General vs Nongeneral Anesthesia for Endovascular Thrombectomy in Patients With Large Core Strokes
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The association of anesthesia approach during endovascular thrombectomy (EVT) with clinical outcomes in large strokes is unexplored. We aimed to evaluate whether general anesthesia (GA), compared with non-GA, was associated with better functional outcomes in the SELECT2 trial. METHODS: In a prespecified secondary analysis of the SELECT2 trial that enrolled patients with large strokes on noncontrast CT (Alberta Stroke Program Early CT Score [ASPECTS] 3-5), CT perfusion/MRI (core volume ≥50 mL), or both, functional outcomes were compared in EVT-treated patients who received GA or non-GA and whether this association was modified by stroke severity (NIH Stroke Scale score), ischemic injury estimates, and collateral status was evaluated. The primary outcome was 90-day functional status (ordinal modified Rankin Scale [mRS]). Secondary outcomes were functional independence (mRS scores 0-2), independent ambulation (mRS scores 0-3), complete dependence or death (mRS scores 5-6), and mortality. RESULTS: -interaction = 0.77 and 0.89, respectively). DISCUSSION: In patients with large core strokes randomized in SELECT2, EVT outcomes did not differ significantly based on anesthesia approach (GA or non-GA) without heterogeneity across stroke severity and size. While GA was associated with higher SBP variability and lower minimum SBP, this did not modify GA association with functional outcomes. While allocation to anesthesia approach was nonrandomized, our findings suggest that optimizing institutional protocols for preferred anesthesia technique, whether GA or non-GA, may enhance EVT procedural outcomes. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov ID: NCT03876457. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients presenting within 24 hours with large vessel occlusion strokes undergoing EVT, the 90-day mRS score is comparable in those with or without GA.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".