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Record W4324325671 · doi:10.21203/rs.3.rs-2668875/v1

Decreased Levels of Synovial Fluid Biomarkers Correlate with the Severity and Function of Patients with Osteoarthritis Following Electroacupuncture

2023· preprint· en· W4324325671 on OpenAlexaboutno aff
Shiguo Yuan, Nan-Sheng Zheng, Jung Chen, Mei-Xiong Chen, Ming-Kui Xu, Jia Li, Huajun Wang, Yanping Gao, Ling Li

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicAcupuncture Treatment Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsElectroacupunctureMedicineOsteoarthritisWOMACVisual analogue scaleInternal medicineSynovial fluidRehabilitationPhysical therapyAnesthesiaAcupuncturePathology

Abstract

fetched live from OpenAlex

Abstract Objective To investigate the expression of inflammatory factors IL-6, IL-8, MMP-1, and MMP-3 in the synovial fluid (SF) of patients with osteoarthritis (OA) during electroacupuncture treatment, and further analyze the correlation between inflammatory factors and the function of patients and the severity of osteoarthritis. Methods 137 patients with knee osteoarthritis (KOA) were collected. 128 patients were eventually enrolled in the study after propensity matching analysis, including 64 patients in the electroacupuncture group and 64 patients in the control group. K-L grading was performed according to X-rays. The patients in the control group were treated with conventional physical rehabilitation therapy. The patients in the electroacupuncture group were treated with 6 weeks of electroacupuncture and conventional physical rehabilitation therapy. The visual analog score (VAS), Western Ontario and McMaster University Osteoarthritis Index (WOMAC), and Lysholm knee score were compared at three time points: before treatment, 6 weeks after treatment, and 6 months after treatment. The levels of SF inflammatory factors IL-6, IL-8, MMP-1, and MMP-3 were analyzed in both groups at three time points to investigate the correlation between inflammatory factors and functional scores and K-L classification. Results The VAS, WOMAC, and Lysholm scores of patients in both groups improved significantly after treatment (P < 0.05). The electroacupuncture group showed a significant reduction in VAS compared to the control group at 6 weeks and 6 months after treatment (P < 0.05). WOMAC scores were significantly lower in the electroacupuncture group compared to the control group at 6 months post-treatment (P < 0.05). Lysholm scores were significantly higher in the electroacupuncture group compared to the control group at 6 weeks and 6 months post-treatment (P < 0.05). The levels of all inflammatory factors decreased significantly in both groups after treatment. The levels of IL-6, IL-8, and MMP-3 were significantly lower in the electroacupuncture group compared with the control group at 6 weeks and 6 months after treatment (P < 0.05). The level of IL-6 was positively correlated with VAS scores (r = 0.45, p < 0.001) and WOMAC (r = 0.3, p < 0.001), and negatively correlated with Lysholm score (r=-0.27, p < 0.001) and K-L classification (r=- 0.54, p < 0.001).The level of IL-8 was positively correlated with VAS (r = 0.32, p < 0.001) and negatively correlated with Lysholm score (r=-0.19, p < 0.0027). The level of MMP-3 was positively correlated with WOMAC score (r = 0.48, p < 0.001). The level of MMP-1 was negatively correlated with K-L classification (r =-0.29, p < 0.001). Conclusion IL-6 in SF was associated with pain, impaired function, and the severity of OA. MMP-3 is associated with the severity of OA. IL-6 and MMP-3 are expected to be used as a biomarker for diagnosis, treatment, and determining the prognosis and severity of OA. Electroacupuncture can effectively relieve pain and enhance articular function in patients with KOA. It is a safe and effective method for treating KOA. SF inflammatory factor levels in patients with KOA decreased significantly after electroacupuncture treatment. Electroacupuncture treatment may work by anti-inflammatory effect.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.032
GPT teacher head0.326
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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