Selection of Patients and Anesthetic Types for Endovascular Treatment in Acute Ischemic Stroke: A Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
BACKGROUND: and Purpose Recent randomized controlled trials have demonstrated consistent effectiveness of endovascular treatment (EVT) for acute ischemic stroke, leading to update on stroke management guidelines. We conducted this meta-analysis to assess the efficacy and safety of EVT overall and in subgroups stratified by age, baseline stroke severity, brain imaging feature, and anesthetic type. METHODS: Published randomized controlled trials comparing EVT and standard medical care alone were evaluated. The measured outcomes were 90-day functional independence (modified Rankin Scale ≤2), all-cause mortality, and symptomatic intracranial hemorrhage. RESULTS: Nine trials enrolling 2476 patients were included (1338 EVT, 1138 standard medical care alone). For patients with large vessel occlusions confirmed by noninvasive vessel imaging, EVT yielded improved functional outcome (pooled odds ratio [OR], 2.02; 95% confidence interval [CI], 1.64-2.50), lower mortality (OR, 0.75; 95% CI, 0.58-0.97), and similar symptomatic intracranial hemorrhage rate (OR, 1.12; 95% CI, 0.72-1.76) compared with standard medical care. A higher proportion of functional independence was seen in patients with terminus intracranial artery occlusion (±M1) (OR, 3.16; 95% CI, 1.64-6.06), baseline Alberta Stroke Program Early CT score of 8-10 (OR, 2.11; 95% CI, 1.25-3.57) and age ≤70 years (OR, 3.01; 95% CI, 1.73-5.24). EVT performed under conscious sedation had better functional outcomes (OR, 2.08; 95% CI, 1.47-2.96) without increased risk of symptomatic intracranial hemorrhage or short-term mortality compared with general anesthesia. CONCLUSIONS: Vessel-imaging proven large vessel occlusion, a favorable scan, and younger age are useful predictors to identify anterior circulation stroke patients who may benefit from EVT. Conscious sedation is feasible and safe in EVT based on available data. However, firm conclusion on the choice of anesthetic types should be drawn from more appropriate randomized controlled trials.
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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 | 0.024 | 0.051 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.052 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".