Effectiveness of Hypopressive Exercises in Women with Pelvic Floor Dysfunction: A Randomised Controlled Trial
Bibliographic record
Abstract
Hypopressive exercises have emerged as a conservative treatment option for pelvic floor dysfunction (PFD). The aim of this study was to compare the effects of an eight-week hypopressive exercise program to those of an individualized pelvic floor muscle (PFM) training (PFMT) program, and to a combination of both immediately after treatment and at follow-up assessments at 3, 6 and 12 months later. The study was a prospective, single-centre, assessor-blinded, randomised controlled trial. Ninety-four women with PFD were assigned to PFMT (n = 32), hypopressive exercises (n = 31) or both (n = 31). All programs included the same educational component, and instruction about lifestyle interventions and the knack manoeuvre. Primary outcomes were the Pelvic Floor Distress Inventory Short Form (PFDI-20); the Pelvic Floor Impact Questionnaire Short Form (PFIQ-7); PFM strength (manometry and dynamometry) and pelvic floor basal tone (dynamometry). There were no statistically significant differences between groups at baseline, nor after the intervention. Overall, women reduced their symptoms (24.41–30.5 on the PFDI-20); improved their quality of life (14.78–21.49 on the PFIQ-7), improved their PFM strength (8.61–9.32 cmH2O on manometry; 106.2–247.7 g on dynamometry), and increased their pelvic floor basal tone (1.8–22.9 g on dynamometry). These data suggest that individual PFMT, hypopressive exercises and a combination of both interventions significantly reduce PFD symptoms, enhance quality of life, and improve PFM strength and basal tone in women with PFD, both in the short and longer term.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".