Prevalence of pelvic musculoskeletal disorders in a female chronic pelvic pain clinic.
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence of 2 musculoskeletal pain disorders among women presenting to a referral chronic pelvic pain clinic. STUDY DESIGN: This was a retrospective, cross-sectional study of 987 women (aged 14-79) presenting for evaluation from 1993 to 2000 at a university-based gynecologic chronic pelvic pain clinic. RESULTS: At the initial visit, all women completed standardized interviews and underwent a pelvic examination. Single-digit palpation of the levator ani and piriformis muscles was performed intravaginally. Among these women, 212 of 955 (22%) had tenderness of the levator ani muscles, while 128 of 943 (14%) had tenderness of the piriformis muscle (pain score > 3 of 10 on a visual analogue scale). Both levator ani tenderness and piriformis tenderness were associated with a higher total number of pain sites, previous surgery for pelvic pain, Beck Depression Inventory score, McGill Pain Inventory score and pain worsened with bowel movements (p < 0.05). CONCLUSION: Piriformis and levator ani pain are present in a significant proportion of female chronic pelvic pain patients. Further research into the natural course, diagnosis and treatment of pelvic musculoskeletal pain is needed to determine its true contribution to chronic pain.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".