Multicenter clinical trial evaluating the safety and efficacy of mechanical thrombectomy using the Versi Retriever
Bibliographic record
Abstract
BACKGROUND: This study aimed to elucidate the safety and efficacy of mechanical thrombectomy using the Versi Retriever in patients with acute ischemic stroke (AIS). METHODS: This was a prospective, multicenter, single-arm study conducted at 10 institutes in Japan from December 2018 to March 2021 on mechanical thrombectomy using the Versi Retriever in patients with AIS. The primary efficacy outcome was the modified Rankin scale (mRS) 0-2 at 90 days after the procedure. The primary safety outcome was mortality within 90 days after the procedure. RESULTS: Fifty-eight patients with a mean age of 72.7 years were enrolled in the study. The primary efficacy outcome of mRS 0-2 at 90 days was 62.0% (95% CI 47.2-75.3%) in patients within 8 hours of stroke onset. The rate of immediate reperfusion of Thrombolysis in Cerebral Infarction (TICI) grade 2b-3 using the Versi Retriever in three passes was 78.0% (64.0-88.5%). The rate of final reperfusion of TICI 2b-3 was 100% (92.9-100%). The primary safety outcome of mortality within 90 days was 8.0% (2.2-19.2%) in patients within 8 hours of AIS onset. The incidence of intracranial hemorrhage within 24 hours was 12.0% (4.5-24.3%) for symptomatic cases and 32.0% (19.5-46.7%) for asymptomatic cases. CONCLUSION: The Versi Retriever proved to be a safe and effective option for mechanical thrombectomy in patients with AIS.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".