The Effect of Pelvic Floor Muscle Interventions on Pelvic Floor Dysfunction After Gynecological Cancer Treatment: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: The aim of this systematic review was to identify, evaluate, and synthesize the evidence from studies that have investigated the effect of nonsurgical, nonpharmacological, pelvic floor muscle interventions on any type of pelvic floor dysfunction or health-related quality of life in patients after any type of treatment for gynecological cancer. METHODS: Six electronic databases (Cochrane Library 2018, CINAHL 1982-2018, MEDLINE 1950-2018, EMBASE 1980-2018, PsycINFO 1806-2018, and EMCARE 1995-2018) were systematically searched in June 2018. Reference lists of identified articles were hand searched. Randomized controlled trials (RCTs), cohort studies, and case series were included if they investigated the effects of conservative treatments, including pelvic floor muscle training or dilator training, on bladder, bowel, or sexual function in patients who had received treatment for gynecological cancer. Risk of bias was assessed using the Physiotherapy Evidence Database scale for RCTs and the Newcastle-Ottawa scale for cohort studies. RESULTS: Five RCTs and 2 retrospective cohort studies were included (n = 886). The results provided moderate-level evidence that pelvic floor muscle training with counseling and yoga or core exercises were beneficial for sexual function (standardized mean difference = -0.96, 95% CI = -1.22 to -0.70, I2 = 0%) and health-related quality of life (standardized mean difference = 0.63, 95% CI = 0.38 to 0.88, I2 = 0%) in survivors of cervical cancer and very low-level evidence that dilator therapy reduced vaginal complications in survivors of cervical and uterine cancer (odds ratio = 0.37, 95% CI = 0.17 to 0.80, I2 = 54%). There were insufficient data for meta-analysis of bladder or bowel function. CONCLUSION: Conservative pelvic floor muscle interventions may be beneficial for improving sexual function and health-related quality of life in survivors of gynecological cancer. Given the levels of evidence reported in this review, further high-quality studies are needed, especially to investigate effects on bladder and bowel function. IMPACT: This review provides moderate-level evidence for the role of pelvic floor rehabilitation to improve health outcomes in the gynecological cancer survivorship journey. Clinicians and health service providers should consider how to provide cancer survivors the opportunity to participate in supervised pelvic floor rehabilitation programs.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| 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 | 0.001 |
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 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".