Optimise : Formation of a National Endovascular Treatment Quality Assurance Program
Bibliographic record
Abstract
Stroke Endovascular Treatment (EVT) has been the standard of care for large vessel, anterior circulation strokes since 2015. Systematic measurement of treatment times and outcomes is a critical part of ensuring quality of care. We describe the design and implementation of a scalable, national model for data collection and feedback.The Canadian Stroke Consortium (CSC) has developed a web-based platform that will enable EVT sites across Canada to track performance measures and outcomes for EVTcalled: OPTIMISE (Optimising Patient Treatment In Major Ischemic Stroke with EVT). Principal performance measures include: Door-to-CT, CT-to-Arterial Puncture and Arterial Puncture-to-First Reperfusion times. Immediate and 3 month outcomes can also be tracked. Sites will be provided with reports on a monthly basis in order to identify performance relative to peers for process improvement and policy development. Reports will also provide national benchmarks for comparison.
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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 | 0.044 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".