Duloxetine for the treatment of post-prostatectomy stress urinary incontinence
Bibliographic record
Abstract
OBJECTIVES: Stress urinary incontinence (SUI) is a known complication following prostatectomy. Duloxetine, a combined serotonin/norepinephrine reuptake inhibitor, can decrease SUI by increasing urethral sphincter contractility. We examined the outcomes of patients with mild to moderate post-prostatectomy SUI treated with duloxetine. METHODS: We conducted a retrospective review of men treated with duloxetine to manage mild to moderate post-prostatectomy SUI from 2006 to 2012. All patients received oral duloxetine 30 mg once a week, then 60 mg thereafter. Patients were seen one month later to determine drug efficacy and side effects. RESULTS: In total, 94 men were included in the study. Daily pad usage decreased from 2.9 (range: 1-5) to 1.6 (range: 0-4) (p < 0.05). Incontinence Impact Questionnaire (IIQ-7) scores decreased from 13.0 (range: 6-18) to 7.9 (range: 2-16) (p < 0.05). Linear satisfaction scores improved from 0.8 (range: 0-2) to 2.0 (range: 1-3) (p < 0.05). Following a 1-month duloxetine trial, 33/94 (35%) men reported satisfactory SUI improvement and requested to continue the medication. The drug was discontinued in 61/94 (65%) patients due to poor efficacy in 32/94 (34%), intolerable side effects in 14/94 (15%) or both in 15/94 (16%). Reported side effects included fatigue, light-headedness, insomnia, nausea and dry mouth. CONCLUSIONS: Duloxetine improved post-prostatectomy SUI in 47/94 (50%) men following a 1-month trial. However, only 33/94 (35%) patients were able to tolerate the drug. Duloxetine may be considered a treatment option for men with mild to moderate post-prostatectomy SUI.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".