Liberação miofascial instrumentalizada lombar e abdominal reduz dismenorreia primaria
Bibliographic record
Abstract
Background: Primary dysmenorrhea is a prevalent condition that impacts the ADLs and work activities of billions of women, and new treatment techniques are needed. Aims: To test a protocol composed of three manual techniques used on primary dysmenorrhea. Method: The pain of 8 patients was assessed before and after the intervention using McGill, VAS and PSST. The intervention consisted of abdominal, sacral and lumbar release maneuvers with a “square” instrument of the IASTM® myofascial release method, one session per week for four weeks. Results: All women showed a significant reduction (average of -80%) in pain, with around a third being cured of pain. The least notable result was in the patient with a BMI compatible with obesity. Conclusion: The proposed instrumented myofascial release maneuvers are efficient in relieving primary dysmenorrhea and other PMS symptoms, but special attention should be focused on obese women.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".