First-in-man experience of the Versi Retriever in acute ischemic stroke
Bibliographic record
Abstract
OBJECTIVE: To describe our initial experience with the Versi Retriever for mechanical thrombectomy in patients with acute ischemic stroke. METHODS: This study is a single-center, single-arm, first-in-man registry under institutional review board control to evaluate the efficacy and safety of the new stent retriever, the Versi Retriever. Patients with acute ischemic stroke were consecutively enrolled between September and November 2017. The clinical and procedural data were retrospectively analyzed. The angiographic result after the procedure was self-graded based on the Thrombolysis in Cerebral Infarction (TICI) scale by each operator. RESULTS: Eleven patients with a mean age of 69.4 years were treated with the Versi Retriever. Median National Institutes of Health Stroke Scale score on admission was 16 (IQR 10-34). The occluded vessel was located in the anterior circulation in 81.8%. Revascularization rates of TICI 2b-3 and TICI 3 at final angiogram were achieved in 100% and 63.6%, respectively. A favorable functional outcome (modified Rankin Scale 0-2) at 90 days was obtained in 72.7%. No symptomatic intracranial hemorrhage occurred and no procedure-related complication was observed. CONCLUSIONS: Our initial experience suggests that the Versi Retriever is a safe and effective stent retriever for mechanical thrombectomy in patients with acute ischemic stroke. CLINICAL TRIAL REGISTRATION: NCT03366818.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".