Endovascular thrombectomy for the treatment of large ischemic stroke: a systematic review and meta-analysis of randomized control trials
Bibliographic record
Abstract
Abstract Importance Endovascular thrombectomy (ET) has previously been reserved for patients with small to medium acute ischemic strokes. Three recent randomized control trials (RCTs) have demonstrated functional benefit and risk profiles for ET in large volume ischemic strokes. Objective The primary objective of the meta-analysis was to determine the combined benefit of ET in adult patients with large volume acute ischemic strokes and to better determine the risk of adverse events following ET. Data Sources We systematically searched MEDLINE, EMBASE, SCOPUS, the Cochrane Central Register of Controlled, and Google Scholar for all RCTs published in English language between January 1, 2010, to February 19, 2023. Study Selection We included only RCTs specifically comparing ET to medical therapy in patients with acute ischemic stroke with large volume infarctions as defined by Alberta Stroke Program Early Computed Tomography Score (ASPECTS) 3-5 or calculated infarct volume of > 50-70mL. Two independent reviewers screened potential studies for full text review and metaanalysis inclusion with conflicts being resolved by consensus or third reviewer. Data Extraction and Synthesis Data was extracted based on pre-specified variables on study methods and design, participant characteristics, analysis approach, as well as efficacy and safety outcomes. Results were combined using a restricted maximum-likelihood estimation random-effects model. Studies were assessed for potential bias and quality of evidence. Main Outcome(s) and Measure(s) The prespecified primary outcome was an overall ordinal shift across the range of modified Rankin scale scores toward a better outcome at 90 days following either ET or medical management for patients with large volume ischemic strokes. Results A total of 3044 studies were screened, and 29 underwent full text review. 3 RCTs (1011 patients) were included in the analysis. The pooled random effects model for the primary outcome of mRS improvement favored ET over medical management, generalized odds ratio 1.55 [95% CI 1.25 – 1.91, T 2 = 0.01, I 2 = 42.84%]. There was a trend toward increased risk of symptomatic ICH in the ET group, relative risk 1.85 [95% CI 0.94 – 3.63, T 2 = 0.00, I 2 = 0.00%]. Conclusions and Relevance In patients with large volume ischemic strokes, ET has a clear functional benefit and does not confer increased risk of significant complications compared to medical management alone.
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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 | 0.030 | 0.073 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.028 | 0.035 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 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".