Complications following artificial urinary sphincter placement after radical prostatectomy and radiotherapy: a meta‐analysis
Bibliographic record
Abstract
OBJECTIVE: To conduct a systematic review and meta-analysis of artificial urinary sphincter (AUS) placement after radical prostatectomy (RP) and external beam radiotherapy (EBRT). PATIENTS AND METHODS: There were 1 886 patients available for analysis of surgical revision outcomes and 949 for persistent urinary incontinence (UI) outcomes from 15 and 11 studies, respectively. The mean age (sd) was 66.9 (1.4) years and the number of patients per study was 126.6 (41.7). The mean (sd, range) follow-up was 36.7 (3.9, 18-68) months. A systematic database search was conducted using keywords, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Published series of AUS implantations were retrieved, according to the inclusion criteria. The Newcastle-Ottawa Score was used to ascertain the quality of evidence for each study. Surgical results from each case series were extracted. Data were analysed using CMA statistical software. RESULTS: AUS revision was higher in RP + EBRT vs RP alone, with a random effects risk ratio of 1.56 (95% confidence interval [CI] 1.02-2.72; P < 0.050; I(2) = 82.0%) and a risk difference of 16.0% (95% CI 2.05-36.01; P < 0.080). Infection/erosion contributed to the majority of surgical revision risk compared with urethral atrophy (P = 0.020). Persistent UI after implantation was greater in patients treated with EBRT (P < 0.001). CONCLUSIONS: Men receiving RP + EBRT appear at increased risk of infection/erosion and urethral atrophy, resulting in a greater risk of surgical revision compared with RP alone. Persistent UI is more common with RP + EBRT.
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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 | 0.019 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.065 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".