Atrial fibrillation detected after stroke is related to a low risk of ischemic stroke recurrence
Bibliographic record
Abstract
Objective To compare the risk of 1-year ischemic stroke recurrence between atrial fibrillation (AF) diagnosed after stroke (AFDAS) and sinus rhythm (SR) and investigate whether underlying heart disease is as frequent in AFDAS as it is in AF known before stroke (KAF). Methods In this retrospective cohort study, we included all ischemic stroke patients admitted to institutions participating in the Ontario Stroke Registry from July 1, 2003, to March 31, 2013. Based on heart rhythm assessed during admission, we classified patients as AFDAS, KAF, or SR. We modeled the relationship between heart rhythm groups and 1-year ischemic stroke recurrence by using Cox regression adjusted for multiple covariates (e.g., oral anticoagulants). We compared the prevalence of coronary artery disease, myocardial infarction, and heart failure among the 3 groups. Results Among 23,376 ischemic stroke patients, 15,885 had SR, 587 AFDAS, and 6,904 KAF. At 1 year, 39 (6.6%) patients with AFDAS, 661 (9.6%) with KAF, and 1,269 (8.0%) with SR had recurrent ischemic strokes (p = 0.0001). AFDAS-related ischemic stroke recurrence adjusted risk was not different from that of SR (hazard ratio 0.90 [95% confidence interval 0.63, 1.30]; p = 0.57). Prevalence of coronary artery disease (18.2% vs 34.7%; p < 0.0001), myocardial infarction (11.6% vs 20.5%; p < 0.0001), and heart failure (5.5% vs 16.8%; p < 0.0001) were lower in AFDAS relative to KAF. Conclusions The lack of difference in 1-year ischemic stroke recurrence between AFDAS and SR and the lower prevalence of heart disease in AFDAS compared to KAF suggest that the underlying pathophysiology of AFDAS may differ from that of KAF.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".