THROMBECTOMY 6 TO 24 HOURS AFTER STROKE USING THE ALBERTA STROKE PROGRAM EARLY CT SCORE (ASPECTS)
Bibliographic record
Abstract
Background:DAWN trial recently established the benefit of mechanical thrombectomy (MT) for patients with occlusion of intracranial internal carotid (ICA) or middle cerebral artery (M1 or M2), last known to be well 6 to 24 hours earlier with deficit-infarct mismatch. We aim to determine outcomes for MT performed at our centre in similar patients with ASPECTS u2265 7 instead of deficit-infarct mismatch.Method: Analysis of extracted data, between 2013 and 2017, from local Safe Implementation of Treatment in Stroke (SITS) registry. ASPECTS were calculated by a neuro-radiologist blinded to clinical outcome. Primary endpoint was functional independence (modified Rankin score u2264 2) at 90 days.Results:We identified 43 patients with occlusions at the M1-segment (n=24, 55,8%), M2-segment (n=12, 27,9%) and intracranial ICA (n=7, 16,3%). Mean age at stroke onset was 69,7 years (SDu00b112,9). Median admission NIHSS was 14 (IQR 9-19). Stroke onset time was unknown in 20 patients: 14 (32,6%) u2018wake-up strokesu2019 and 6 (14,0%) u2018daytime unwitnessed-onset strokesu2019. Median interval between time last known to be well and groin puncture was 575 min (IQR 400-730 min). Rate of functional independence at 90 days was 60,5%. Rate of symptomatic intracranial haemorrhage was 2,3% and 90-day mortality 9,3%.Conclusion: In our series, patients with ischemic stroke last known to be well 6 to 24 hours earlier and an ASPECTS u2265 7 treated with MT, functional independence rate at 90 days was similar to DAWN trial result (60,5% vs. 49%). Further research is needed to determine reliability of the ASPECTS in assessing favourable outcome for this time-window.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".