Clinical outcomes of patients with diabetes and atrial fibrillation treated with apixaban: results from the ARISTOTLE trial
Bibliographic record
Abstract
AIMS: We compared clinical outcomes in patients with AF with and without diabetes in the Apixaban for Reduction in Stroke and Other Thromboembolic Events in Atrial Fibrillation trial. METHODS AND RESULTS: The main efficacy endpoints were SSE and mortality; safety endpoints were major and major/clinically relevant non-major bleeding. A total of 4547/18 201 (24.9%) patients had diabetes who were younger (69 vs. 70 years), more had coronary artery disease (39 vs. 31%), and higher mean CHADS2 (2.9 vs. 1.9) and HAS-BLED scores (1.9 vs. 1.7) (all P < 0.0001) than patients without diabetes. Patients with diabetes receiving apixaban had lower rates of SSE [hazard ratio (HR) 0.75, 95% confidence interval (CI) 0.53-1.05), all-cause mortality (HR 0.83, 95% CI 0.67-1.02), cardiovascular mortality (HR 0.89, 95% CI 0.66-1.20), intra-cranial haemorrhage (HR 0.49, 95% CI 0.25-0.95), and a similar rate of myocardial infarction (HR 1.02, 95% CI 0.62-1.67) compared with warfarin. For major bleeding, a quantitative interaction was seen (P-interaction = 0.003) with a greater reduction in major bleeding in patients without diabetes even after multivariable adjustment. Other measures of bleeding showed a consistent reduction with apixaban compared with warfarin without a significant interaction based on diabetes status. CONCLUSION: Apixaban has similar benefits on reducing stroke, decreasing mortality, and causing less intra-cranial bleeding than warfarin in patients with and without diabetes.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".