Dyslipidemia in osteoarthritis: A study combining bibliometric analysis and retrospective data mining

骨关节炎中的血脂异常:一项结合文献计量分析和回顾性数据挖掘的研究

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Abstract

Osteoarthritis (OA) is one of the common chronic arthritis in middle-aged and elderly people, but the effect of lipid metabolism on OA is still unclear. The aim of this study was to explore the value of lipid metabolism markers as emerging biomarkers for assessing OA disease activity. The literature on OA and lipid metabolism indicators was extensively analyzed by bibliometric. Correlation analysis was used to analyze the correlation between lipid profile indicators (total cholesterol; triglycerides [TG]; high density lipoprotein cholesterol [HDL-C]; and low density lipoprotein cholesterol) and immunoinflammatory indicators (high sensitivity C-reactive protein; erythrocyte sedimentation rate [ESR]) in patients with OA as well as the disease activity level (visual analog scale (VAS). Logistic regression modeling was used to calculate univariate and multivariate factors of disease activity. A total of 843 papers were retrieved. China and the United States are the 2 most productive countries in this field, and the United States has the highest H-index. In addition, Osteoarthritis and Cartilage is the most published journal. OA lipid metabolism research has long focused on inflammation, lipid metabolism, and pain. The levels of inflammation (ESR, high sensitivity C-reactive protein) and lipid metabolism indicators (total cholesterol; TG, HDL-C) were significantly increased in OA patients. Inflammation indicators were significantly correlated with lipid metabolism indicators. In addition, HDL-C, ESR, and TG were identified as independent influencing factors for OA-VAS. In summary, the role of lipid metabolism in OA has been a hot topic. Markers of inflammation and lipid metabolism were independent influencing factors of OA-VAS.

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