Pelvic floor muscle functioning in women with vulvar vestibulitis syndrome
Bibliographic record
Abstract
Vaginal sEMG biofeedback and pelvic floor physical therapists' manual techniques are being increasingly included in the treatment of vulvar vestibulitis syndrome (VVS). Successful treatment outcomes have generated hypotheses concerning the role of pelvic floor pathology in the etiology of VVS. However, no data on pelvic floor functioning in women with VVS compared to controls are available. Twenty-nine women with VVS were matched to 29 women with no pain with intercourse. Two independent, structured pelvic floor examinations were carried out by physical therapists blind to the diagnostic status of the participants. Results indicated that therapists reached almost perfect agreement in their diagnosis of pelvic floor pathology. A series of significant correlations demonstrated the reliability of assessment results across muscle palpation sites. Women with VVS demonstrated significantly more vaginal hypertonicity, lack of vaginal muscle strength, and restriction of the vaginal opening, compared to women with no pain with intercourse. Anal palpation could not confirm generalized hypertonicity of the pelvic floor. We suggest that pelvic floor pathology in women with VVS is reactive in nature and elicited with palpations that result in VVS-type pain. Treatment interventions need to recognize the critical importance of addressing the conditioned, protective muscle guarding response in women with VVS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".