Abstract 152: Endovascular Therapy versus Medical Management for Acute Ischemic Stroke With Large Infarct: A Time-Benefit Relationship Analysis
Bibliographic record
Abstract
Objective: Recent randomized trials demonstrated the benefit of endovascular thrombectomy for acute ischemic stroke with large infarct. We aimed to characterize the effect of time to treatment on the benefit of endovascular therapy compared to medical management among patients with acute large ischemic stroke. Methods: Analysis the Endovascular Therapy in Acute Anterior Circulation Large Vessel Occlusive Patients with a Large Infarct Core trial (ANGEL-ASPECT), which was a multicenter, randomized trial at 46 comprehensive stroke centers in China from August 2020 to October 2022. Onset to arterial puncture time (OPT) associated with outcomes of endovascular therapy were analyzed as a category and continuous variable. The primary outcome was favorable outcome (modified Rankin scale 0-3) at 90 days. Secondary outcomes included degree of disability (modified Rankin scale range), symptomatic intracranial hemorrhage, any intracranial hemorrhage, and mortality. Results: Among 455 eligible patients, the median age was 68 years, and median Alberta Stroke Program Early Computed Tomography Score was 3 (interquartile range 3-4). Compared with medical management alone, endovascular therapy plus medical management was associated with higher rates of favorable outcome with OPT within 6 hours (44.4% vs 29.9%, adjusted odds ratio[aOR] 2.78 [95% confidence interval [CI] 1.22-6.32]), 6-12 hours (45.7% vs 29.6%, aOR 2.39 [95% CI 1.21-4.71]), but not in OPT beyond 12 hours (51.6% vs 41.4%, aOR 2.05 [95% CI, 0.88-4.77]). The benefit in favorable outcome became nonsignificant after OPT of 13 hours and 22 minutes. In three OPT intervals, the odds of better disability outcome with endovascular therapy plus medical management than medical management alone were observed; the rates of symptomatic intracranial hemorrhage and mortality were similar, though the rates of any intracranial hemorrhage increased. Conclusion: In patients with large cerebral infarction, endovascular therapy plus medical management was efficacious in improving functional outcomes with acceptable safety in a broad time window of 0 to 24 hours, but greater benefit was observed with earlier treatment. A pooled analysis with larger sample size is needed.
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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 | 0.014 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".