Ninety‐Day Stroke or Transient Ischemic Attack Recurrence in Patients Prescribed Anticoagulation in the Emergency Department With Atrial Fibrillation and a New Transient Ischemic Attack or Minor Stroke
Bibliographic record
Abstract
Background For patients with atrial fibrillation seen in the emergency department (ED) following a transient ischemic attack (TIA) or minor stroke, the impact of initiating oral anticoagulation immediately rather than deferring the decision to outpatient follow-up is unknown. Methods and Results We conducted a planned secondary data analysis of a prospective cohort of 11 507 adults in 13 Canadian EDs between 2006 and 2018. Patients were eligible if they were aged 18 years or older, with a final diagnosis of TIA or minor stroke with previously documented or newly diagnosed atrial fibrillation. The primary outcome was subsequent stroke, recurrent TIA, or all-cause mortality within 90 days of the index TIA diagnosis. Secondary outcomes included stroke, recurrent TIA, or death and rates of major bleeding. Of 11 507 subjects with TIA/minor stroke, atrial fibrillation was identified in 11.2% (1286, mean age, 77.3 [SD 11.1] years, 52.4% male). Over half (699; 54.4%) were already taking anticoagulation, 89 (6.9%) were newly prescribed anticoagulation in the ED. By 90 days, 4.0% of the atrial fibrillation cohort had experienced a subsequent stroke, 6.5% subsequent TIA, and 2.6% died. Results of a multivariable logistic regression indicate no association between prescribed anticoagulation in the ED and these 90-day outcomes (composite odds ratio, 1.37 [95% CI, 0.74-2.52]). Major bleeding was found in 5 patients, none of whom were in the ED-initiated anticoagulation group. Conclusions Initiating oral anticoagulation in the ED following new TIA was not associated with lower recurrence rates of neurovascular events or all-cause mortality in patients with atrial fibrillation.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".