Association of Sex With Stroke and Bleeding Risk of Apixaban and Rivaroxaban in Elderly Atrial Fibrillation Patients Using Propensity Score Weights
Bibliographic record
Abstract
Background Evidence from clinical trials suggests a differential effect of sex on the effectiveness and safety of direct oral anticoagulants (DOACs) for stroke prophylaxis in atrial fibrillation (AF). Methods This population-based cohort study examined the independent effect of sex on hemorrhage and ischemic stroke in 23,884 patients (55% females; age ≥ 66 years) with AF starting apixaban or rivaroxaban treatment in Ontario, Canada. Patients were followed for 90 days after their DOAC prescription. Using female sex as the exposure of interest, differences in baseline characteristics were balanced between sexes using inverse probability weights based on propensity scores. Applying weighted modified Poisson regression, risk ratios (RRs) were estimated for major hemorrhage, ischemic stroke/systemic embolism/transient ischemic attack (hereafter stroke), myocardial infarction, and all-cause mortality, with males as a reference. Results Females were older, had higher predicted stroke risk (based on CHADS 2 score), and had fewer comorbidities than did males. Males had a higher prevalence of coronary artery disease, diabetes, and cancer, and similar predicted bleeding risk (based on HAS-BLED score). After weighting, baseline characteristics were well balanced. The 90-day risks for hemorrhage (RR 0.96; 95% confidence interval [CI] 0.80-1.15; P = 0.69) and stroke (RR 1.01; 95% CI 0.86-1.19; P = 0.94) were similar between sexes, which remained true when assessing each DOAC separately by dosing regimen. Compared to males, females had a lower risk for myocardial infarction (RR 0.66; 95% CI 0.52-0.84; P = 0.0008), and for all-cause mortality (RR 0.76; 95% CI 0.67-0.87; P < 0.0001). Conclusions Our findings do not suggest an association of sex with the 90-day risk of hemorrhage or ischemic stroke in older AF patients prescribed apixaban or rivaroxaban.
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".