Comparison of urethral-sparing versus non urethral-sparing techniques of robot-assisted simple prostatectomy: a systematic review and meta-analysis of sexual, functional, and surgical outcomes
Bibliographic record
Abstract
Simple prostatectomy (SP) with urethral preservation offers various benefits. Recent advancements in technology have made urethral-sparing robot-assisted simple prostatectomy (US-RASP) more feasible. This systematic review compares the efficacy of US-RASP to non-urethral-sparing robot-assisted simple prostatectomy (Non-US-RASP). A systematic literature search was conducted on PubMed, Scopus, ProQuest, Cochrane Library, and ScienceDirect, following PRISMA 2020 guidelines up to September 2024. Meta-analyses of sexual, functional, and surgical outcomes were performed using Review Manager version 5.4. The risk of bias was assessed with the Newcastle-Ottawa scale (NOS). Six observational studies involving 615 patients were included (332 US-RASP versus 283 non-US-RASP). US-RASP significantly improved sexual outcomes, with higher 6-month ejaculatory preservation (OR 31.77, 95% CI: 13.28 to 76.02, p<0.001) and a higher 12-month MSHQ-EjD SF score (MD 6.38, 95% CI: 5.90 to 6.85, p<0.001). Surgical outcomes favored US-RASP with shorter catheterization time (MD -2.67, 95% CI: -4.63 to -0.71, p=0.008) and reduced length of stay (MD -1.39, 95% CI: -2.51 to -0.28, p=0.01). However, US-RASP was associated with a higher 12-month PVR score (MD 14.00, 95% CI: 12.33 to 15.68, p<0.001). This meta-analysis suggests that US-RASP is an effective alternative to Non-US-RASP, demonstrating better sexual and surgical outcomes despite a higher PVR. However, these findings should be confirmed with a well-designed larger randomized trial.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.034 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".