The accumulation of particles in ureteric stents is mediated by flow dynamics: Full-scale computational and experimental modeling of the occluded and unoccluded ureter
Bibliographic record
Abstract
Ureteric stents are clinically deployed to restore urinary drainage in the presence of ureteric occlusions. They consist of a hollow tube with multiple side-holes that enhance urinary drainage. The stent surface is often subject to encrustation (induced by crystals-forming bacteria such as Proteus mirabilis) or particle accumulation, which may compromise stent's drainage performance. Limited research has, however, been conducted to evaluate the relationship between flow dynamics and accumulation of crystals in stents. Here, we employed a full-scale architecture of the urinary system to computationally investigate the flow performance of a ureteric stent and experimentally determine the level of particle accumulation over the stent surface. Particular attention was given to side-holes, as they play a pivotal role in enhancing urinary drainage. Results demonstrated that there exists an inverse correlation between wall shear stress (WSS) and crystal accumulation at side-holes. Specifically, side-holes with greater WSS levels were those characterized by inter-compartmental fluid exchange between the stent and ureter. These “active” side-holes were located either nearby ureteric obstructions or at regions characterized by a physiological constriction of the ureter. Results also revealed that the majority of side-holes (>60%) suffer from low WSS levels and are, thus, prone to crystals accumulation. Moreover, side-holes located toward the proximal region of the ureter presented lower WSS levels compared to more distal ones, thus suffering from greater particle accumulation. Overall, findings corroborate the role of WSS in modulating the localization and extent of particle accumulation in ureteric stents.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".