Changes in Levator Ani Anatomical Configuration Following Physiotherapy in Women With Stress Urinary Incontinence
Bibliographic record
Abstract
PURPOSE: We quantified the effect of pelvic floor muscle training on the anatomical configuration of the levator ani using magnetic resonance imaging. MATERIALS AND METHODS: Five female participants with stress urinary incontinence underwent magnetic resonance imaging before and after participating in a pelvic floor muscle physiotherapy program. Axial T1-weighted images of the levator ani were taken with the participant in a supine position. Source images were then manually segmented and surface modeling was applied to build a 3-dimensional model of the levator ani. Models were then measured to determine the levator ani surface area as well as the encircled volume at rest and during voluntary contraction. The percentage of levator ani retraction and symphysis pubis movement during voluntary contraction before and after physiotherapy were also measured. RESULTS: After physiotherapy the levator ani surface area at rest was significantly smaller than before physiotherapy, decreasing from 677.11 +/- 45.00 to 620.48 +/- 36.14 mm(2) (p = 0.04). The relative reduction in volume encircled by the levator ani during contraction increased significantly from -11.66 +/- 7.42 to -26.02 +/- 13.52 mm(3) (p = 0.04). Levator ani surface retraction during a voluntary contraction increased significantly from 65.61% +/- 17.07% to 81.70% +/- 16.30% (p = 0.02). Symphysis pubis movement during pelvic floor muscle contraction decreased from 1.45 +/- 1.32 to 0.44 +/- 0.61 mm (p = 0.05). CONCLUSIONS: Findings from this preliminary study indicate that pelvic floor muscle training results in anatomical changes in the levator ani and reduction of pubic movement. These results provide insight into the possible anatomical mechanisms through which physiotherapy enables the pelvic floor muscle to minimize urine leakage.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".