Geometry Governs Mechanics of Cardiovascular Stents
Bibliographic record
Abstract
Cardiovascular stents are tubular lattice structures implanted into a stenosed artery to provide adequate lumen support and promote circulation. Commonly encountered complications are stent migration, NeoIntimal Hyperplasia (NIH), and damage to the arterial wall. Central to all these problems is the mechanical response of a stent to forces operating in situ including stent-artery interaction. The influence of geometry or repetitive pattern of the stent upon its mechanical response is the subject of this study. We focus on damage to the arterial wall caused by the stent which can lead to eventual in-stent restenosis. Stent-artery compliance mismatch and longitudinal strain due to Poisson effect are hypothesized as the main contributing factors to restenosis. Finite Element Analysis (FEA) is employed to compare radial compliance and longitudinal strains of different stent geometries. Existing geometrical calculations in the literature [1] are applied to stents of different geometries to compute a non-dimensional NIH index. The main finding is that hybrid lattice stent designs exhibit negligible longitudinal strains (Poisson effect) as the stent expands/contracts during each Cardiac cycle. Wall stresses can be minimized though a careful tailoring of stent geometry.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".