Randomized controlled study of the antinociceptive effect of ultrasound on trigger point sensitivity: novel applications in myofascial therapy?
Bibliographic record
Abstract
OBJECTIVE: To investigate whether therapeutic ultrasound modulates the pain sensitivity of myofascial trigger points. DESIGN: Repeated measures, single-blinded randomized controlled trial of ultrasound treatment of trigger points. SETTING: Outpatient injury rehabilitation clinic. SUBJECTS: Forty-four patients (22 males, 22 females) with trigger points identified within the trapezius muscle. INTERVENTIONS: Five-minute therapeutic intensity of ultrasound versus 5-min low-intensity application of ultrasound to a trapezius myofascial trigger point locus. MAIN MEASURES: Pain pressure threshold readings were measured at the trapezius trigger point site before and after exposure to the ultrasound intervention. RESULTS: Pain pressure threshold scores increased an average of 44.4 (14.2)% after therapeutic exposure to ultrasound (pre-ultrasound test 35.4 (8.5) N, post-ultrasound test 51.1 (12.8) N). No significant difference in pain pressure threshold scores was observed with low-intensity ultrasound exposures (pre-ultrasound 36.1 (6.1) N, post-ultrasound 36.6 (4.8) N). CONCLUSIONS: Therapeutic exposures to ultrasound reduce short-term trigger point sensitivity. Ultrasound may be a useful clinical tool for the treatment and management of trigger points and myofascial pain syndromes.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 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".