623 THIELE MASSAGE AS POSSIBLE THERAPEUTIC INTERVENTION FOR WOMEN WITH CHRONIC PELVIC PAIN CAUSED BY TENDERNESS OF THE LEVATOR ANI MUSCLE
Bibliographic record
Abstract
Aim: To investigated the association between tenderness of pelvic muscles and dyspareunia in women with CPP.Methods: Case-control study performed at tertiary care University Hospital and approved by local Research Ethics Committee.Fortyeight healthy female volunteers (control group) and 108 women with CPP (CPP group: 53 subjects with dyspareunia and 55 subjects without dyspareunia) were included.The tenderness of pelvic muscle (TPM) was scored bilaterally according to subject reactions: 0 no pain, 1 painful discomfort, 2 intense pain; total score: 6.The intensity of dyspareunia was classified according to the limitation of sexual activity.Intensity of pain was evaluated by visual analogue scale (VAS) and McGill Pain Index (MPI).All participants were also submitted to the Beck Depression Index (BDI).Results: 89.0% of CPP group showed tenderness in levator ani, 51.0% in piriformis, and 31.7% in internal obturator muscles (P < 0.01).The TPM score median was 0 (0-4) for the control group and 3 (0-6) for the CPP group (P < 0.001).In the CPP group, patients with dyspareunia showed higher frequency of tenderness when compared to those without dyspareunia (75.5% and 42.0% respectively, P < 0.01), higher duration of pain (73.7±72 and 49±60 months respectively, P < 0.05), higher BDI scores (22 and 13 respectively, P < 0.01).Neither VAS nor MPI were distinct between groups. Conclusion:The results suggest that tenderness of pelvic muscles is highly associated with dyspareunia in women with CPP.Causal association needs to be investigated.
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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 | 0.000 |
| 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) | 0.003 | 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".