<p>Effect of Electro-Acupuncture (EA) and Manual Acupuncture (MA) on Markers of Inflammation in Knee Osteoarthritis</p>
Bibliographic record
Abstract
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), CC-chemokine 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 McMaster Universities Osteoarthritis Index (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 was 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. CONCLUSION: Eight 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. TRIAL REGISTRATION: Controlled-Trials.com Identifier: 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".