Endovascular thrombectomy versus standard medical treatment in acute ischemic stroke patients with large infarcts (ASPECTS ≤ 5): A meta-analysis
Bibliographic record
Abstract
Background: Recent studies highlight the benefits of endovascular thrombectomy (EVT) combined with standard medical treatment (SMT) for acute ischemic stroke (AIS) patients with large infarcts compared to SMT alone. Objective: This study evaluates the efficacy, bleeding risk, and mortality of EVT versus SMT in AIS patients with Alberta Stroke Program Early CT Score (ASPECTS) ≤5. Methods: A systematic review of MEDLINE, Embase, and Cochrane databases was conducted on June 6, 2024, to identify randomized controlled trials (RCTs) comparing EVT plus SMT with SMT alone in AIS patients with ASPECTS ≤5. Primary outcomes included successful reperfusion, modified Rankin scale (mRS) scores of 0–2 and 0–3, and neurological improvement. Secondary outcomes assessed all-cause mortality, intracranial hemorrhage (ICH), and EQ-5D-5L Utility Index. Statistical analyses applied the Mantel–Haenszel method with 95% confidence intervals (CIs), with heterogeneity evaluated via I 2 statistics. Results: Six RCTs involving 1887 patients (944 receiving EVT) were included. EVT significantly increased the incidence of mRS 0–2 (RR 2.50; 95% CI 1.89 to 3.30; p < .001; I 2 = 8%) and mRS 0–3 (RR 1.92; 95% CI 1.50 to 2.46; p < .001; I 2 = 62%). However, EVT was associated with a higher risk of ICH (RR 1.73; 95% CI 1.11 to 2.69; p = .016; I 2 = 0%) and did not reduce mortality compared to SMT (RR 0.86; 95% CI 0.72 to 1.02; p = .082; I 2 = 47%). Conclusion: EVT improves functional outcomes in AIS patients with moderate-to-low ASPECTS but increases the risk of ICH without reducing mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".