P.100 Endovascular Thrombectomy (EVT) for stroke: experience in a Canadian teaching hospital
Bibliographic record
Abstract
Background: EVT is now recommended as standard of care for stroke in Canada, but its implementation still poses challenges. We studied the delivery of EVT in our hospital, a participanting site in the ESCAPE trial, which serves the province of Nova Scotia. Methods: Patients who underwent EVT December 2011 – December 2016 were identified prospectively. Demographics, process measures, imaging characteristics (Alberta Stroke Program Early CT Score [ASPECTS], collateral score, Thrombolysis in Cerebral Infarction [TICI] score), and outcomes, including modified Rankin score [mRS] ~ 90 days post-EVT, were collected retrospectively. Effectiveness was assessed by comparison with outcomes in the ESCAPE trial. Results: 91 patients (M:F= 48:43; mean age 64 years) presented to hospital after 194 min ± 230 min from last seen normal. In 58%, the ASPECTS was >7. 80% had good/intermediate collaterals. Alteplase was administered to 72% (75% in ESCAPE, p=0.97). EVT mean duration was 70 min ± 62 min. Successful recanalization (≥TICI 2b) was achieved in 76% (vs 72.4% in ESCAPE, p= 0.97). Among the 54 patients recanalized, mRS scores of 0-2, 3-5 and 6 were seen in 57.4, 24.1 and 14.8% respectively; ESCAPE comparators 53, 37 and 10%, p=0.96, 0.86 and 0.91. Conclusions: EVT at our hospital yielded results similar to the ESCAPE trial.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".