Ureteral stent in ureteroneocystostomy for vesicoureteral reflux
Bibliographic record
Abstract
INTRODUCTION: We aimed to assess the association between stent placement during ureteral reimplantation for vesicoureteral reflux (VUR) and short-term postoperative outcomes. METHODS: We conducted a retrospective analysis of National Surgical Quality Improvement Program-Pediatrics (NSQIP-P). Independent variables included stent placement, age, sex, urologic comorbidity, prior VUR procedures, severity of reflux, preoperative urinary tract infections (UTIs), American Society of Anesthesiologists (ASA) classification, and operative approach. Outcomes of interest were emergency department (ED) visits, operative time, readmissions, unplanned operations, length of hospital stay (LOS), and postoperative UTIs. Descriptive statistics were performed, and Chi-squared and Mann-Whitney U tests were used for univariate analysis. For multivariate analyses, logistic regression, linear regression, and negative binomial models were applied. RESULTS: A total of 4550 patients were identified (median age 47.36 months, 68.7% female, 48.8% stented). In multivariate analyses, ureteral stenting was significantly associated with higher rates of ED visits (p=0.0019), related readmissions (p<0.0001), and postoperative UTIs (p<0.0001). The expected length of hospitalization for the stent group was 37% longer than for the non-stent group (p<0.0001), and the operative time was, on average, 31 minutes longer (p<0.0001). CONCLUSIONS: This study reveals an association between ureteral stenting and short-term adverse postoperative outcomes following ureteral reimplantation for VUR. Consideration should be given to the selective use of stents at the time of ureteral reimplantation for VUR. There are limitations to the study due to the absence of some surgical data in the database, such as type of reimplant, long-term success rate, and type of stent used.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".