Non-Newtonian Effects on Blood Flow Dynamics in Stented Coronary Artery Bifurcations
Bibliographic record
Abstract
From clinical practice, it is known that coronary artery bifurcations are regions where the flow is strongly perturbed, and is prone to the development of atherosclerotic lesions. Bifurcation lesions have always represented a major challenge for placement of stents for treatment of stenosis. Conventional bare metal stents are mostly used in clinical practice of bifurcation lesion treatments since there is no specific commercially available stent dedicated for treating bifurcations. Stent design is strongly influenced by the specific hemodynamic conditions in a given vessel. Therefore, in principal, what was previously assessed for standard stent design, should be re-assessed for stenting bifurcations. In this paper a blood flow model for stented coronary artery bifurcation is presented. The non-Newtonian approach incorporating blood rheology under low shear rates is presented by employing Carreau model. Computational fluid dynamics modeling is used to adapt the model and characterize the non-Newtonian flow patterns and identify the hemodynamic factors that may influence the stent design. The results shows that the flow conditions and particularly shear stress distribution in the vicinity of stent struts and near arterial wall are significantly different compared to the usually assumed Newtonian flow conditions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".