Innovative textile structures designed to prevent type III endoleaks in endovascular stent‐grafts
Bibliographic record
Abstract
The damage caused to the fabric of endovascular stent-grafts most often occurs at the contact zones between the fabrics where they are attached to the apices of Z-shaped stents as a result of normal physiologic pulsatile movement within angulated vessels in vivo. Although design improvements were made over the years, the risks were not fully eliminated even with the newer M-shaped stent reconfiguration. In this study, we proposed to create and manufacture a novel fabric for stent-grafts with specifically designed reinforced zones to enhance resistance to fabric abrasion. These reinforced zones are set at the vicinity of the apices of the Z-shaped stents and between two adjacent Z-shaped stents where folding and pleating are commonly observed to occur in angulated vessels. Three innovative weaving structures with two different types of yarns and two controls were designed and prepared. Two commonly used commercial devices supported, respectively, with ringed stents, and Z-shaped stents were selected as the references for comparison. Textile structures including thickness, water permeability, mechanical properties, (more specifically tensile and bursting stress, as well as fatigue simulation) were tested on all fabrics. Compared to commercially available plain weaves, the fabrics with locally reinforced zones showed improved mechanical characteristics and fatigue resistant properties. A fabric designed with specifically reinforced zones has now clearly been shown to effectively reduce the abrasion caused by the apices of Z-shaped stents. However, further optimization may still be possible.
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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".