Effectiveness of Tuina manipulation in patients with knee osteoarthritis: study protocol for a randomized controlled trial
Bibliographic record
Abstract
Abstract Background: Knee osteoarthritis (KOA) is a common disabling musculoskeletal disorder. Previous studies showed that Tuina manipulation and health care education were effective treatments for patients with KOA. However, there is no evidence to support the use of one intervention over the other. The purpose of this study is to evaluate the effectiveness of Tuina manipulation and health care education for the management of pain and dysfunction in patients with KOA.Methods/Design: This study is a single-centre, two-arm, open-label randomized controlled trial (RCT). A total of 170 eligible KOA patients will be randomly assigned to the Tuina manipulation group or the health education group in a 1:1 ratio. Patients in the Tuina manipulation group will receive a 30-minute 2-step treatment plan, including pain point assessment and manual therapy, which will be performed 12 times in 4 weeks. The health education group will receive 45 minutes of lecture and discussion three times a week for four weeks. The primary outcome is the Knee Injury and Osteoarthritis Outcome Score (KOOS). Secondary outcomes include the McGill Pain Questionnaire (MPQ) and 36-item Short-Form Health Survey (SF-36). The results of this study will help clarify the value of Tuina manipulation and health education as treatments for KOA and will highlight any differences in treatment outcomes.Discussion: The design and methodology of the trial is rigorous and allows the collection of valuable data to assess the efficacy of a specific Tuina regimen for the treatment of KOA. Therefore, the trial will provide a solid foundation for future clinical research on KOA and Tuina therapy.Trial registration: This trial was registered with the Chinese Clinical Trial Registry on 24 February 2020 (ChiCTR2000030154), http://www.chictr.org.cn/index.aspx
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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 | 0.040 | 0.045 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.081 | 0.012 |
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".