Electroacupuncture versus Diclofenac in symptomatic treatment of Osteoarthritis of the knee: a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: The purpose of this study was to compare the efficacy of electroacupuncture (EA), diclofenac and their combination in symptomatic treatment of osteoarthritis (OA) of the knee. METHODS: This study was a randomized, single-blind, placebo controlled trial. The 193 out-patients with OA of the knee were randomized into four groups: placebo, diclofenac, EA and combined (diclofenac plus EA). Paracetamol tablets were prescribed as a rescue analgesic during the study. The patients were evaluated after a run-in period of one week (week 0) and again at the end of the study (week 4). The clinical assessments included the amount of paracetamol taken/week, visual analog scale (VAS), Western Ontario and McMaster Universities (WOMAC) OA Index, Lequesne's functional index, 50 feet-walk time, and the orthopedist's and patient's opinion of change. RESULTS: One hundred and eighty six patients completed the study. The improvement of symptoms (reduction in mean changes) in most outcome parameters was greatest in the EA group. The proportions of responders and patients with an overall opinion of "much better" were also greatest in the EA group. The improvement in VAS was significantly different between the EA and placebo group as well as the EA and diclofenac group. The improvement in Lequesne's functional index also differed significantly between the EA and placebo group. In addition, there was a significant improvement in WOMAC pain index between the combined and placebo group. CONCLUSION: EA is significantly more effective than placebo and diclofenac in the symptomatic treatment of OA of the knee in some circumstances. However, the combination of EA and diclofenac treatment was no more effective than EA treatment alone.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 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 | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".