Association of atrial fibrillation with mortality and disability after ischemic stroke
Bibliographic record
Abstract
OBJECTIVE: We determined whether patient characteristics (age, sex, comorbidities), stroke severity, and quality of care explained a proportion of the association between atrial fibrillation (AF) and increased disability and mortality in patients with acute ischemic stroke. METHODS: The study included a prospective cohort of consecutive patients admitted with acute ischemic stroke included in the Registry of the Canadian Stroke Network (July 1, 2003 to March 31, 2008). Multivariable logistic regression analyses were used to determine the magnitude of association between AF and modified Rankin score 4-5 at discharge, 30-day mortality, and 1-year mortality. RESULTS: There were 10,528 patients admitted with acute ischemic stroke. AF was associated with an increased risk of severe disability and mortality, but the magnitude of association was substantially attenuated in the full multivariable models: modified Rankin score 4-5 at discharge (univariate odds ratio [OR] 1.74, 95% confidence interval [CI] 1.57-1.93; multivariable OR 1.19, 95% CI 1.03-1.36), 30-day mortality (univariate OR 2.52, 95% CI 2.25-2.84; multivariable OR 1.36, 95% CI 1.17-1.58), and 1-year mortality (univariate OR 2.41, 95% CI 2.19-2.66; multivariable OR 1.25, 95% CI 1.10-1.42). Older age and increased stroke severity explained most of the association between AF and poor stroke outcomes. We found no association between AF and poor stroke outcomes in patients receiving therapeutic preadmission oral anticoagulant therapy. CONCLUSIONS: Older age and increased stroke severity explain most of the association between AF and poorer outcomes after acute ischemic stroke. Nonuse of oral anticoagulant therapy represents the most important modifiable care gap to mitigate the association between AF and poor outcomes after ischemic stroke.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".