Clinical relevance of Tai Chi on pain and physical function in adults with knee osteoarthritis: An ancillary meta-analysis of randomized controlled trials
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Bibliographic record
Abstract
The clinical relevance of Tai Chi on pain, stiffness, and physical function in adults with knee osteoarthritis (KOA) has not been established. Therefore, the purpose of the current study was to address this gap. Eight randomized controlled trials from a recent meta-analysis representing 407 participants (216 Tai Chi, 191 control) in adults ≥18 years of age with KOA and included the assessment of pain, stiffness, and physical function using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) were assessed. The inverse variance heterogeneity model (IVhet) was first used to pool standardized mean difference effect sizes (ES) for each outcome. Clinical relevance, i.e., number-needed-to treat (NNT) ≤10 and relative risk reduction (RRR) ≥25% was calculated across assumed controlled risks (ACR) ranging from 0.01 to 0.99. Statistically significant improvements were found for pain (ES, −0.75, 95% CI, −0.99, −0.51; Q = 8.9, p = 0.26; I 2 = 21%), stiffness (ES, −0.70, 95% CI, −0.95, −0.46; Q = 9.6, p = 0.21; I 2 = 27%), and physical function (ES, −0.91, 95% CI, −1.12, −0.70; Q = 7.2, p = 0.40; I 2 = 3%). The intersection of results for a NNT ≤10 and RRR ≥25% yielded high evidence and clinically relevant improvements across a wide range of ACR for pain (0.15 to 0.88), stiffness (0.15 to 0.87), and physical function (0.13 to 0.97). These findings suggest that Tai Chi results in statistically significant as well as clinically important improvements in pain, stiffness, and physical function across a wide range of ACR in adults with KOA.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.026 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.024 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it