Abstract 3776: Apixaban Compared To Aspirin In Patients With Atrial Fibrillation And Prior Transient Ischemic Attack Or Stroke: Results Of A Predefined Subgroup Analysis From Averroes
Bibliographic record
Abstract
Background In patients with atrial fibrillation (AF), vitamin K antagonists (VKA) effectively prevent stroke. However many patients are unsuitable for or unwilling to take VKAs despite a high risk of stroke. Apixaban, a novel factor Xa inhibitor, is effective and well tolerated in these patients. Methods In AVERROES 5.599 patients with AF, at increased risk of stroke and unsuitable for VKA therapy were randomized to receive, double-blind, apixaban 5 mg twice daily or aspirin (81-324 mg/day). The mean duration of follow up was 1.1 years. The primary outcome was stroke or systemic embolism. A pre-specified subgroup analysis was performed to compare patients with and without prior TIA or ischemic stroke ( NCT00496769 ). Results In 764 patients with prior TIA or stroke there were 10 primary outcome events in those randomized to apixaban (2.46%/year) and 33 in those randomized to aspirin (8.27%/year), hazard ratio (HR) =0.29, 95% confidence interval (95% CI) 0.15-0.60; p<0.001)(p for interaction = 0.83) . There were 9 ischemic strokes in those randomized to apixaban (2.21%/year) and 27 in those randomized to aspirin (6.27%/year), hazard ratio (HR) =0.33, (95% CI) 0.15-0.69; p<0.002)(p for interaction = 0.64). Haemorrhagic stroke occurred in one patient on apixaban and 4 patients on aspirin. Mortality rates were 22 (5.30%/year) on apixaban and 27 (6.55%/year on aspirin, (HR=0.82, 95%CI 0.47-1.45; p= 0.50)(p value for interaction = 0.11). There were no statistically significant differences in major bleeds. Conclusions In patients with AF who had a TIA or stroke and unsuitable for VKA therapy, apixaban reduced the risk of stroke or systemic embolism to larger extent than aspirin.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.015 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".