Is It Safe to Switch from a Standard Anterior to Retzius-Sparing Approach in Robot-Assisted Radical Prostatectomy?
Bibliographic record
Abstract
Background: Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) has been shown to lead to better outcomes regarding early continence compared to standard anterior RARP (SA-RARP). The goal of this study was to assess the feasibility and safety of implementing RS-RARP in a tertiary center with experience in SA-RARP. Methods: From February 2020, all newly diagnosed non-metastatic prostate cancer patients for whom RARP was indicated were evaluated for RS-RARP. Data from the first 100 RS-RARP patients were prospectively collected and compared with data from the last 100 SA-RARP patients. Patients were evaluated for Clavien Dindo grade ≥3a complications, urinary continence after 2 and 6 weeks, 3, 6 and 12 months, erectile function, positive surgical margins (PSMs) and biochemical recurrence (BCR). Results: There was no significant difference in postoperative complications at Clavien-Dindo grade ≥3a (SA-RARP: 6, RS-RARP: 4; p = 0.292). At all time points, significantly higher proportions of RS-RARP patients were continent (p < 0.001). No significant differences in postoperative potency were observed (52% vs. 59%, respectively, p = 0.608). PSMs were more frequent in the RS-RARP group (43% vs. 29%, p = 0.034), especially in locally advanced tumors (pT3: 64.6% vs. 43.8%, p = 0.041—pT2: 23.5% vs. 15.4%, p = 0.329). The one-year BCR-free survival was 82.6% vs. 81.6% in the SA-RARP and RS-RARP groups, respectively (p = 0.567). The median follow-up was 22 [18–27] vs. 24.5 [17–35] months in the RS-RARP and SA-RARP groups, respectively (p = 0.008). Conclusions: The transition from SA-RARP to RS-RARP can be safely performed by surgeons proficient in SA-RARP. Continence results after RS-RARP were significantly better at any time point. A higher proportion of PSMs was observed, although it did not result in a worse BCR-free survival.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".