Uniform Expansion of a Polymeric Helical Stent
Bibliographic record
Abstract
Helical coil polymeric stents provide an alternative method of stenting compared to traditional metallic stents, but require additional investigation to understand deployment, expansion, and fixation. A bilayer helical coil stent consisting of PLLA and PLGA was investigated using the finite element model to evaluate performance by uniform expansion and subsequent recoiling. In vitro material characterization studies showed that a preinsertion water-soaking step to mimic body implantation conditions provided the required ductility level expansion. In this case, the mechanical contribution of the outer PLGA layer was negligible since it softened significantly under environmental conditions. The viscoelastic response was not considered in this study since the strain rate during expansion was relatively slow and the material response was primarily plastic. The numerical model was validated with available experimental expansion and recoiling data. A parametric study was then undertaken to investigate the effect of stent geometry and coefficient of friction at the stent-cylinder interface on the expansion and recoiling characteristics. The model showed that helical stents exhibit a uniform stress distribution after expansion, which is important for controlled degradation when using biodegradable materials. The results indicated that increasing stent width, pitch value, and coil thickness resulted in a larger diameter after recoiling, which would improve fixation in the artery. It was also noted that a helical stent should have more than five coils to be stable after recoiling. This work is part of a larger research study focused on the performance of a balloon-inflated polymeric helical stent for artery applications.
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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".