Alberta Stroke Program Early Computed Tomography Score, Infarct Core Volume, and Endovascular Therapy Outcomes in Patients With Large Infarct
Bibliographic record
Abstract
Importance: Endovascular therapy (EVT) demonstrated better outcomes compared with medical management in recent randomized clinical trials (RCTs) of patients with large infarct. Objective: To compare outcomes of EVT vs medical management across different strata of the Alberta Stroke Program Early Computed Tomography Score (ASPECTS) and infarct core volume in patients with large infarct. Design, Setting, and Participants: This prespecified secondary analysis of subgroups of the Endovascular Therapy in Acute Anterior Circulation Large Vessel Occlusive Patients With a Large Infarct Core (ANGEL-ASPECT) RCT included patients from 46 stroke centers across China between October 2, 2020, and May 18, 2022. Participants were enrolled within 24 hours of symptom onset and had ASPECTS of 3 to 5 or 0 to 2 and infarct core volume of 70 to 100 mL. Patients were divided into 3 groups: ASPECTS of 3 to 5 with infarct core volume less than 70 mL, ASPECTS of 3 to 5 with infarct core volume of 70 mL or greater, and ASPECTS of 0 to 2. Interventions: Endovascular therapy or medical management. Main Outcomes and Measures: The primary outcome was the ordinal 90-day modified Rankin Scale (mRS) score. Results: There were 455 patients in the trial; median age was 68 years (IQR, 60-73 years), and 279 (61.3%) were male. The treatment effect did not vary significantly across the 3 baseline imaging subgroups (P = .95 for interaction). The generalized odds ratio for the shift in the 90-day mRS distribution toward better outcomes with EVT vs medical management was 1.40 (95% CI, 1.06-1.85; P = .01) in patients with ASPECTS of 3 to 5 and infarct core volume less than 70 mL, 1.22 (95% CI, 0.81-1.83; P = .23) in patients with ASPECTS of 3 to 5 and infarct core volume of 70 mL or greater, and 1.59 (95% CI, 0.89-2.86; P = .09) in patients with ASPECTS of 0 to 2. Conclusions and Relevance: In this study, no significant interaction was found between baseline imaging status and the benefit of EVT compared with medical management in patients with large infarct core volume. However, estimates within subgroups were underpowered. A pooled analysis of large core trials stratified by ASPECTS and infarct core volume strata is warranted. Trial Registration: ClinicalTrials.gov Identifier: NCT04551664.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".