Group-based pelvic floor muscle training is a more cost-effective approach to treat urinary incontinence in older women: economic analysis of a randomised trial
Bibliographic record
Abstract
QUESTION(S): How cost-effective is group-based pelvic floor muscle training (PFMT) for treating urinary incontinence in older women? DESIGN: Economic evaluation conducted alongside an assessor-blinded, multicentre randomised non-inferiority trial with 1-year follow-up. PARTICIPANTS: A total of 362 women aged ≥ 60 years with stress or mixed urinary incontinence. INTERVENTION: Twelve weekly 1-hour PFMT sessions delivered individually (one physiotherapist per woman) or in groups (one physiotherapist per eight women). OUTCOME MEASURES: Urinary incontinence-related costs per woman were estimated from a participant and provider perspective over 1 year in Canadian dollars, 2019. Effectiveness was based on reduction in leakage episodes and quality-adjusted life years. Incremental cost-effectiveness ratios and net monetary benefit were calculated for each of the effectiveness outcomes and perspectives. RESULTS: Both group-based and individual PFMT were effective in reducing leakage and promoting gains in quality-adjusted life years. Furthermore, group-based PFMT was ≥ 60% less costly than individual treatment, regardless of the perspective studied: -$914 (95% CI -970 to -863) from the participant's perspective and -$509 (95% CI -523 to -496) from the provider's perspective. Differences in effects between study arms were minor and negligible. Adherence to treatment was high, with low loss to follow-up and no between-group differences. CONCLUSION: Compared with standard individual PFMT, group-based PFMT was less costly and as clinically effective and widely accepted. These results indicate that patients and healthcare decision-makers should consider group-based PFMT to be a cost-effective first-line treatment option for urinary incontinence. TRIAL REGISTRATION: ClinicalTrials.govNCT02039830.
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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 | 0.016 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.010 | 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".