Association Between Time to Treatment and Outcomes of Endovascular Therapy vs Medical Management in Patients With Large Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Randomized trials have proven the benefit of endovascular therapy (EVT) for acute large ischemic stroke. This study was to characterize the effect of time to treatment on benefit of EVT vs medical management (MM) among patients with large ischemic stroke. METHODS: This was a post hoc analysis of the Endovascular Therapy in Acute Anterior Circulation Large Vessel Occlusive Patients with a Large Infarct Core randomized trial. Patients who had an Alberta Stroke Program Early Computed Tomography Score of 3-5 or an ischemic core volume of 70-100 mL within 24 hours of symptom onset were treated with EVT plus MM or MM. Onset-to-expected arterial puncture time (OPT) was analyzed as a categorical variable (<6, 6-<12, and 12-24 hours) using binary logistic regression and as a continuous variable using a multivariable fractional polynomial interaction. The primary efficacy outcome was favorable outcomes (modified Rankin Scale scores 0-3) at 90 days. Safety outcomes included any intracranial hemorrhage (ICH), symptomatic ICH, and mortality. RESULTS: interactions >0.10). DISCUSSION: These findings strengthen the benefit of EVT initiated within 13 hours and 22 minutes after symptom onset compared with MM alone in patients with large ischemic stroke, but EVT should not be withheld for patients presenting beyond 13 hours and 22 minutes. Pooled analysis of larger sample sizes is needed. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov; NCT04551664. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that EVT is associated with improved functional outcomes for acute large ischemic stroke within 24 hours after last known well, with no interaction by time.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".