First clinical multicenter experience with the new Pipeline Vantage flow diverter
Bibliographic record
Abstract
BACKGROUND: Flow diversion is an innovative and increasingly used technique for the treatment of intracranial aneurysms. New flow diverters (FDs) are being introduced to improve the safety and efficacy of this treatment. The aim of this study was to assess the safety, feasibility, and efficacy of the new Pipeline Vantage (PV) FD. METHODS: Patients with intracranial aneurysms treated with the PV at 10 international neurovascular centers were retrospectively analyzed. Patient and aneurysm characteristics, procedural parameters, complications, and the grade of occlusion were assessed. RESULTS: 60 patients with 70 aneurysms (5.0% with acute hemorrhage, 90.0% located in the anterior circulation) were included. 82 PVs were implanted in 61 treatment sessions. The PV could be successfully implanted in all treatments. Additional coiling was performed in 18.6%, and in-stent balloon angioplasty (to enhance the vessel wall apposition) in 24.6%. Periprocedural technical complications occurred in 24.6% of the treatments, were predominantly FD deployment problems, and were all asymptomatic. The overall symptomatic complication rate was 8.2% and the neurological symptomatic complication rate was 3.3%. Only one symptomatic complication was device-related (perforator artery infarctions leading to stroke). After a mean follow-up of 7.1 months, the rate of complete aneurysm occlusion was 77.9%. One patient (1.7%) died due to aneurysmal subarachnoid hemorrhage which occurred before treatment, unrelated to the procedure. CONCLUSIONS: The new PV FD is safe and feasible for the treatment of intracranial aneurysms. The short-term occlusion rates are promising but need further assessment in prospective long-term follow-up studies.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".