Long-term impact of posterior reconstruction urethrovesical anastomosis during robot-assisted prostatectomy
Bibliographic record
Abstract
INTRODUCTION: We aimed to assess early and late continence rates post-robot-assisted radical prostatectomy (RARP), comparing posterior reconstruction (PR) urethrovesical anastomosis (UVA) to conventional urethrovesical anastomosis (C-UVA). METHODS: Consecutive patients with clinically localized prostate cancer undergoing RARP underwent simple randomization to PR-UVA or C-UVA. Return to continence outcomes were assessed using a validated questionnaire (Expanded Prostate Cancer Index Composite [EPIC] Short Form-26) at baseline, two-, three-, four-, six-, eight-, and 12-month followups. Five-year outcomes were assessed by frequency of undergoing continence-improving procedures. RESULTS: A total of 163 patients were randomized 1:1 to PR-UVA or C-UVA from April 2014 to July 2015, and 140 patients completed followup. There were no significant clinical or functional differences between groups preoperatively. Using a continence definition of 0-1 pads/day, the continence rates for PR-UVA vs. C-UVA were 39% vs. 38% at two months, respectively (p=1.0), and 93% vs. 86%, respectively, at 12 months (p=0.3). Frequency of urine leak, quantity of pad use, subjective urinary control, and overall bother improved significantly in all patients during the 12-month study period (p<0.001); however, no difference was demonstrated between groups. Five-year results showed no statistically significant difference in the number of patients undergoing a continence-improving procedure (hazard ratio 1.21, 95% confidence interval 0.40-3.65, p=0.7). CONCLUSIONS: PR-UVA failed to show a benefit in short-term return to urinary continence or need for an incontinence-improving procedure five years post-RARP.
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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 | 0.000 |
| 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".