The risk of urinary retention following robot-assisted radical prostatectomy and its impact on early continence outcomes
Bibliographic record
Abstract
INTRODUCTION: We aimed to evaluate the risk factors of acute urinary retention (AUR) following robot-assisted radical prostatectomy (RARP), as well as the relationship of AUR with early continence outcomes. METHODS: The records of 740 consecutive patients who underwent RARP by two experienced surgeons at our institution were retrospectively reviewed from a prospectively collected database. Multiple factors, including age, body mass index (BMI), international prostate symptom score (IPSS), prostate volume, presence of median lobe, nerve preservation status, anastomosis time, and catheter removal time (Day 4 vs. 7), were evaluated as risk factors for AUR using univariate and multivariate analysis. The relation between AUR and early return of continence (one and three months) post-RARP was also evaluated. RESULTS: The incidence of clinically significant vesico-urethral anastomotic (VUA) leak and AUR following catheter removal were 0.9% and 2.2% (17/740), respectively. In men who developed AUR, there was no significant relationship with regards to age, BMI, IPSS, prostatic volume, median lobe, nerve preservation, or anastomosis time; however, the incidence of AUR was significantly higher for men with catheter removal at Day 4 (4.5% [16/351]) vs. Day 7 (0.2% [1/389]) (p=0.004). Moreover, patients with early removal of the catheter (Day 4) who developed AUR had an earlier one-month return of 0-pad continence 87.5% (14/16) compared to patients without AUR 45.6% (153/335), with no significant difference at three months. CONCLUSIONS: While AUR is an uncommon complication of RARP, its incidence is much higher than VUA leakage. Further, it is often not well-discussed during patient counselling preoperatively. Moreover, earlier return of urinary continence was observed in patients experiencing AUR following RARP exclusively with catheter removal at Day 4. Future studies are warranted to validate the long-term impact of AUR on continence outcomes.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".