Osteopathic Medicine in Four Chronic Musculoskeletal Pain Diseases: An Observational Trial with Follow-Up
Bibliographic record
Abstract
BACKGROUND AND AIM: Patients with chronic musculoskeletal pain diseases (CMPDs) often use osteopathic medicine (OM), although the changes in patients with pain diseases are still insufficiently investigated. This study aimed to observe changes along and after OM in addition to routine care on pain, functioning, and quality of life in patients with four CMPDs. METHODS: In this observational trial with follow-up, patients suffering from chronic neck pain (CNP, n = 10), chronic low back pain (CLBP, n = 10), chronic shoulder pain (CSP, n = 10), or chronic knee pain (CKP, n = 10) received up to six OM sessions in addition to routine care. RESULTS: A total of 40 patients (73% female, mean age 47.7 ± 8.3 years, mean pain intensity 59.4 ± 12.5 mm, measured by a visual analog scale [VAS] 0-100 mm) were included. After 26 weeks, there was an improvement in the VAS pain score in the whole population (mean difference to baseline -33.1 mm [95% CI -40.5 to -25.7]), as well in the patients with the four diseases: CNP (-33.7 mm [-54.7 to -12.6]), CLBP (-28.2 mm [-47.9 to -8.4]), CSP (-32.4 [-46.8 to -18.0]), and CKP (-38.1 mm [-49.1 to -27.0]). Regarding disease-specific outcomes, we found improvements in CNP, as measured by the neck disability index (scale 0-50; mean difference -3.6 [-9.0 to 1.9]), CLBP, as measured by the low back pain rating scale (scale 0-60; -3.4 [-12.5 to 5.7]), CSP, as measured by the disabilities of the arm, shoulder and hand score (scale 0-100; -13.4 [-23.1 to -3.7]), and CKP, as measured by the Western Ontario and McMaster Universities Osteoarthritis Index (scale 0-96; -13.0 [-23.5 to -2.5]). These improvements persisted through week 52. No adverse events were observed. CONCLUSION: The study observed beneficial changes along and after the OM treatment in addition to routine care in patients with four different CMPDs. High-quality, multicenter randomized controlled trials are strongly needed to compare the effectiveness of OM and standard care interventions in treating CMPDs in the future. We have provided sufficient data for sample size calculations for these trials.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".