The Silk Vista Baby Study: A Multicenter Aneurysm Report From North America and Europe
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The Silk Vista Baby (SVB) flow diverter (FD) stent (Balt SAS) is the first device designed for treating distally located brain aneurysms. It can be delivered through a 0.017-inch ID microcatheter, enabling access to small, distal vessels. The aim of this study was to evaluate the effectiveness, safety, technical success, occlusion rate, and clinical outcomes of the SVB device. METHODS: This retrospective, multicenter study included data from 18 centers from November 2023 to September 2024. Procedures were performed by experienced neurointerventionalists following institutional standards of care. Outcomes analyzed included effectiveness, safety, and aneurysm occlusion rates. Descriptive analyses and Pearson χ 2 or Independent t -Test were used for statistical evaluation. RESULTS: A total of 95 patients, mean age 55.4 years, were included. A total of 31% of aneurysms were ruptured at admission. Most (58.3%) were located in the anterior circulation, and 45% had previous treatment, mainly coiling (69.4%). Complication rates were higher for ruptured aneurysms (24.1%) compared with unruptured ones (9.2%). Two deaths occurred, 1 (1.1%) related to the procedure. At discharge, 87% of patients had modified Rankin Scale ≤2. The latest follow-up showed overall complete/near-complete occlusion rates of 76.1%, with 81.14% for ruptured and 73.43% for unruptured aneurysms. Technical success was higher in unruptured cases (100% vs 93.1%). CONCLUSION: Our case series demonstrated the efficacy of the SVB with a high rate of technical success. The occlusion rates for ruptured cases are comparable with those of other FDs. However, the rates are lower for unruptured cases. This discrepancy is likely due to the characteristics of the aneurysms, particularly in the presence of side branches in bifurcation lesions. The SVB safety profile is similar to other FDs in unruptured cases, while the ruptured group presented more complications.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".