Impact of Age on Long-Term Urinary Continence after Robotic-Assisted Radical Prostatectomy
Bibliographic record
Abstract
Aim and Objectives: We aimed to test the impact of age on long-term urinary continence (≥12 months) in patients undergoing robotic-assisted radical prostatectomy. Methods and Materials: We relied on an institutional tertiary-care database to identify the patients who underwent robotic-assisted radical prostatectomy between January 2014 and January 2021. Patients were divided into three age groups: age group one (≤60 years), age group two (61–69 years) and age group three (≥70 years). Multivariable logistic regression models tested the differences between the age groups in the analyses addressing long-term urinary continence after robotic-assisted radical prostatectomy. Results: Of the 201 prostate cancer patients treated with robotic-assisted radical prostatectomy, 49 (24%) were assigned to age group one (≤60 years), 93 (46%) to age group two (61–69 years) and 59 (29%) to age group three (≥70 years). The three age groups differed according to long-term urinary continence: 90% vs. 84% vs. 69% for, respectively, age group one vs. two vs. three (p = 0.018). In the multivariable logistic regression, age group one (Odds Ratio (OR) 4.73, 95% CI 1.44–18.65, p = 0.015) and 2 (OR 2.94; 95% CI 1.23–7.29; p = 0.017) were independent predictors for urinary continence, compared to age group three. Conclusion: Younger age, especially ≤60 years, was associated with better urinary continence after robotic-assisted radical prostatectomy. This observation is important at the point of patient education and should be discussed in informed consent.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".