Tai Chi Qigong for the quality of life of patients with knee osteoarthritis: a pilot, randomized, waiting list controlled trial
Bibliographic record
Abstract
OBJECTIVE: To evaluate the effects of Tai Chi Qigong training on the quality of life and physical function of patients with osteoarthritis of the knee. DESIGN: A preliminary, single-blind, randomized controlled trial. SETTING: General community, performed at Hwaseong City Health Center. PARTICIPANTS: Forty-four elderly subjects (mean age, 69.1 +/- 5.4 years) with knee osteoarthritis. INTERVENTION: The patients were randomized (2:1) to: (1) an eight-week Tai Chi Qigong training programme or (2) a waiting list control group. The programme involved eight weeks of group Tai Chi Qigong sessions, with 60 minutes per session twice a week. MAIN OUTCOME MEASURES: The primary outcome was quality of life measured with the Short Form 36 (SF-36) at baseline and week 8. Secondary outcomes included the Western Ontario and McMaster University Osteoarthritis Index (WOMAC) and 6-m walking time. RESULTS: The training group had statistically significant improvements in the quality of life (changes of SF-36, Qigong versus control: 21.6 +/- 16.8 versus 9.8 +/- 13.6, P < 0.05) and 6-m walking test (change in walking time, Qigong versus control: -1.6 +/- 1.7 versus -0.2 +/- 0.8 s, P < 0.01). The WOMAC scores in the training group were markedly improved, although the differences were not statistically significant. CONCLUSIONS: Tai Chi Qigong training appears to have beneficial effects in terms of the quality of life and physical functioning of elderly subjects with knee osteoarthritis. However, more rigorous trials are needed to confirm the efficacy of this training for patients with osteoarthritis of the knee.
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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 | 0.002 |
| 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 | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".