Five-Step Knee Adjustment Manipulation Based on the ‘Muscle and Bone Balance’ Principle for Treating Knee Osteoarthritis: Study Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
Background: Knee osteoarthritis (KOA) is the leading cause of knee joint dysfunction. Manual therapy (MT) can decrease patients' levels of pain and improve their functionality. But most traditional methods focus solely on the knee joint or its surrounding tissues, neglecting the impact of the waist, hip, ankle, and lower limb alignment on KOA. The objective is to clarify the effects of the five-step knee adjustment manipulation on KOA, evaluate its efficacy, and explore new treatment approaches for manual KOA therapy. Methods: (1) 45 healthy volunteers will be recruited to observe the differences in lower limb alignment, quadriceps cross-sectional area, knee joint range of motion (ROM), and gait between healthy individuals and KOA participants. (2) Conduct a multi-center, randomized, single-blind, controlled clinical trial. 120 eligible participants will be included and randomly assigned to a five-step knee adjustment manipulation (FS) group or a sham manipulation (SM) group with a ratio of 1:1. Each group will receive 2 sessions per week applied for 4 weeks and then be followed up for another 8 weeks. The primary outcome is visual analogue scale (VAS). The secondary outcomes include Western Ontario and McMaster Universities Arthritis Index (WOMAC) score, ROM, quadriceps cross-sectional area (CSA), gait analysis, and so on. Conclusion: This technique emphasizes a holistic approach, addressing the lumbar spine, hip, knee, and ankle joints, as well as related muscle groups, to correct lower limb alignment and restore muscle and bone balance. We think it will contribute to providing a promising alternative intervention for middle-aged and older adults with KOA. Trial Registration: The study was approved by the Ethics Committee of Shanghai Municipal Hospital of Traditional Chinese Medicine (Ethics No.: 2024SHL-KY-70-01). Registered in Chinese Clinical Trial Registry (No. ChiCTR2400085536).
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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 | 0.020 | 0.020 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.051 | 0.008 |
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".