Effects of Traditional Chinese Medicine Rehabilitation Program on Knee Osteoarthritis in Aging Population: A Multicenter Randomized Controlled Trial
Bibliographic record
Abstract
INTRODUCTION: Knee osteoarthritis (KOA) is a prevalent degenerative disease that causes pain and disability in older individuals. This study aimed to examine the effects of the traditional Chinese medicine (TCM) rehabilitation program for aging populations with KOA. METHODS: A total of 101 participants with KOA were randomly assigned to either a TCM rehabilitation group (n = 49) or a conventional physical therapy group (n = 52) with a 1:1 allocation ratio for this randomized controlled trial. Participants in the TCM group received acupuncture, massage, and South Shaolin exercise training for 4 weeks, with three sessions per week lasting 50 min per session. Participants in the control group received conventional physical therapies of equal duration and frequency. RESULTS: Outcomes were Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Visual Analogue Scale (VAS), Knee Outcome Survey Activities of Daily Living Scale, the 6-min Walking test (6MWT), the Time Up and Go (TUG) Test, and the Stair-climbing Test. Significant improvements were observed in the WOMAC, VAS, 6MWT, TUG, and Stair-climbing test after a 4-week TCM rehabilitation intervention (p < 0.05). The WOMAC and VAS were found to be decreased at the 4-week follow-up assessments compared to baseline scores (p < 0.05). Only the TUG test showed significant changes in the control group compared with the TCM rehabilitation group (p = 0.043) after 4 weeks post-intervention. CONCLUSION: The TCM rehabilitation program improved knee function and reduced pain intensity in aging populations with knee osteoarthritis. Well-designed randomized controlled trials with long-term follow-up assessments are needed to draw more definitive conclusions. Trial registration Chinese Clinical Trial Register ChiCTR2000033351, date of registration: May 29, 2020.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 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 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".