Erectile function recovery after robotic-assisted radical prostatectomy (RARP): long term exhaustive analysis across all preoperative potency categories.
Bibliographic record
Abstract
INTRODUCTION: To evaluate erectile function recovery following robotic-assisted radical prostatectomy (RARP) according to preoperative sexual health inventory for men (SHIM) score stratification. MATERIALS AND METHODS: We prospectively collected data on 250 consecutive patients who underwent RARP by a single surgeon between October 2006 and October 2012. Thirty-six patients were excluded because of lack of preoperative SHIM score. All patients had a minimum follow up of 2 years. Patients were divided into four groups according to their preoperative SHIM score: group 1 with normal potency (SHIM 22-25), group 2 with mild ED (SHIM 17-21), group 3 with mild-moderate ED (SHIM 12-16) and group 4 with moderate-severe ED (SHIM 1-11). Patients were followed at 3, 6, 9, 12, 18, 24 months intervals and twice yearly thereafter. SHIM questionnaire and erection hardness scale (EHS) score were collected at each visit. Potency was defined as successful penetration during intercourse (EHS score 3-4) with or without phosphodiesterase type 5-inhibitor (PDE5-I). RESULTS: After exclusion, 214 patients were evaluated. The number of patients in group 1, 2, 3 and 4 were 95, 59, 26 and 34, respectively. At 3, 6, 9, 12, 18, 24 months, SHIM scores and potency rates were statistically different between groups 1 versus 2 versus 3 versus 4 (p < 0.01, at each time point). Patients in each group 1, 2 and 3 showed a statistically significant improvement in potency rates and SHIM scores at consecutive follow up visits up to 24 months (p < 0.01, for each potency group). Potency rates at 24 months for groups 1 to 4 were 83.3%, 54.5%, 50.0%, and 20.7%, respectively (p < 0.001). CONCLUSION: For proper patient counseling and better prediction of erectile function recovery after RARP, it is important to stratify patients according to preoperative SHIM scores. Setting realistic expectations may increase patient satisfaction.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".