How does the pelvic floor respond to modulations in trunk pressure induced by a variety of voicing tasks? A cross‐sectional, observational study
Bibliographic record
Abstract
The pelvic floor responds to changes in trunk pressure, elevating during low-pressure exhale and descending during high-pressure exhale. Voicing occurs during exhalation, spanning low-to-high trunk-pressure, yet it is unknown how voicing affects the pelvic floor. The aim of this study was to quantify pelvic floor response to voicing and identify if there are differences for women with stress urinary incontinence. We hypothesized that shouting would cause pelvic floor descent, with greater magnitude for incontinent women. Sixty women (38 incontinent, 22 continent) performed four voicing tasks (counting to "4" in speaking/shouting/low-pitch/high-pitch voice) while transperineal ultrasound measured changes in pelvic floor morphology. ANOVA compared variance of responses to voicing and t-tests compared groups. Bladder neck height shortened, levator plate length increased and levator plate angle decreased more during shouting compared to speaking; consistent with pelvic floor straining. There were no differences for high versus low pitch-voicing and small group differences based on continence status. Voicing causes pelvic floor muscles to strain, with greater strain during shouting. Changing vocal pitch does not affect pelvic floor morphology and incontinent women had slight differences from continent women. Voicing may be a safe way to lengthen the pelvic floor without provoking incontinence.
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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 | 0.001 |
| 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".