Abstract W P241: Early Anti-Coagulation in Acute Cardio-Embolic Stroke is Safe But Does Not Prevent Recurrent Stroke: A Single Centre Review
Bibliographic record
Abstract
Background: Atrial fibrillation is the most common arrhythmia in older adults and a common cause of stroke. Patients with acute cardio-embolic stroke from atrial fibrillation are at high risk for recurrence with up to 50% of recurrent stroke occurring within 2 weeks of the index event. Anti-coagulation with heparinoids within 48 hours of stroke has been shown to increase risk of symptomatic intracranial hemorrhage (ICH) with no clear benefit on early stroke recurrence. Methods: This study was a retrospective chart review of consecutive patients who were admitted to the stroke service at the Foothills Medical Centre between 2009 and 2011. All patients with an acute stroke with a cardio-embolic etiology and a diagnosis of atrial fibrillation either by history or on electrocardiogram within two years of stroke were reviewed. We hypothesized that anti-coagulation within two weeks of stroke, appropriately begun because of a diagnosis of atrial fibrillation, decreased rates of recurrent stroke without causing an increase in rates of symptomatic ICH. Results: During the three-year period 324 patients were identified with cardio-embolic stroke secondary to atrial fibrillation. Within two weeks of stroke onset 63.0% (203/324) of patients were therapeutic on anti-coagulation with warfarin being the most common anti-coagulant used (67.6%). Patients who were anti-coagulated had a smaller mean stroke volume (18.9 cc vs 49 cc) and lower mean NIHSS at presentation (7 vs 9) but otherwise did not differ in baseline characteristics. Three (0.9%) patients had a clinically significant ICH; only one patient was actively anti-coagulated at the time of ICH, one was taking aspirin only and one was on aspirin and low dose enoxaparin for prevention of deep vein thrombosis. Recurrent stroke occurred in 16 patients (4.9%) within the two-week period. Anti-coagulation did not significantly reduce the risk of recurrent stroke (RR 0.67 95% CI 0.19 - 2.36). Conclusion: Anti-coagulation within 2 weeks of acute stroke in patients with atrial fibrillation appears to be safe among patients with smaller infarcts. Large studies would be needed to show if anticoagulation actually reduced the rate of early recurrent cardioembolic stroke.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".