Pilot Study of Ureteral Movement in Stented Patients: First Step in Understanding Dynamic Ureteral Anatomy to Improve Stent Comfort
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Ureteral stents may cause significant morbidity, including pain, dysuria, hematuria, and infection. New biomaterials, coatings, and designs have been studied in an attempt to reduce stent-related symptoms, but to date, the ideal comfortable stent has not been developed. In order to facilitate development of a stent that will mold and change with patient movement, we examined stent and ureteral movement with changes in patient body position. PATIENTS AND METHODS: Four women and two men with a median age of 60.5 +/- 7.7 years who underwent shockwave lithotripsy and insertion of a ureteral stent were enrolled. Static radiographs were performed with the patients in four positions: supine, standing, sitting, and bending forward. Differences in stent position were analyzed digitally relative to fixed bony reference points to determine ureteral movement. RESULTS: The renal stent curl was most cephalad when the patient was supine and moved caudally an average of 2.5 +/- 1.5 cm when the patient stood up. The absolute vertical length of the stent was greatest when the patient was supine (31.1 +/- 1.2 cm) and shortened with standing (28.3 +/- 2.3 cm) and sitting (26.6 +/- 1.5 cm). The bladder curl moved an average of 2.3 +/- 1.2 cm vertically with patient movement. CONCLUSIONS: By measuring stent position, we were able to quantify the range of motion of the ureter during changes in body position. Stent movement appears to be a combination of bowing in the proximal ureter and moving within the bladder. Future stent designs may take this into account to decrease stent-related symptoms.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".