Three-Year Outcomes of Recovery of Erectile Function after Open Radical Prostatectomy with Sural Nerve Grafting
Bibliographic record
Abstract
INTRODUCTION: Optimal oncologic control of higher stage prostate cancers often requires sacrificing the neurovascular bundles (NVB) with subsequent postoperative erectile dysfunction (ED), which can be treated with interposition graft using sural nerve. AIMS: To examine the long term outcome of sural nerve grafting (SNG) during radical retropubic prostatectomy (RRP) performed by a single surgeon. METHODS: Sixty-six patients with clinically localized prostate cancer and preoperative International Index of Erectile Function (IIEF) score >20 who underwent RRP were included. NVB excision was performed if the risk of side-specific extra-capsular extension (ECE) was >25% on Ohori' nomogram. SNG was harvested by a plastic surgeon, contemporaneously as the urologic surgeon was performing RRP. IIEF questionnaire was used pre- and postoperatively and at follow-up. MAIN OUTCOME MEASURES: Postoperative IIEF score at three years of men undergoing RRP with SNG. Recovery of potency was defined as postoperative IIEF-EF domain score >22. RESULTS: There were 43 (65%) unilateral SNG and 23 (35%) bilateral SNG. Mean surgical time was 164 minutes (71 to 221 minutes).The mean preoperative IIEF score was 23.4+1.6. With a mean follow-up of 35 months, 19 (28.8%) patients had IIEF score >22. The IIEF-EF scores for those who had unilateral SNG and bilateral SNG were 12.9+4.9 and 14.8+5.3 respectively. History of diabetes (P=0.001) and age (P=0.007) negatively correlated with recovery of EF. 60% patients used PDE5i and showed a significantly higher EF recovery (43% vs. 17%, P=0.009). CONCLUSIONS: SNG can potentially improve EF recovery for potent men with higher stage prostate cancer undergoing RP. The contemporaneous, multidisciplinary approach provides a good quality graft and expedited the procedure without interrupting the work-flow.
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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 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".