Electroacupuncture for Knee Osteoarthritis Based on Different Meridian Syndrome: A Randomized Controlled Pilot Trial
Bibliographic record
Abstract
Background We aimed to explore the feasibility of evaluating effectiveness and safety of electroacupuncture (EA) for the treatment of knee osteoarthritis (KOA) based on different meridian syndromes. Methods A multicenter randomized controlled trial was conducted in Beijing from January 2019 to December 2019. Sixty KOA participants were randomly allocated to either EA (n=30) or SA (n=30) groups. Participants in EA group were treated with semi-standardized on different meridian syndrome, including five obligatory acupoints and three adjunct acupoints. Eight non-acupoints that were separated from conventional acupoints or meridians were used for the SA group. Both groups received 24 sessions within eight weeks. The primary outcome was response rate, defined as a change of ≥50% from baseline in total scores of Western Ontario and McMaster Universities osteoarthritis index (WOMAC) at the end of treatment. Secondary outcomes included function, pain, stiffness, quality of life and acupuncture-related adverse events at four and eight weeks. Results Of 60 participants randomized, 56 (93.3%) completed the study. Response rates were 60% for the EA group and 30% for the SA group after eight weeks. Significant differences were observed in WOMAC pain and total scores within two groups ( P =0.026, P =0.043). Rates of adverse events were low and similarly distributed between groups. Conclusion EA intervention based on meridian differentiation in KOA was feasible and appeared safe, having a stronger impact on pain than SA. Future studies can be designed with larger sample size, adequately powered, randomization design and less biases. Trial registration number: NCT03274713.
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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 | 0.006 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".