Abstract 14130: Efficacy and Safety of Endovascular Therapy in Stroke Patients With Large Ischemic Core in Comparison to Medical Management: Meta-Analysis of Randomized Control Studies
Bibliographic record
Abstract
Introduction: Endovascular therapy (EVT) is a treatment recommended for stroke patients with large vessel occlusion and an Alberta Stroke Program Early Computed Tomography Score (ASPECTS) ≥6. However, the utility of EVT in patients with large core ischemic stroke has not been well established. Methods: This meta-analysis assesses EVT's efficacy and safety using available trials comparing EVT to medical management (MM) in stroke patients with large ischemic core. Eligibility criteria: 1) were randomized controlled trials, 2) compared EVT with MM alone, 3) studied patients presenting with LIC cerebrovascular events, and 4) reported outcomes of interest. We extracted data for the major imaging inclusion criteria, the National Institutes of Health Stroke Scale (NIHSS) score, pre-stroke mRs score, and occlusion site. We also extracted outcome data for the EVT groups vs MM groups, including measurement of early neurological recovery, and definition of sICH. Results: Our primary end point was the mean modified Rankin scale score (RSS) at 90-day follow up. EVT was associated with higher odds of significant improvement in functional status with reduction in mean mRS by -0.31 [-0.47; -0.14]) compared to MM. The odds of achieving mRS 0 to 2 was higher in the EVT arm compared to the MM arm (2.53 [1.59; 4.02]). There was no difference in achieving mRS 0 to 3, early neurologic improvement defined according to NIHSS score, overall 90-day mortality and risk of symptomatic ICH between patients treated with EVT or MM in our analysis. Conclusions: Our study suggests that EVT may lead to improved outcomes in stroke patients with large core ischemia.
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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 | 0.022 | 0.042 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.058 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".