Outcomes of apixaban vs. warfarin by type and duration of atrial fibrillation: results from the ARISTOTLE trial
Bibliographic record
Abstract
AIMS: It is uncertain whether the benefit from apixaban varies by type and duration of atrial fibrillation (AF). METHODS AND RESULTS: A total of 18 201 patients with AF [2786 (15.3%) with paroxysmal and 15 412 (84.7%) with persistent or permanent] were randomized to apixaban or warfarin. In this pre-specified secondary analysis, we compared outcomes and treatment effect of apixaban vs. warfarin by AF type and duration. The primary efficacy endpoint was a composite of ischaemic or haemorrhagic stroke or systemic embolism. The secondary efficacy endpoint was all-cause mortality. There was a consistent reduction in stroke or systemic embolism (P for interaction = 0.71), all-cause mortality (P for interaction = 0.75), and major bleeding (P for interaction = 0.50) with apixaban compared with warfarin for both AF types. Apixaban was superior to warfarin in all studied endpoints, regardless of AF duration at study entry (P for all interactions >0.13). The rate of stroke or systemic embolism was significantly higher in patients with persistent or permanent AF than patients with paroxysmal AF (1.52 vs. 0.98%; P = 0.003, adjusted P = 0.015). There was also a trend towards higher mortality in patients with persistent or permanent AF (3.90 vs. 2.81%; P = 0.0002, adjusted P = 0.066). CONCLUSION: The risks of stroke, mortality, and major bleeding were lower with apixaban than warfarin regardless of AF type and duration. Although the risk of stroke or systemic embolism was lower in paroxysmal than persistent or permanent AF, apixaban is an attractive alternative to warfarin in patients with AF and at least one other risk factor for stroke, regardless of the type or duration of AF.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".