Abstract WP197: Timing Of Anticoagulation After Ischemic Stroke In Patients With Atrial Fibrillation: An International Survey
Bibliographic record
Abstract
Introduction: The timing of direct oral anticoagulant (DOAC) after atrial fibrillation (AF)-related stroke is unknown. Most guidelines are inconsistent and based on expert opinion. We conducted a survey to evaluate the global practice patterns of this common clinical scenario. Methods: We used an electronic survey with practice-related demographic and clinical questions of 10 cases with different stroke severities and sizes: transient ischemic attack, small, medium, large, and strokes with hemorrhagic infarction and parenchymal hematoma. Results: A total of 242 clinicians from 21 countries completed at least one clinical scenario. The majority of the respondents were from Australia (36.4%) or Canada (22.7%). Stroke-specific sub-specialty training was self-reported in 82.2% of the respondents. Median (IQR) time spent dedicated to stroke patient care/research was 70 (60) % of total working hours. Only 14% of responding clinicians reported current participation in a randomized trial of DOAC initiation timing after AF-related stroke. Stroke size, severity, and the grade of hemorrhage if present seem to be determinants of the decisions. Lack of consensus was observed in moderate stroke, multi-territory infarcts, large stroke, and in the presence of HT. The majority of respondents would be willing to randomize patients with different stroke sizes and severities with/without HT in a clinical trial of early versus delayed initiation of DOAC after AF-related stroke. Conclusions: Decisions related to the timing of DOAC initiation after AF-related stroke vary globally. The variability in clinical practice will continue until randomized controlled trials are completed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".