Endoscopic Treatment of Vesicourethral Stenosis after Radical Prostatectomy: Outcomes and Predictors of Success
Bibliographic record
Abstract
PURPOSE: We describe patency outcomes and predictors of success for the endoscopic treatment of vesicourethral stenosis after radical prostatectomy. MATERIALS AND METHODS: A retrospective review identified 142 patients who underwent endoscopic treatment for vesicourethral stenosis after radical prostatectomy during a 10-year period. Clinical parameters examined were treatment modality, prior endoscopic treatment, age, concurrent radiotherapy, body mass index 35 kg/m(2) or greater, diabetes and smoking. The primary outcome measure was absence of stenosis (less than 16Fr) on followup cystoscopy. Treatment modalities were divided into 5 groups of holmium laser incision, cold knife incision, electrocautery incision, dilation or UroLume® stent. Descriptive statistics as well as univariate and multivariate logistic regression were performed. RESULTS: A total of 142 patients required 292 endoscopic treatments for a mean of 2.1 treatments per patient. The success rate of a single endoscopic treatment was 44.2%. However, 91% of the patients were ultimately treated successfully with endoscopic measures with a mean followup of 9.7 months. On multivariate analysis treatment modality (OR 0.65, 95% CI 0.52-0.80, p <0.001), prior failed treatment (OR 0.86, 95% CI 0.74-0.99, p=0.04) and smoking (OR 0.55, 95% CI 0.34-0.97, p=0.04) were associated with failure, while age (p=0.85), diabetes (p=0.25), radiotherapy (p=0.68) and body mass index 35 kg/m(2) or greater (p=0.92) were not. Compared to holmium laser incision all modalities except UroLume were associated with treatment failure. CONCLUSIONS: Most patients with vesicourethral stenosis after radical prostatectomy are treated successfully with endoscopic modalities but often require multiple procedures. Unlike anterior urethral strictures, in this specific scenario the use of repeat endoscopic treatments appears justified. Holmium laser incision may be more successful compared to other endoscopic modalities.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".