Clinical effectiveness and micro-perfusion alteration of Jingui external lotion in patients with knee osteoarthritis: study protocol for a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis is a major cause of disability in the aging population. Based on pathological, magnetic resonance imaging (MRI) and arthroscopy studies, progressive osteoarthritis involves all tissues of the joint and includes bone marrow lesions, synovial proliferation, fat pad inflammation, and high subchondral bone turnover. Recent research suggests that abnormal perfusion in bone marrow lesions, fat pads, and subchondral bone is associated with pain in knee osteoarthritis, and that dynamic contrast-enhanced MRI is a promising method for studying micro-perfusion alteration in knee osteoarthritis. Traditional Chinese Medicine approaches have been employed for thousands of years to relieve knee osteoarthritis pain. Among herbal medicines, the Jingui external lotion is the preferred and most commonly used method in China to reduce pain in patients with knee osteoarthritis; however, there is a lack of validated evidence for its effectiveness. The purpose of this study is to explore the effectiveness of Jingui external lotion for the management of painful knee osteoarthritis in a short-term study. In addition, we will assess micro-perfusion alteration in the patellar fat pad as well as the femur and tibia subchondral bone via dynamic contrast-enhanced MRI. METHODS/DESIGN: This trial is a randomized, controlled study. A total of 168 patients will be randomized into the following two groups: 1) the Jingui external lotion group (treatment group); and 2) the placebo lotion group (control group). In both groups, lotion fumigation and external washing of the patients' knees will be administered twice a day for 14 consecutive days. Follow-up will be at regular intervals during a 4-week period with a visual analog scale to assess pain, and additional characterization with the Western Ontario and McMaster Universities Index score; rescue medication will be recorded as the extent and time pattern. In addition, micro-perfusion alteration in the patellar fat pad, femur and tibia subchondral bone will be assessed via dynamic contrast-enhanced MRI. DISCUSSION: This study will provide clinical evidence of the efficacy of Jingui external lotion in treating knee osteoarthritis, and it will be the first randomized controlled trial to investigate micro-perfusion alteration of knee osteoarthritis with Traditional Chinese Medicine external lotion via dynamic contrast-enhanced MRI. TRIAL REGISTRATION: ClinicalTrials.gov identifier: ChiCTR-TRC-14004727 ; 31 May 2014.
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How this classification was reachedexpand
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 | 0.010 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".