E.02 Streamlining hyperacute stroke management at Royal University Hospital
Bibliographic record
Abstract
Background: The Saskatoon stroke program participated in the ESCAPE trial looking at rapid endovascular revascularization for large vessel occlusion. Improvements were necessary to meet the timelines mandates in ESCAPE and to comply with Canadian Best Practice Guidelines. Methods: Retrospective chart review and prospective gathering of key metrics was performed using REDCap (Research Electronic Data Capture) software. Changes adapted from Canadian Best Practice Recommendations for Stroke Care, the ESCAPE protocol, and the Calgary stroke program HASTE project were implemented. Results: Changes implemented included increasing ambulance bypass window to 12 hours, FAST stroke assessment, emergency department pre-notification and registration, stroke alert protocol, team swarm of the patient, administration of tPA in the computed tomography (CT) room, and rapid access to the endovascular suite. Total number of patients between the years 2012 and 2014 was 287, and of those, 93 received tPA. Door-to-CT times decreased from 40 minutes to 21 minutes from 2012 to 2014; and Door-to-Needle (tPA) decreased from 62 minutes to 46 minutes from 2012 to 2014. Conclusions: By following Canadian best practice recommendations for stroke care, the ESCAPE protocol, and adaptation of Calgary stroke program HASTE project, our stroke program implemented changes to reduce treatment times for patients experiencing stroke in our province.
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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 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.023 | 0.004 |
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".