Effect of Electro-acupuncture (EA) and Manual Acupuncture (MA) on Markers of Inflammation in knee osteoarthritis
Bibliographic record
Abstract
<title>Abstract</title> Background Inflammation plays a significant role in the pathogenesis of knee osteoarthritis (KOA). Although both Electro-acupuncture (EA) and Manual Acupuncture (MA) are known to influence systemic inflammation, little is known about the potential changes in inflammation as a working mechanism of EA and MA in KOA.Methods Data from the Acupuncture for Knee Osteoarthritis Trial (ATKOA) were used. Serum concentrations of inflammatory factors (tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), IL-6, IL-8, IL-18, IL-4, IL-10,IL-13,IL-15, IL-17, monocyte chemotactic protein-1 (MCP-1), CCchemokine ligand 5 (CCL5), and cartilage degradation biomarkers (matrix metalloproteinase-1 MMP-1, MMP-3, MMP-13 and cartilage oligomeric matrix protein COMP) were measured at baseline and after 8 weeks of treatment. Clinical outcomes were valid and reliable self-reported pain and function measures for osteoarthritis using the Western Ontario and McMasters osteoarthritis index questionnaire (WOMAC) and Visual Analogue Scale (VAS) at baseline and post-treatment.Results Both 8-weeks EA and MA significantly reduced pro-inflammatory cytokines (TNFα, IL-1β) and cartilage degradation biomarkers (MMP-3, MMP-13), significantly increased the anti-inflammatory cytokine IL-13 compared with pre-treatment (p<0.05). Further, the reduction of TNF-α were more significant in EA when compared to MA (p=0.046). While, there was no significant difference between groups in cytokines IL-1β (p=0.102), MMP-3(p=0.113), MMP-13(p=0.623) or IL-13(p=0.935). Moreover, in both EA and MA the effect of acupuncture on the VAS and WOMAC function scale after 8 weeks is clinically important, although no significant differences were found between groups.Conclusions 8 weeks of both EA and MA seem to provide improvement in pain relief and function among individuals with mild to moderate knee OA. This benefit is partly mediated by changes of major inflammatory factors TNF-α, IL-1β and IL-13.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".