Mechanical Thrombectomy in Ischemic Stroke with a Large Infarct Core: A Meta-Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
Background/Objectives: Endovascular treatment (EVT) is recommended for acute ischemic stroke due to large-vessel occlusion (LVO) and an Alberta Stroke Program Early CT Score (ASPECTS) ≥ 6. Randomized controlled trials (RCTs) have recently become available on EVT effects in people with LVO-related large core stroke (ASPECTS 0–5). Here, we provide an updated meta-analysis of the EVT effect on functional neurological status in people with large-core stroke. Methods: The study followed the PRISMA guidelines. PubMed, EMBASE and Cochrane Central were searched for RCTs comparing EVT vs. best medical treatment (BMT) in large-core LVO stroke. The primary outcome was functional independence at 90 days (modified Rankin Scale; mRS 0–2). The secondary outcomes were symptomatic intracranial hemorrhage (sICH), good functional outcome (mRS 0–3) and excellent functional outcome (mRS 0–1). EVT vs. BMT was compared through random effect meta-analysis. Heterogeneity was assessed with the I2 and Q test and risk of bias reported according to the RoB2 tool. Results: Six RCTs were included (n = 1656 patients). All studies had a moderate risk of bias, with blinding bias due to the nature of the intervention, potential allocation bias and incomplete outcome reporting. Functional independence was significantly more frequent in the EVT vs. BMT group (OR = 2.47, 95% CI = 1.52–4.03, p < 0.001). sICH rates (OR = 1.77, 95% CI = 1.01–3.11, p = 0.04) and good functional outcome (OR = 2.20; 95% CI = 1.72–2.81, p < 0.001) were more frequent in the EVT vs. BMT group, while the rates of mRS 0–1 did not differ. Conclusions: In patients with large-core stroke and LVO, EVT plus BMT as compared to BMT alone carries a significant increase in independent ambulation and good functional outcome at 3 months despite the marginal increase in sICH.
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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 | 0.023 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.059 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".