Multicenter Assessment of the pREset and pREset LITE for Thrombectomy in Primary Medium Vessels OCCL
Bibliographic record
Abstract
Introduction: To evaluate the safety and efficacy of the pREset and pREset LITE1,2 (Phenox GmbH, Bochum, Germany) stent-retrievers in acute ischemic stroke (AIS) patients with a primary medium vessel occlusion (MeVO). Method(s): A retrospective review of the MAD-MT Consortium, a synthesis of prospectively maintained databases at 42 academic institutions in North America, Asia, and Europe, was performed to analyze consecutive AIS patients who underwent thrombectomy with the pREset 4x20 or pREset LITE 3x20 or 4x20 for a primary MeVO. Patients’ characteristics, procedural complications, angiographic and clinical outcomes were reviewed. Result(s): Between January 2017 and January 2022, 227 patients and MeVO were included (50% female, median age 78 [65–84] years, 45% of IVtPA before thrombectomy). The devices were used in 161/227 (71%,) “medium” vessels (M2, P1, A1) and in 66/227 (29%) “distal” vessels. Conclusion(s): Mechanical thrombectomy using the pREset and pREset LITE appears to be highly effective for MeVO among different centers and physicians, further studies are needed to better define the targeted population. Publication History Article published online: 09 February 2023 © 2023. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution License, permitting unrestricted use, distribution, and reproduction so long as the original work is properly cited. (https://creativecommons.org/licenses/by/4.0/) Thieme Medical and Scientific Publishers Pvt. Ltd. A-12, 2nd Floor, Sector 2, Noida-201301 UP, India
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".