Favorable first-pass recanalization rates with NeVa™ thrombectomy device in acute stroke patients: Initial clinical experience
Bibliographic record
Abstract
BACKGROUND: The NeVa™ thrombectomy device (Vesalio LLC, Nashville, USA) has been reported to succeed in large vessel occlusion thrombectomy in animal, in-vitro, and clinical studies. Designed with Drop Zone technology, a closed distal tip, and strong expansive radial force, the device demonstrated particular efficiency in resistant "white" thrombi in preclinical research. Our goal is to determine the safety and performance of this novel stent retriever on first-pass rates and overall recanalization. METHODS: The Interventional Neurology Database is a prospectively maintained database of anterior and posterior circulation stroke thrombectomy cases. We retrospectively analyzed cases where the NeVa™ thrombectomy device was used as the first-line treatment strategy. Data collection occurred between January 2019 and January 2020. First-pass recanalization, final recanalization, 90-day functional outcome, complication, and bleeding rates are reported. RESULTS: One hundred eighteen patients were treated with the NeVa™ thrombectomy device. The mean patient age was 69 ± 14 years, the median baseline National Institutes of Health Stroke Scale was 14, and the median initial Alberta Stroke Program Early Computed Tomography score was 8. The median time from groin puncture to successful recanalization was 29 min (interquartile range (IQR): 20-40). First-pass recanalization rates were 56.8% (modified treatment in cerebral infarction (mTICI) 2b/3) and 44.9% (mTICI 2c/3). Final successful recanalization rate was 95.8% (thrombolysis in cerebral infarction 2b/3). Favorable functional outcome (modified Rankin Scale 0-2) was 53% in the "first-pass" subgroup and 42.4% in the total patient population. The median number of passes to achieve the final recanalization score was 1 (IQR 1-2). The rate of embolization into new territory was 1.7%. Four patients (3.3%) had symptomatic hemorrhage. CONCLUSIONS: In our experience, the NeVa™ device demonstrated high first-pass and overall recanalization rates along with a good safety profile.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".