Warfarin Use and the Risk for Stroke and Bleeding in Patients With Atrial Fibrillation Undergoing Dialysis
Bibliographic record
Abstract
BACKGROUND: Current observational studies on warfarin use and the risk for stroke and bleeding in patients with atrial fibrillation (AF) undergoing dialysis found conflicting results. METHODS AND RESULTS: We conducted a population-based retrospective cohort study of patients aged ≥65 years admitted to a hospital with a primary or secondary diagnosis of AF, in Quebec and Ontario, Canada from 1998 to 2007. The AF cohort was grouped into dialysis (hemodialysis and peritoneal dialysis) and nondialysis patients and into warfarin and no-warfarin users according to the first prescription filled for warfarin within 30 days after AF hospital discharge. We determined the association between warfarin use and the risk for stroke and bleeding in dialysis and nondialysis patients. The cohort comprised 1626 dialysis patients and 204 210 nondialysis patients. Among dialysis patients, 46% (756/1626) patients were prescribed warfarin. Among dialysis patients, warfarin users had more congestive heart failure and diabetes mellitus, but fewer prior bleeding events in comparison with the no-warfarin users. Among dialysis patients, warfarin use, in comparison with no-warfarin use, was not associated with a lower risk for stroke (adjusted hazard ratio, 1.14; 95% confidence interval, 0.78-1.67) but was associated with a 44% higher risk for bleeding (adjusted hazard ratio, 1.44; 95% confidence interval, 1.13-1.85) after adjusting for potential confounders. Propensity score-adjusted analyses yielded similar results. CONCLUSIONS: Our results suggest that warfarin use is not beneficial in reducing stroke risk, but it is associated with a higher bleeding risk in patients with AF undergoing dialysis.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".