Assessing the comparative effectiveness of Tai Chi versus physical therapy for knee osteoarthritis: design and rationale for a randomized trial
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (OA) causes pain and long-term disability with annual healthcare costs exceeding $185 billion in the United States. Few medical remedies effectively influence the course of the disease. Finding effective treatments to maintain function and quality of life in patients with knee OA is one of the national priorities identified by the Institute of Medicine. We are currently conducting the first comparative effectiveness and cost-effectiveness randomized trial of Tai Chi versus a physical-therapy regimen in a sample of patients with symptomatic and radiographically confirmed knee OA. This article describes the design and conduct of this trial. METHODS/DESIGN: A single-center, 52-week, comparative effectiveness randomized controlled trial of Tai Chi versus a standardized physical-therapy regimen is being conducted at an urban tertiary medical center in Boston, Massachusetts. The study population consists of adults ≥ 40 years of age with symptomatic and radiographic knee OA (American College of Rheumatology criteria). Participants are randomly allocated to either 12 weeks of Tai Chi (2x/week) or Physical Therapy (2x/week for 6 weeks, followed by 6 weeks of rigorously monitored home exercise). The primary outcome measure is pain (Western Ontario and McMaster Universities WOMAC) subscale at 12 weeks. Secondary outcomes include WOMAC stkiffness and function domain scores, lower extremity strength and power, functional balance, physical performance tests, psychological and psychosocial functioning, durability effects, health related quality of life, and healthcare utilization at 12, 24 and 52 weeks. DISCUSSION: This study will be the first randomized comparative-effectiveness and cost-effectiveness trial of Tai Chi versus Physical Therapy in a large symptomatic knee OA population with long-term follow up. We present here a robust and well-designed randomized comparative-effectiveness trial that also explores multiple outcomes to elucidate the potential mechanisms of mind-body effect for a major disabling disease with substantial health burdens and economic costs. Results of this study are expected to have important public health implications for the large and growing population with knee OA. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01258985.
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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 | 0.182 | 0.172 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.010 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.013 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".