Single Session Pre-Operative Pelvic Floor Muscle Training with Biofeedback on Urinary Incontinence and Quality of Life after Radical Prostatectomy
Bibliographic record
Abstract
Purpose: Urinary incontinence (UI) is a common complication of radical prostatectomy (RP) affecting patient's quality of life (QoL). In the present study, we aimed to investigate the effects of single-session preoperative pelvic floor muscle training (PFMT) with biofeedback (BFB) on short- and mid-term postoperative UI and QoL. Materials and Methods: This study was performed between 2018 and 2020. The patients were randomized into two groups: the case group received a training session with BFB, supervised oral and written instructions on pelvic floor muscle exercises in a 1-h-long training session 1 month before the surgery. Patients were asked to regularly perform exercises immediately after the session until surgery. The controls received no instructions. We used the International Consultation on Incontinence Questionnaire-UI (ICIQ-UI) short-form and ICIQ-Lower Urinary Tract Symptoms QoL Module (ICIQ-LUTSqol) at 1, 3, and 6 months after removing the urinary catheter. Results: A total of 80 patients with a mean age of 63.83 ± 3.61 years were analyzed. Patient characteristics were similar between the groups. The mean ICIQ-UI score was significantly lower in the intervention group at 1 and 3 months after catheter removal ( P = 0.01 and P = 0.029, respectively) but similar at 6 months ( P = 0.058). The mean ICIQ-LUTSqol score was significantly lower in the intervention group at 1, 3, and 6 months after catheter removal ( P < 0.001, P = 0.005, and P = 0.011, respectively). Conclusion: A single session of preoperative PFMT with BFB has significant short-term effects on UI after RP but not at 6 months. However, this intervention can improve LUTS-related QoL even at 6 months after catheter removal.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".