Stent-Graft Fabrics Incorporating a Specific Corona Ready to Fenestrate
Bibliographic record
Abstract
In situ fenestration of endovascular stent-grafts has become a mainstream bailout technique to treat complex emergent aneurysms while maintaining native anatomical visceral and aortic arch blood supplies. Fabric tearing from creating the in situ fenestration using balloon angioplasty may extend beyond the intended diameter over time. Further tearing may result from the physiologic pulsatile motion at the branching site. A resultant endoleak at the fenestrated sites in stent-grafts could ultimately lead to re-pressurization of the aortic sac and, eventually, rupture. In an attempt to address this challenge, plain woven fabrics were designed. They hold a specific corona surrounding a square-shaped cluster with a plain weave fabric structure, a 2/2 twill, or a honeycomb. The corona was designed to stop potential further tearing of the fabric caused by the initial balloon angioplasty and stent or later post-implantation motion. The cluster within the corona was designed with relatively loose fabric structures (plain weave, 2/2 twill weave, and honeycomb) to facilitate the laser fenestration. Two commercial devices, Anaconda (Vascutek, Terumo Aortic) and Zenith TX2 (Cook), were selected as controls for comparison against this new design. All the specimens were characterized by morphology, thickness, and water permeability. The results demonstrated that all specimens with a low thickness and water permeability satisfied the requirements for a stent graft material that would be low profile and resistant to endoleaks. The in situ fenestrations were performed on all fabrics utilizing an Excimer laser followed by balloon angioplasty. The fabrics were further observed by light microscopy and scanning electron microscopy. The dimension of the fenestrated apertures was smaller than the balloon's diameter. The tearing was effectively confined within the corona. The clinical acceptability of this concept deserves additional bench testing and animal experimentation.
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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) | 0.000 | 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".