Histological examination of vascular damage caused by stent retriever thrombectomy devices
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Although the recently marketed stent retriever thrombectomy devices have demonstrated a high recanalization rate and favorable clinical outcomes, there is a concern about the risks of intimal injuries when pulling out the stent in the unfolded position. In this study, the Solitaire Flow Restoration System and the Trevo retriever were used in a histopathological comparison of vascular injuries caused by stent retriever thrombectomy devices. METHODS: Rabbit carotid arteries were used in the experiments with stent retriever thrombectomy devices. Carotid artery samples were harvested either 1 or 2 weeks postoperatively for histological examination. RESULTS: Histological changes caused by the use of stent retriever thrombectomy devices were observed from the intimal to medial layers. With the Solitaire FR 4 mm, intimal and medial thickening was observed 1 week postoperatively, and progression of intimal thickening was observed 2 weeks postoperatively. The extent of intimal thickening tended to be greater with the Solitaire FR 6 mm than with the Solitaire FR 4 mm, but this difference was not significant. Compared with the Solitaire FR 4 mm, the Trevo had a significantly smaller area of intimal thickening. CONCLUSIONS: Although there are some differences among devices, results from this study indicate that stent retriever thrombectomy devices induce vascular damage that extends to the medial layer.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".