Effect of Tai Chi exercise on lower limb function and balance ability in patients with knee osteoarthritis: A protocol of a randomized controlled trial
Bibliographic record
Abstract
Abstract Background: Knee Osteoarthritis (KOA) is a chronic degenerative joint disease commonly occurring in middle-aged and elderly people. The main clinical manifestations are joint pain, limited activity, and decreased muscle strength resulting in decreased motor control ability. Exercise therapy is an effective method to enhance muscle strength of lower limbs, while China's traditional skill Tai Chi is a combination of activity and inertia, internal and external exercise therapy. In recent years, scholars at home and abroad have found that regular Tai Chi can effectively improve patients' lower limb function and balance ability. The purpose of this study is to explore the effects of Tai Chi on lower limb function and balance ability in patients with knee osteoarthritis. Methods: This is a prospective randomized controlled clinical trial. 146 cases of knee osteoarthritis patients will be randomly divided into experimental group and control group according to 1:1 ratio, 73 cases in each group, the control group: sodium hyaluronate; experimental group: Tai Chi added on the basis of the control group. Both groups will receive standard treatment for 5 weeks and will be followed up for 3 months. Observation indicators include: the western Ontario and McMaster universities osteoarthritis index (WOMAC); hospital for special surgery knee score (HSS); balance stability index, liver and kidney function, adverse reaction rate, etc. SPSS 23.0 software will be used for data analysis. Discussion: This study will evaluate the effects of Tai Chi on lower limb function and balance ability of patients with knee osteoarthritis. The results of this trial will provide a clinical basis for the selection of exercise therapy for patients with knee osteoarthritis.
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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 | 0.027 | 0.020 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.021 | 0.002 |
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".