Efficacy and safety of endovascular treatment for acute ischemic stroke due to medium and distal vessel occlusion: a protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
ABSTRACT Introduction Endovascular thrombectomy (EVT) improves outcomes in large-vessel occlusion (LVO) stroke and has recently shown benefit in dominant M2 occlusions. However, its role in medium vessel occlusions (MeVO) and distal vessel occlusions remains uncertain. This systematic review and meta-analysis evaluates the efficacy and safety of EVT plus usual care versus usual care alone in acute ischemic stroke due to MeVO or distal vessel occlusion. Methods We will search four electronic databases (Ovid MEDLINE, Embase, CINAHL and Cochrane CENTRAL) from inception to May 2025 without language and other restrictions. Eligible studies will be randomized trials comparing EVT plus medical therapy versus medical therapy alone in adults with acute ischemic stroke due to MeVO or distal vessel occlusion. Paired reviewers will independently screen identified hits for eligibility, extract data from eligible studies, and assess risk of bias using the Risk Of Bias instrument for Use in SysTematic reviews-for Randomised Controlled Trials (ROBUST-RCT). Clinically important outcomes will include functional disability, mortality, neurological function and cognition, quality of life, recanalization, and adverse events. Certainty of evidence will be assessed using Grading of Recommendations, Assessment, Development and Evaluation (GRADE). Random-effects meta-analyses will be conducted, with pre-defined subgroup analyses planned. Ethics and Dissemination No ethics approval is required. Results will be disseminated via peer-reviewed publication and conference presentations to inform clinicians, guideline developers, and health system decision-makers.
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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 | 0.081 | 0.113 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.022 | 0.036 |
| Bibliometrics | 0.012 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.048 | 0.007 |
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".