Abstracts From the 1st Canadian Stroke Congress
Bibliographic record
Abstract
Background: We sought to evaluate whether a good initial NCCT (Ͼ 7 on ASPECTS scoring system) and short time to reperfusion predicts good clinical outcome in the Penumbra Pivotal Stroke Trial.Methods: NCCT at presentation was evaluated by two readers blinded to clinical outcomes using ASPECTS.Patients were divided into 3 groups: ASPECTS 7-10(good); 4-6(intermediate) and 0-3(poor).TIMI reperfusion scores, stroke onset to reperfusion and CT to reperfusion times were noted.Primary clinical outcome was mRSՅ2 at 90 days.Results: Of 125 patients, 85 satisfied all inclusion and exclusion criteria.Median NIHSS was 18, 49.4% had good ASPECTSՆ7, 81.2% had TIMI 2-3 reperfusion and 27.1 % good clinical outcomes (mRSՅ2).0/22 patients with ASPECTS Ͻ 4 and 2/20 patients with ASPECTS(4-6) had good clinical outcomes when compared to 21/41 patients with ASPECTS Ն7 [RR 21, 95% CI 4.4-98.6].Patients with onset to reperfusion timeՅ360 mins had better clinical outcomes[RR 3.04 95% CI 1.1-8.34].In the good scan (ASPECTS Ն 7) group (nϭ42), median NIHSS was 16.5, 83.3% achieved TIMI 2-3 with 50% showing good clinical outcomes.Patients with TIMI 2-3 scores (21/35) achieved better clinical outcomes than those with TIMI 0-1(0/6)[RR ϱ] (p value 0.009).Patients with good ASPECTS and onset to reperfusion timeՅ360 mins achieved better clinical outcomes (14/18, 77.8%) when compared to Ͼ360 mins group(7/19, 36.8%)[RR6, 95% CI 1.4-25.58].Conclusion: Proper patient selection based on initial NCCT and faster recanalization are essential in achieving good clinical outcomes in patients with acute ischemic strokes undergoing IA procedures.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.260 | 0.108 |
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".