Long-term efficacy and safety of endovascular thrombectomy for acute ischemic stroke with large vessel occlusion: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: Endovascular thrombectomy (EVT) improves functional outcomes at 90 days in patients with acute ischemic stroke (AIS) with large vessel occlusion (LVO). However, its long-term efficacy and safety beyond 90 days remain unclear. Objective: We conducted a systematic review and meta-analysis to evaluate the efficacy and safety of EVT plus best medical treatment (BMT) versus BMT alone beyond 90 days in patients with AIS and LVO. Methods: PubMed, Embase, and Cochrane Central databases were searched to identify randomized controlled trials (RCTs) comparing EVT plus BMT versus BMT alone in AIS patients with LVO. Primary outcomes included functional independence (mRS ≤2), independent ambulation (mRS ≤3), death or dependency (mRS 4–6), and all-cause mortality beyond 90 days. We applied a random-effects model and pooled risk ratios (RRs) along with 95% confidence intervals (CIs) using the Cochrane RoB2 tool for assessing risk of bias in randomized trials. Results: Seven RCTs with 2358 patients (56% males) were included. The mean age of the patients was 69.5 years and mean follow-up duration was 1.2 years. The results showed that EVT combined with BMT improved functional independence (mRS ≤2) (RR 2.08, CI: 1.55–2.80; P < 0.00001), independent ambulation (mRS ≤3) (RR 1.71, CI: 1.36–2.15; P < 0.00001), and quality of life (SMD 0.36; CI: 0.19–0.54; P < 0.00001) beyond 90 days compared to BMT alone. Moreover, the EVT plus BMT group also had a significantly reduced death or dependency (mRS 4–6) (RR 0.78, CI: 0.73–0.84; P < 0.00001) and all-cause mortality (RR 0.83, CI: 0.76–0.90; P < 0.0001) beyond 90 days than the BMT group. All RCTs were rated as having a low risk of bias. Conclusion: EVT combined with BMT significantly improves long-term functional outcomes and quality of life and reduces mortality in AIS patients with LVO compared to BMT 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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.040 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 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".