Safety and Efficacy of the LVIS EVO Device for Stent-Assisted Coiling of Intracranial Aneurysms: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The low-profile visualized intraluminal support EVO (LVIS EVO) stent is a novel device for stent-assisted coiling (SAC) that offers improved visibility, radial force, and navigability in tortuous cerebral vessels. This systematic review and meta-analysis evaluated the safety and efficacy of the LVIS EVO stent in treating intracranial aneurysms (IAs). Methods: A systematic search of PubMed, Web of Science, Cochrane Library, and Scopus databases to identify studies reporting clinical outcomes of LVIS EVO in SAC of IAs was performed. Primary outcomes included aneurysm occlusion based on the Raymond–Roy Occlusion Classification (RROC), procedural, and clinical complication rates. Pooled estimates with 95% confidence intervals (CIs) were calculated using either a fixed- or random-effects model. Heterogeneity was assessed using the I2 statistic. Sensitivity analyses were conducted using the leave-one-out method. Results: Twelve studies involving 567 patients and 586 aneurysms were included. Immediate angiographic results showed complete occlusion (RROC I) in 78% (95% CI: 0.53–0.92), residual neck (RROC II) in 13% (95% CI: 0.08–0.21), and residual aneurysm (RROC III) in 9% (95% CI: 0.02–0.34). At follow-up, complete obliteration was observed in 73% (95% CI: 0.60–0.83). Procedural complications occurred in 5% (95% CI: 0.03–0.09), and clinical complications in 6% (95% CI: 0.04–0.10). Conclusions: The LVIS EVO stent demonstrated high technical success, effective aneurysm occlusion, and low complication rates, supporting its safety and efficacy. Prospective studies are warranted to confirm long-term outcomes.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.031 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".