Abstract 448: Effects of Secondary Embolization on Endovascular Treatment Outcomes in Patients with Acute Ischemic Stroke: Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background Endovascular thrombectomy is standard for large‐vessel occlusion stroke, but distal embolization is common and may diminish benefits with mixed evidence on its clinical impact. Given heterogeneous methods and findings across studies, a meta‐analysis is warranted to quantify how distal embolization affects the outcomes. Methods A comprehensive literature search was conducted across various databases until June 2025 to identify relevant studies assessing the outcomes after distal embolization. The quality was assessed using the New Castle Ottawa tool and the analysis was performed using RevMan 5 software. Results Distal embolization during mechanical thrombectomy was not associated with higher odds of 90‐day functional independence (mRS 0‐2) (OR 0.64, P = 0.06) or with 90‐day mortality (OR 1.16; P = 0.61). Symptomatic intracranial hemorrhage rates were also similar between groups (OR 1.38, P = 0.34). In contrast, distal embolization was associated with greater worsening in NIHSS from baseline to discharge (MD 5.58; P = 0.004; I 2 = 26%) and lower odds of successful reperfusion (OR 0.42; P < 0.0001; I 2 = 27%). Conclusion Distal embolization during mechanical thrombectomy does not appear to alter 90‐day functional independence, mortality, or symptomatic intracranial hemorrhage, but it is associated with lower rates of successful reperfusion and worse early neurological status at discharge. These findings suggest that distal embolization chiefly undermines immediate procedural and short‐term clinical outcomes, highlighting the need to refine techniques and devices to minimize its occurrence.
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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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.038 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".