Opposing needling in the treatment of knee osteoarthritis: an improved study protocol for a randomized controlled trial
Bibliographic record
Abstract
Background: Knee osteoarthritis (KOA) is a common degenerative joint disease that typically affects individuals over 40 years of age and is characterized by knee pain, stiffness, and functional impairment. Current treatment options, including basic care, pharmacologic therapy, and surgery, often provide limited pain relief or are associated with adverse effects, high costs, and surgical risks. Acupuncture has been conditionally recommended by international guidelines for KOA management and has shown beneficial effects in alleviating pain and improving function. However, most studies have investigated single modalities such as manual acupuncture or electroacupuncture, leaving opportunities to explore strategies that may further enhance therapeutic outcomes. Opposing needling, a classical technique involving contralateral point selection, has demonstrated superior analgesic effects in various chronic pain conditions and is increasingly applied in KOA. Methods: This two-center randomized controlled trial will enroll 108 eligible patients with KOA, who will be randomly assigned in a 1:1:1 ratio to opposing needling plus electroacupuncture, sham opposing needling plus electroacupuncture, or electroacupuncture alone. The 12-week study comprises an 8-week intervention period and a 4-week follow-up, with treatments administered three times per week. The primary outcome will be the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), while secondary outcomes will include WOMAC subscales, Visual Analog Scale, Numeric Rating Scale, Global Pain Scale, Lequesne Index, Knee Injury and Osteoarthritis Outcome Score, and Short Form-36 Health Survey. Discussion: The findings are expected to provide robust evidence regarding the efficacy and safety of opposing needling as an adjunctive therapy for KOA and to inform optimized treatment strategies. Clinical trial registration: itmctr.ccebtcm.org.cn, ITMCTR2025001291.
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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 | 0.036 | 0.040 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.005 |
| Insufficient payload (model declined to judge) | 0.051 | 0.006 |
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".