Efficacy and safety of apixaban compared with aspirin in the elderly: a subgroup analysis from the AVERROES trial
Bibliographic record
Abstract
BACKGROUND: increasing age is associated with a higher prevalence of atrial fibrillation (AF), and higher risks of stroke and bleeding. We report the effects of apixaban versus acetylsalicylic acid (ASA) in older patients (≥75 years and ≥85 years) compared with younger patients with AF unsuitable for vitamin K antagonists. METHODS: AVERROES (Apixaban Versus ASA to Prevent Stroke In AF Patients Who Have Failed or Are Unsuitable for Vitamin K Antagonist Treatment) trial (n = 5,599) included 1,898 patients ≥75 years and 366 patients ≥85 years. We compared the baseline characteristics and effects of apixaban compared with aspirin on clinical outcomes by age. RESULTS: compared with aspirin, apixaban was more efficacious for preventing strokes and systemic embolism in patients ≥85 years (absolute rate [AR] 1%/year on apixaban versus 7.5%/year on aspirin; hazard ratio [HR] 0.14, 95% confidence interval [CI] 0.02-0.48) compared with younger patients (AR 1.7%/year on apixaban versus 3.4%/year on aspirin; HR 0.50, 95% CI 0.35-0.69) (P-value for interaction = 0.05). Major haemorrhage was higher in patients ≥85 years compared with younger patients but similar with apixaban versus aspirin in both young and older individuals (4.9%/year versus 1.0%/year on aspirin and 4.7%/year versus 1.2%/year on apixaban) with no significant treatment-by-age interaction (P-value = 0.65). CONCLUSIONS: older patients with AF are at particularly high risk of stroke if given aspirin and have substantially greater relative and absolute benefits from apixaban compared with younger patients with no greater risk of haemorrhage. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov number: NCT00496769. URL: https://clinicaltrials.gov/ct2/show/NCT00496769.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.009 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".