Efficacy of electro-acupuncture and manual acupuncture versus sham acupuncture for knee osteoarthritis: study protocol for a randomised controlled trial
Bibliographic record
Abstract
Abstract Background Knee osteoarthritis (KOA) is one of the most common musculoskeletal disorders. Although the available evidence for its efficacy is inconclusive, acupuncture is used as an alternative therapy for KOA. The aim of this trial is to determine the efficacy of electro-acupuncture and manual acupuncture versus sham acupuncture for KOA. Methods/design This is a study protocol for a randomised, three-arm, multicentre, clinical trial. A total of 480 patients with KOA will be randomly assigned to the electro-acupuncture group, the manual acupuncture group or the sham acupuncture group in a 1:1:1 ratio. All patients will receive 24 sessions over 8 weeks. Participants will complete the trial by visiting the research centre at week 26 for a follow-up assessment. The primary outcome is the success rate: the proportion of patients achieving a minimal clinically important improvement, which is defined as ≥2 points on the numerical rating scale and ≥6 points on the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) function score at week 8 compared with baseline. Secondary outcomes include the numerical rating scale, WOMAC score, global patient assessment and quality of life at weeks 4, 8, 16 and 26 after randomisation. Discussion This trial may provide high-quality evidence for the efficacy of acupuncture in the treatment of KOA. The results of this study will be published in peer-reviewed journals. Trial registration ClinicalTrials.gov, NCT03274713 . Registered on 20 November 2017.
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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 | 0.041 | 0.049 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.016 | 0.007 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.088 | 0.015 |
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".