Avaliação do efeito da manipulação fascial no tratamento da dispareunia feminina: série de casos
Bibliographic record
Abstract
INTRODUCTION: Pelvic pain affects approximately 30% of sexually active women, and among them, around 50% report experiencing dyspareunia. The goal of treatment is to monitor the progression of pain symptoms of musculoskeletal and myofascial origin, aiming to improve the patients' quality of life. OBJECTIVE: The aim of this study is to describe the effects of fascial manipulation according to the Stecco Method, combined with perineal massage, on pain intensity, sexual function, psychological risk levels for stress, depression, and anxiety, as well as on pain characteristics and pelvic floor muscle strength. METHOD: The sample consisted of seven women participating in a postpartum recovery program, all diagnosed with dyspareunia and undergoing a three-month intervention. The assessment instruments used were the Numeric Pain Rating Scale (NPRS), the McGill Pain Questionnaire, the FSFI-19, the DASS-21 scale, and the Modified Oxford Scale. Participants were evaluated at three distinct time points: M0 (before the intervention – at the time of diagnosis), M1 (one month after the start of the intervention), and M2 (three months after the start of the intervention). A descriptive statistical analysis was conducted using the absolute and relative frequencies of the data collected. To verify the normality of the data, the Shapiro-Wilk test was used. RESULTS: The results reported reductions in pain between time points M0–M1 and M0–M2. In the McGill Pain Questionnaire, a gradual decrease in pain was observed from M0 to M2. In the FSFI-19, the "pain" item showed improvement between M0 and M1, while the "satisfaction" item showed a decrease between M0 and M2. The "total" score of the scale showed a slight increase over the three time points. In the DASS-21 scale, the most notable reduction was in the "stress" item, decreasing from 8.3 at M0 to 5.0 at M2. Finally, in the Modified Oxford Scale, 71.4% of the participants presented low-intensity contractions at M0. At M1 and M2, there was a predominance of more satisfactory contraction intensity, with 42.9% of participants reaching grades 3 and 28.6% grade 4 at M1, and 42.9% reaching grade 3 and another 42.9% grade 4 at M2. CONCLUSION: The combination of fascial manipulation and perineal massage applied in the treatment of dyspareunia resulted in a decrease in pain intensity and characteristics, reduced stress levels, increased pelvic floor muscle strength, and improvements in the "satisfaction" and "pain" items, as well as a reduction in the total scale score.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".