Rates of Ischemic Stroke During Warfarin Treatment for Atrial Fibrillation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Recent evidence suggests that there may be an increased risk of ischemic stroke immediately after warfarin initiation. We examined the rate of ischemic stroke among patients with atrial fibrillation newly started on warfarin therapy. METHODS: We conducted a population-based cohort study among Ontario residents aged ≥66 years with atrial fibrillation who received warfarin between April 1, 1997, and March 31, 2010. Each patient was followed up for ≤5 years in 30-day intervals. For each interval, we determined the rate of ischemic stroke. RESULTS: After 5 years, the cumulative incidence of ischemic stroke among new users of warfarin (n=148,446) was 4.0% (n=6006). The risk was highest during the first 30 days after initiation (6.0% per person-year; 95% confidence interval, 5.5%-6.4%) compared with the remainder of follow-up (1.6% per person-year; 95% confidence interval, 1.5%-1.6%), and increased with higher baseline CHADS2 (congestive heart failure, hypertension, age ≥75 years, diabetes, previous stroke) scores. Less frequent monitoring may have contributed. CONCLUSIONS: In a large cohort of older patients with atrial fibrillation, we observed the highest rate of ischemic stroke in the first 30 days after warfarin initiation. Although causation cannot be established given the observational nature of this study, our findings highlight the need for future research in this population.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".