Effectiveness and safety of rivaroxaban vs. apixaban in patients with atrial fibrillation and peripheral artery disease
Bibliographic record
Abstract
AIMS: To assess whether rivaroxaban is associated with a decreased risk of major adverse limb events (MALE), stroke, systemic embolism (SE), and major bleeding (MB) among patients with non-valvular atrial fibrillation (NVAF) and peripheral artery disease (PAD), compared with apixaban. METHODS AND RESULTS: We conducted a population-based cohort study using the UK Clinical Practice Research Datalink. Patients aged ≥45 years with incident NVAF and PAD who initiated rivaroxaban or apixaban between 2013 and 2021 were included. Primary effectiveness outcomes were MALE, and a composite of ischaemic stroke, transient ischaemic attack (TIA), or SE. The primary safety outcome was MB. The risk of major cardiovascular events (MACE) was assessed as a secondary outcome. Confounding was addressed using propensity score fine stratification and weighting. Weighted Cox proportional hazards models estimated hazard ratios (HRs) with 95% confidence intervals (CIs). The cohort included 6170 new users of rivaroxaban and 9990 new users of apixaban (44% female; mean [SD] age 78.5 [9.2] years). Incidence rates were similar for MALE (6.7 vs. 5.6/1000 person-years; adjusted HR (aHR): 1.20; 95% CI 0.87-1.65), stroke/TIA/SE (24.5 vs. 21.3/1000 person-years; aHR: 1.15; 95% CI 0.97-1.36), and MACE (40.1 vs. 35.9 per 1000 person-years; aHR 1.10: 95% CI 0.94-1.28). Major bleeding rates were higher with rivaroxaban (46.1 vs. 29.8/1000 person-years; aHR: 1.55; 95% CI 1.36-1.77). CONCLUSION: In patients with NVAF and PAD, rivaroxaban was associated with a similar risk of MALE and stroke/TIA/SE, but a higher risk of MB compared with apixaban. These findings support apixaban as a potentially safer anticoagulant in this high-risk population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".