Patient outcomes after treatment of brain aneurysm in small diameter vessels with the silk vista baby flow diverter: A systematic review
Bibliographic record
Abstract
BACKGROUND: The Silk Vista Baby (SVB, BALT) is a first-in-class flow-diverter device delivered using a 0.017" microcatheter, designed for the treatment of intracranial aneurysms, including those in small diameter vessels. This study reports a systematic literature review (SLR) to evaluate the safety and efficacy of using SVB to treat intracranial aneurysms in vessels less than 3.5 mm in diameter. METHODS: We performed a PRISMA-compliant SLR to evaluate the outcomes of SVB in the treatment of aneurysms in small intracranial vessels. Primary outcomes were occlusion status and major stroke, and secondary outcomes included all-cause mortality, procedure-related neurologic death, and post-operative aneurysm rupture. Data were expressed as descriptive statistics only. RESULTS: A total of four studies, including 163 patients with 173 intracranial aneurysms, were included. The most common aneurysm locations were the anterior cerebral artery (24.9% [43/173]), the middle cerebral artery (24.3% [42/173]), and the anterior communicating artery (23.1% [40/173]). Parent artery diameter ranged from 0.9 mm to 3.6 mm, and 29% were acutely or previously ruptured aneurysms. Overall, complete or near-complete occlusion was 72.1% on early-term follow-up. Mortality rate among the studies was 2.5%, with 3 instances adjudicated as neurologic deaths (1.8%). Major stroke was noted in 1.2% of cases, and branch occlusion or stent thrombus formation in 5.5%. CONCLUSION: Our review suggests that SVB is a safe and effective treatment for intracranial aneurysms in small vessels. Further prospective and comparative studies with patient outcome data specific to aneurysm location are needed to confirm the safety and efficacy of SVB.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".