Heat and Acupuncture to Manage Osteoarthritis of the Knee (HARMOKnee): Protocol for an Effectiveness-Implementation Hybrid Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Knee osteoarthritis (KOA) is one of most prevalent and fastest-growing causes of pain, impaired mobility, and poor quality of life in the rapidly aging population worldwide. There is a lack of high-quality evidence on the efficacy of traditional Chinese medicine (TCM), particularly acupuncture, and a lack of KOA practice guidelines that are tailored to unique population demographics and tropical climates. OBJECTIVE: Our HARMOKnee (Heat and Acupuncture to Manage Osteoarthritis of the Knee) trial aims to address these gaps by evaluating the short- and medium-term clinical and cost-effectiveness of acupuncture with heat therapy in addition to standard care, compared to standard care alone. Through a robust process and economic evaluation, we aim to inform evidence-based practice for patients with KOA to facilitate the large-scale implementation of a comprehensive and holistic model of care that harmonizes elements of Western medicine and TCM. We hypothesize that acupuncture with heat therapy as an adjunct to standard care is clinically more effective than standard care alone. METHODS: A multicenter, pragmatic, parallel-arm, single-blinded, effectiveness-implementation hybrid randomized controlled trial will be conducted. We intend to recruit 100 patients with KOA randomized to either the control arm (standard care only) or intervention arm (acupuncture with heat therapy, in addition to standard care). The inclusion criteria are being a community ambulator and having primary KOA, excluding patients with secondary arthritis or previous knee replacements. The primary outcome measure is the Knee Osteoarthritis Outcome Score at 6 weeks. Secondary outcome measures include psychological, physical, quality of life, satisfaction, and global outcome measures at 6, 12, and 26 weeks. A mixed method approach through an embedded process evaluation will facilitate large-scale implementation. An economic evaluation will be performed to assess financial sustainability. RESULTS: Patient enrollment has been ongoing since August 2022. The recruitment process is anticipated to conclude by July 2024, and the findings will be analyzed and publicized as they are obtained. As of November 6, 2023, our patient enrollment stands at 65 individuals. CONCLUSIONS: The findings of our HARMOKnee study will contribute substantial evidence to the current body of literature regarding the effectiveness of acupuncture treatment for KOA. Additionally, we aim to facilitate the creation of standardized national guidelines for evidence-based practice that are specifically tailored to our unique population demographics. Furthermore, we seek to promote the adoption and integration of acupuncture and heat therapy into existing treatment models. TRIAL REGISTRATION: ClinicalTrials.gov NCT05507619; https://clinicaltrials.gov/study/NCT05507619. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/54352.
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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 | 0.046 | 0.045 |
| Meta-epidemiology (narrow) | 0.008 | 0.003 |
| Meta-epidemiology (broad) | 0.013 | 0.008 |
| 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 | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.070 | 0.011 |
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".