Outcomes of Mechanical Thrombectomy for Patients With Stroke Presenting With Low Alberta Stroke Program Early Computed Tomography Score in Early and Late Time Windows
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: This study aimed to compare outcomes of low Alberta Stroke Program Early Computed Tomography Score (ASPECTS) patients with stroke who underwent mechanical thrombectomy (MT) within 6 hours or 6 to 24 hours after stroke onset. METHODS: A retrospective cohort study was conducted using data from a large multicenter international registry from 2013 to 2023. Patients with low ASPECTS (2-5) who underwent MT for anterior circulation intracranial large vessel occlusion were included. A propensity matching analysis was conducted for patients presented in the early (<6 hours) vs late (6-24 hours) time window after symptom onset or last known normal. RESULTS: Among the 10 229 patients who underwent MT, 274 met the inclusion criteria. 122 (44.5%) patients were treated in the late window. Early window patients were older (median age, 74 years [IQR, 63-80] vs 66.5 years [IQR, 54-77]; P < .001), had lower proportion of female patients (40.1% vs 54.1%; P = .029), higher median admission National Institutes of Health Stroke Scale score (20 [IQR, 16-24] vs 19 [IQR, 14-22]; P = .004), and a higher prevalence of atrial fibrillation (46.1% vs 27.3; P = .002). Propensity matching yielded a well-matched cohort of 84 patients in each group. Comparing the matched cohorts showed there was no significant difference in acceptable outcomes at 90 days between the 2 groups (odds ratio = 0.90 [95% CI = 0.47-1.71]; P = .70). However, the rate of symptomatic ICH was significantly higher in the early window group compared with the late window group (odds ratio = 2.44 [95% CI = 1.06-6.02]; P = .04). CONCLUSION: Among patients with anterior circulation large vessel occlusion and low ASPECTS, MT seems to provide a similar benefit to functional outcome for patients presenting <6 hours or 6 to 24 hours after onset.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.001 | 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".