Incidence of urinary incontinence following endoscopic laser enucleation of the prostate by en-bloc and non-en-bloc techniques: a multicenter, real-world experience of 5068 patients
Bibliographic record
Abstract
We aim to evaluate the incidence of incontinence following laser endoscopic enucleation of the prostate (EEP) comparing en-bloc (Group 1) versus 2-lobe/3-lobe techniques (Group 2). We performed a retrospective review of patients undergoing EEP for benign prostatic enlargement in 12 centers between January 2020 and January 2022. Data were presented as median and interquartile range (IQR). Univariable and multivariable logistic regression analysis was performed to evaluate factors associated with stress urinary incontinence (SUI) and mixed urinary incontinence (MUI). There were 1711 patients in Group 1 and 3357 patients in Group 2. Patients in Group 2 were significantly younger (68 [62-73] years vs 69 [63-74] years, P = 0.002). Median (interquartile range) prostate volume (PV) was similar between the groups (70 [52-92] ml in Group 1 vs 70 [54-90] ml in Group 2, P = 0.774). There was no difference in preoperative International Prostate Symptom Score, quality of life, or maximum flow rate. Enucleation, morcellation, and total surgical time were significantly shorter in Group 1. Within 1 month, overall incontinence rate was 6.3% in Group 1 versus 5.3% in Group 2 ( P = 0.12), and urge incontinence was significantly higher in Group 1 (55.1% vs 37.3% in Group 2, P < 0.001). After 3 months, the overall rate of incontinence was 1.7% in Group 1 versus 2.3% in Group 2 ( P = 0.06), and SUI was significantly higher in Group 2 (55.6% vs 24.1% in Group 1, P = 0.002). At multivariable analysis, PV and IPSS were factors significantly associated with higher odds of transient SUI/MUI. PV, surgical time, and no early apical release technique were factors associated with higher odds of persistent SUI/MUI.
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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 | 0.000 |
| 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".