Effectiveness of Pelvic Floor Muscle and Education-Based Therapies on Bladder, Bowel, Vaginal, Sexual, Psychological Function, Quality of Life, and Pelvic Floor Muscle Function in Females Treated for Gynecological Cancer: A Systematic Review
Bibliographic record
Abstract
PURPOSE OF REVIEW: Gynecological malignancies are prevalent in females, and this population is likely to experience symptoms of pelvic floor disorders and sexual dysfunction. Non-surgical, non-pharmaceutical conservative therapies, namely pelvic floor muscle (PFM) therapies and education-based interventions, could be beneficial for this population. The purpose of this systematic review was to examine the evidence regarding their effectiveness on bladder, bowel, vaginal, sexual, psychological function, quality of life, and PFM function in gynecological cancer populations. RECENT FINDINGS: Six databases were searched to identify studies employing any interventional study design, except case studies, to investigate the effect of PFM therapies, education-based interventions, or combined therapies on any outcome of interest. The search yielded 4467 results, from which 20 studies were included. Of these, 11 (55%) were RCTs, two (10%) were non-RCTs with two groups, and seven (35%) were non-RCTs with a single group. Findings suggest that combined (multimodal) therapies, specifically PFM (active > passive) + education therapies, appear more effective for vaginal, overall pelvic floor, sexual, and PFM function. PFM therapies (active and/or electrostimulation) may improve bladder outcomes. Limited evidence suggests PFM (active) + education therapies may improve bowel function. Conservative therapies may improve psychological function, although available data do not appear to favor a particular therapy. Given the conflicting findings regarding quality of life, no clear conclusions can be made. Interpretation of findings highlighted the importance of intervention dosage, adherence, and supervision for optimal effectiveness. Despite the limitations of the included studies, this review provides new and valuable insights for future research and clinical practice.
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".