Periprocedural safety and technical outcomes of the new Silk Vista Baby flow diverter for the treatment of intracranial aneurysms: results from a multicenter experience
Bibliographic record
Abstract
PURPOSE: The aim of our study was to assess the technical success and the safety of this new low-profile flow diverter Silk Vista Baby (SVB) by evaluating the intraprocedural and periprocedural complication rate. MATERIAL/METHODS: Clinical, procedural, and angiographic data were analyzed. RESULTS: 41 consecutive patients (28 women; age average 50.5 years) with 43 aneurysms were treated with SVB. Aneurysm sizes were classified by their maximum diameter, with an average size of 9.5 mm (range 2-30 mm). Thirty-four cases were unruptured. five aneurysms previously ruptured, had recurrence after the initial coiling. There were two ruptured cases. Aneurysms' locations were: M1 segment (five cases), M2 segment (three cases), M3 segment (one case), middle cerebral artery (MCA) bifurcation (six cases), carotid-T (two cases), anterior communicating artery/A1/A2 (11 cases), pericallosal artery (four cases), supraclinoid ICA (two cases), PCom (one case), V4 segment (three cases), PCA (three cases), SCA (one case), and PICA (one case). We had five intraprocedural complications which resolved without clinical consequences and three events postprocedural events. Initial occlusion rates were: eight aneurysms (18.6%) were completely occluded, five aneurysms (11.6%) showed near-complete occlusion, four cases (9.3%) showed incomplete filling, and 26 cases (60.4%) showed persisting filling. The mRS score at discharge from the hospital did not change from the admission mRS score. CONCLUSION: Our study demonstrated that the use of the new low-profile flow diverter, SVB device, for the treatment of intracranial aneurysms is feasible and technically safe.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".