Regional Variation in Transient Ischemic Attack and Minor Stroke in Alberta Emergency Departments
Bibliographic record
Abstract
Background and Purpose— Multiple studies have shown the 90-day risk of stroke following an emergency department (ED) diagnosis of transient ischemic attack (TIA) or minor stroke is significant, with the greatest risk of recurrence being within the first 24 to 48 hours following initial symptom onset. This study explored regional differences in ED disposition, neuroimaging, and subsequent 90-day stroke risk of patients diagnosed with TIA or minor stroke in Alberta. Methods— We used administrative databases to identify ED visits, neuroimaging, and 90-day return visits for TIA or minor stroke in Alberta from April 2011 to March 2016 among adults ≥20 years of age and stratified them based on regions of presentation (Edmonton, Calgary, or nonmajor urban). Results— During the 5-year study period, 22 421 patients had index ED visits for TIA or minor stroke. All 3 regions had a similar number of ED visits for TIA/minor stroke; however, on index ED visit, Calgary had a higher proportion of computed tomographic angiography imaging (48.8%; P <0.0001) compared with Edmonton (6.7%) and nonmajor urban region (5.7%) and higher proportion of discharged patients (83%; P <0.0001) compared with Edmonton (77.7%) and nonmajor urban region (73.5%). The risk of admission for stroke within 90 days of discharge after index ED visit for TIA/minor stroke in Calgary (3.4%) was lower than Edmonton (4.5%) and the nonmajor urban region (4.6%; P =0.002). Conclusions— This study demonstrates regional variation in computed tomographic angiography for neurovascular imaging of patients presenting to the ED for TIA/minor stroke and a possible association with frequency of index visit admission and 90-day readmission for the same problem.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".