sex remain uncertain. We investigated the relationships between statin use and sex-specific stroke incidence, severity, and mortality. METHODS: Data from 3 trials of oral glycoprotein IIb/IIIa inhibitors (first and second Sibrafiban versus aspirin to Yield Maximum Protection from ischemic Heart events postacute cOroNary sYndromes [SYMPHONY] and Blockade of the glycoprotein IIb/IIIa Receptor to Avoid Vascular Occlusion [BRAVO]) were pooled and stroke outcomes compared among 8191 baseline statin users versus 14,752 nonusers. Time-to-event data were modeled with proportional hazards regression. Stroke severity was assessed retrospectively with the Canadian Neurological Scale (CNS) based on records with scoreable neurological examinations. RESULTS: A total of 217 subjects had strokes (0.95%). Statin users had a lower risk of stroke in unadjusted (hazard ratio [HR], 0.69; 95% CI, 0.51 to 0.92) and risk-adjusted models (HR, 0.72; 95% CI, 0.53 to 0.97). There was no difference in stroke mortality with statin use (P=0.8). CNS scores could be assigned to 106 of the subjects, with no difference in severity among statin users and nonusers (median CNS=10.5 in users versus CNS=9.75 in nonusers; P=0.14). Women had more severe strokes than men (median CNS=10.5 in men versus 9.5 in women; Poisson regression P=0.035). Women had more severe strokes after adjustment for statin use (P=0.03) and the combination of statin use, atrial fibrillation, and age (P=0.03). CONCLUSIONS: In patients included in these clinical trials of oral glycoprotein IIb/IIIa inhibitors, statin use is associated with a reduced risk of stroke but not severity or mortality. Women had more severe strokes than men, a difference that was not explained by baseline characteristics or statin use.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".