Biomechanical responses after Wingspan Stent deployment in swine ascending pharyngeal artery
Bibliographic record
Abstract
OBJECTIVES: Symptomatic intracranial atherosclerotic stenosis is associated with a high rate of recurrent stroke. Endovascular angioplasty and stenting using the Wingspan(TM) Stent (Stryker) has been used for treatment of this disorder. However, a recent randomized trial (SAMMPRIS Clinical Trial) reported that it was inferior to aggressive medical management. To explore the cause of stroke complications after treatment with the Wingspan Stent, we simulated the biomechanical responses in a swine ascending pharyngeal artery (APA) using the finite element method. METHODS: A Wingspan Stent was deployed in a swine APA, and simulated stress distributions including radial, circumferential, and wall shear stress were evaluated. Histopathological analysis of the selected APA was made 28 days post-stenting. RESULTS: We detected increased radial stress concentration at distal stent markers with a stent edge and a graded augmentation of radial stress from proximal to distal. There was an impaired wall shear stress near the stent struts and stent markers. Intense neointimal hyperplasia was observed from the middle to distal segment of the stent 28 days after the procedure. DISCUSSION: This preliminary data suggest that the Wingspan Stent produces increased radial stress distribution with distal segment in a tapering artery. It is possible that the radial stress concentration plays a role in the development of neointimal hyperplasia.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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".