Effectiveness and Safety of Edoxaban Compared With Apixaban in Elderly Patients With Nonvalvular Atrial Fibrillation: A Real-World Population-Based Cohort Study
Bibliographic record
Abstract
BACKGROUND: The very elderly (≥80 years) are at high risk of nonvalvular atrial fibrillation and thromboembolism. Given its recent approval, the comparative effectiveness and safety of edoxaban in this population, relative to the commonly used apixaban, remain unknown. METHODS: Using the United Kingdom Clinical Practice Research Datalink, we identified a cohort of patients aged ≥80 with incident nonvalvular atrial fibrillation and newly treated with edoxaban or apixaban between 2015 and 2021. Cohort entry was defined as the first prescription for one of the 2 drugs. We used propensity score fine stratification and weighting for confounding adjustment. A weighted Cox proportional hazards model was used to estimate the hazard ratios (HR) with 95% CI of ischemic stroke/transient ischemic attack/systemic embolism (primary effectiveness outcome) and of major bleeding (primary safety outcome) associated with edoxaban compared with apixaban. We also assessed the risk of all-cause mortality and a composite outcome of ischemic stroke/transient ischemic attack, systemic embolism, gastrointestinal bleeding, and intracranial hemorrhage as secondary outcomes. RESULTS: The cohort included 7251 new-users of edoxaban and 39 991 of apixaban. Edoxaban and apixaban had similar incidence rates of thromboembolism (adjusted rates, 20.38 versus 19.22 per 1000 person-years; adjusted HR, 1.06 [95% CI, 0.89-1.26]), although the rates of major bleeding were higher with edoxaban (adjusted rates, 45.57 versus 31.21 per 1000 person-years; adjusted HR, 1.42 [95% CI, 1.26-1.61]). The risk of the composite outcome was 21% higher with edoxaban (adjusted HR, 1.21 [95% CI, 1.07-1.38]). All-cause mortality was similar between edoxaban and apixaban (adjusted HR, 1.04 [95% CI, 0.96-1.12]). CONCLUSIONS: In very elderly patients with nonvalvular atrial fibrillation, edoxaban resulted in similar thromboembolism prevention as apixaban, although it was associated with a higher risk of major bleeding. These findings may improve the management of nonvalvular atrial fibrillation by informing physicians on the choice of anticoagulant for this vulnerable population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".