Duloxetine compared with placebo for the treatment of women with mixed urinary incontinence
Bibliographic record
Abstract
AIMS: Evaluate duloxetine in the treatment of women with mixed urinary incontinence (MUI). MATERIALS AND METHODS: 588 women, 19-85 years old with >or=4 incontinence episodes/week were randomly assigned to duloxetine 80 mg/day (N = 300) or placebo (N = 288). Patients were classified into three symptom subgroups: stress or urge predominant MUI (SPMUI or UPMUI) or balanced MUI (BMUI) based on their responses to the validated Stress/Urge Incontinence Questionnaire. Half the population was randomly assigned to have urodynamics; SPMUI, UPMUI, and BMUI condition diagnoses were based on signs, symptoms, and urodynamic observations. The primary outcome measure was the change in incontinence episode frequency (IEF). Secondary outcome measures included the Incontinence Quality of Life (I-QOL) scores, the ICI Quality of Life (ICIQ-SF) score, and the Patient Global Impression of Improvement (PGI-I) rating. RESULTS: At baseline, women with SPMUI averaged 15.9 IEF/week (61% stress), those with UPMUI averaged 13.2 (70% urge), and those with BMUI averaged 16.5 (52% urge). Overall IEF decreases were significantly greater with duloxetine than placebo (median percent reduction 60% vs. 47%, P < 0.001); both UUI and SUI episodes were significantly decreased with duloxetine (median SUI IEF reduction 59% vs. 43%, P = 0.001; UUI IEF reduction 58% vs. 40%, P < 0.001). Duloxetine IEF decreases were significantly greater for patients with SPMUI conditions and symptoms and for those with UPMUI conditions but not symptoms. Significant benefits were also demonstrated with duloxetine for improvements in I-QOL total score (11.5 points vs. 8.1 points, P = 0.002), all three I-QOL subscale scores, and for the ICIQ-SF score (-2.6 vs. -1.7, P = 0.002) as well as for PGI-I ratings (much/very much better 44.2% vs. 27.3%, P = 0.001). CONCLUSION: Duloxetine demonstrated significant efficacy in this population of women with MUI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| 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".