Osteopathic manipulative treatment improves function and relieves pain in knee osteoarthritis: A single-blind, randomized-controlled trial
Bibliographic record
Abstract
OBJECTIVES: In this study, we aimed to compare the efficacy of osteopathic manipulative treatment (OMT) to exercise treatment in the knee osteoarthritis (OA). PATIENTS AND METHODS: A total of 100 patients (9 males, 76 females; mean age 54.8±8.5 years; range, 40 to 70 years) with Stage II-III bilateral knee OA enrolled to the study and randomized into two groups between January 2015 and June 2015. Group 1 performed exercise and received OMT and Group 2 performed exercise alone. We assessed the clinical parameters with Western Ontario MacMaster Questionnaire (WOMAC) pain score, WOMAC joint stiffness score, WOMAC physical function score, Visual Analog Scale (VAS) and 50-m walking time. All patients were assessed at the beginning of the study, just after the treatment, and four weeks after the treatment. RESULTS: There was no significant difference between groups in terms of physical examination and clinical assessment parameters before treatment. Functional improvement (p<0.05) and pain relief (p<0.05) were significantly higher in the exercise + OMT group. CONCLUSION: Based on our study results, OMT is a particular treatment used by osteopathic physicians to complement conventional treatment of OA of the knee. In addition to the conservative treatment, OMT can be used.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| 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 | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".