Atrial fibrillation and the use of warfarin in patients admitted to an acute stroke unit.
Bibliographic record
Abstract
OBJECTIVES: To examine the use of warfarin in patients with atrial fibrillation (AF) admitted to hospital because of stroke or transient ischemic attack; and to describe the outcome of AF-associated stroke. DESIGN: Review of the medical records of patients, identified from a prospective registry, admitted from January 1, 1994 through December 31, 1996. SETTING: Tertiary care teaching hospital. RESULTS: AF was present in 92 of 722 (13%) patients at the time of admission. Only eight of 60 (13%) patients with ischemic stroke who were known to be in AF before their stroke were taking warfarin. The in-hospital case-fatality ratio for AF patients was more than double that of patients in sinus rhythm (21% versus 9%, respectively, P=0.001). AF patients were less likely to be discharged home (31% versus 59%, P=0.005). Of the 68 AF patients who survived, 74% left hospital taking warfarin. No warfarin-treated patient experienced intracranial bleeding while in hospital or during follow-up. CONCLUSIONS: Patients with AF had more severe strokes than patients in sinus rhythm. A small proportion of patients with known AF were taking warfarin at the time of hospitalization. Bleeding complications were infrequent. Broader implementation of guidelines for the management of AF is justified to reduce the frequency of stroke in this group of patients.
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".