Single-Port versus Multiple-Port Robot-Assisted Radical Prostatectomy: A Systematic Review and Meta-Analysis
Why this work is in the frame
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Bibliographic record
Abstract
Background: Single-port robotic-assisted radical prostatectomy has been reported as a safe and feasible technique. However, recent studies comparing single-port versus multiple-port robotic radical prostatectomy have displayed conflicting results. Objectives: To investigate the benefit of single-port robotic radical prostatectomy and the impact on outcome compared to multiple-port robotic radical prostatectomy. Methods: Based on PRISMA and AMSTAR criteria, a systematic review and meta-analysis were carried out. Finally, we considered the controlled studies with two cohorts (one cohort for single-port RARP and the other cohort for multiple-port RARP). For statistical analysis, Review Manager (RevMan) software version 5.4 was used. The Newcastle-Ottawa Scale was employed to assess the risk of bias. Results: Five non-randomized controlled studies with 666 patients were included. Single-port robotic radical prostatectomy was associated with shorter hospital stays. Only 60.6% of single-port patients (109/180) required analgesia compared to 90% (224/249) of multiple-port patients (Z = 3.50; p = 0.0005; 95% CI 0.07:0.47). Opioid administration was also significantly lower in single-port patients, 26.2% (34/130) vs. 56.6% (77/136) (Z = 4.90; p < 0.00001; 95% CI 0.15:–0.44) There was no significant difference in operative time, blood loss, complication rate, positive surgical margin rate, or continence at day 90. Conclusion: The available data on single-port robotic radical prostatectomy is very limited. However, it seems comparable to the multiple-port platform in terms of short-term outcomes when performed with expert surgeons. Single-port prostatectomies might provide a shorter hospital stay and a lower requirement for opioids; however, randomized trials with long-term follow-up are mandatory for valid comparisons.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.079 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.058 | 0.014 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it