Cost Effectiveness of Warfarin Versus Aspirin in Patients Older Than 75 Years With Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Oral anticoagulants are effective at reducing stroke compared with aspirin in atrial fibrillation patients older than 75 years. Although the benefits of reduced stroke risk outweigh the risks of bleeding, the cost effectiveness of warfarin in this patient population has not yet been established. METHODS: An economic evaluation was conducted alongside a randomized, controlled trial; 973 patients ≥75 years of age with atrial fibrillation were recruited from primary care and randomly assigned to either take warfarin or aspirin. Follow-up was for a mean of 2.7 years. Costs of thrombotic and hemorrhagic events, anticoagulation clinic visits, and primary care utilization were determined. Clinical benefits were expressed in terms of a primary event avoided: fatal/nonfatal disabling stroke, intracranial hemorrhage, or systemic embolism. A cost-utility analysis was performed using quality-adjusted life years as the benefit measure. RESULTS: Total costs over 4 years were lower in the warfarin group (difference, -£165; 95% CI, -£452-£89), primarily driven by the difference in primary event costs. The primary event rate over 4 years was lower in the warfarin group (0.049 versus 0.099), and the quality-adjusted life years score was higher (difference, 0.02; 95% CI, -0.07-0.11). With lower costs and a higher quality-adjusted life years score, warfarin is the dominant treatment, but the differences in both costs and effects are small. CONCLUSIONS: Warfarin is cost-effective compared with aspirin in atrial fibrillation patients age ≥75 years. These data support the anticoagulant therapy option in this high-risk patient population. However, the small differences in costs and effects indicate the importance of exploring patient preferences.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".