Prospective assessment of the incidence and associations of postvoid dribbling after urethroplasty
Bibliographic record
Abstract
INTRODUCTION: The incidence and associations of postvoid dribbling (PVD) after urethroplasty remains unclear. The purpose of this study was to examine the impact of urethroplasty on PVD and factors associated with de novo PVD. METHODS: From 2011-2018, patients were offered enrollment in a prospective study assessing PVD after urethroplasty. PVD was assessed preoperatively and six months post-surgery with the question, "After urinating, do you have post-urination dribbling or leakage of urine?" Choices included, "Never" (1), "Occasionally" (2), "Sometimes" (3), "Most of the time" (4), or "All of the time" (5). A response of 3-5 was considered clinically significant. Wilcoxon signed-rank test was used to compare pre- and postoperative PVD, while logistic regression was used to determine the association between new-onset PVD and clinical variables. RESULTS: A total of 384 patients completed the study, with 46.9% (180) reporting PVD preoperatively compared to 39.8% (153) postoperatively (p=0.01); 18.0% (67) of patients experienced de novo PVD, 57.0% (219) no change, and 25.0% (96) reported improvement. On multivariable logistic regression, patients undergoing anastomotic urethroplasty were less likely to report de novo PVD (odds ratio [OR] 0.33, 95% confidence interval [CI] 0.13-0.83, p=0.02). No other factor was associated with de novo PVD, including age (p=0.59), stricture length (p=0.71), location (p=0.50), etiology (p=0.59), failed endoscopic treatment (p=0.18), previous urethroplasty (p=0.55), or recurrence (p=0.78). De novo PVD was not associated with patient dissatisfaction (10.1% vs. 7.6%, p=0.49). CONCLUSIONS: PVD is common in patients with urethral stricture. While there is an overall improvement after urethroplasty, 18.0% of patients will experience de novo PVD, with a reduced incidence in those undergoing anastomotic urethroplasty.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".