Thrombectomy for Patients With Large-Volume Ischemic Stroke: A Systematic Review and Meta-Analysis of 6 Randomized Trials
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Debilitating large-volume strokes negatively affect function in patients. Recent high-quality clinical trials evaluated endovascular interventions for improving functional outcomes. We conducted a review and meta-analysis of randomized trials on large-volume cortical infarct treatment with endovascular thrombectomy (EVT). METHODS: A comprehensive literature search was performed (September-October 2024) using databases that included Medline, Embase, Google Scholar, Scopus, and Cochrane Central. Inclusion focused on completed randomized trials involving large-volume strokes with Alberta Stroke Program Early Computed Tomography Score of 3 to 5 and core volumes >50 mL treated with thrombectomy. Data extraction followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Primary outcome evaluated median modified Rankin score at 90 days, and secondary outcomes evaluated independent ambulation and functional independence. Safety outcomes were evaluated, and subgroup analyses compared stroke characteristics with outcomes. Meta-analysis used random effects model for generalized odds ratios (OR), and risk of bias was evaluated with the Cochrane Risk-of-Bias in randomized trials tool. RESULTS: The 6 trials included a total of 1896 subjects, with 952 (50.2%) treated with thrombectomy and medical management, and 944 (49.8%) only managed medically. Thrombectomy resulted in improved primary functional outcome (OR = 1.62, 95% CI, 1.38-1.89). Both secondary functional outcomes improved with thrombectomy treatment (OR = 1.91, 95% CI, 1.51-2.43; OR = 2.49, 95% CI, 1.92-3.24, respectively). The need for decompressive hemicraniectomy or death at 90 days was not different between groups. However, symptomatic hemorrhage and any intracranial hemorrhage were associated with thrombectomy (risk ratio = 1.66, 95% CI, 1.01-2.72; risk ratio = 1.74, 95% CI, 1.30-2.33, respectively). Subgroup analyses showed improved outcomes with thrombectomy treatment (OR = 1.45, 95% CI, 1.26-1.66). Cochrane Risk-of-Bias in randomized trials tool noted some risk in overall bias and outcome measurement but exhibited low risk in other domains. CONCLUSION: EVT significantly improves outcomes in large-volume strokes, widening its spectrum of benefit. Further research should standardize EVT protocols.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.040 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".