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Association Between Serum Uric Acid and Carotid Intima-Media Thickness in Different Fasting Blood Glucose Patterns: A Case-Control Study

Our objective was to analyze the correlation between serum uric acid (SUA) levels and carotid intima-media thickness (CIMT) and explore the relationship between SUA and carotid atherosclerosis in different glucose metabolism patterns. A total of 614 patients were enrolled in this case-control study,...

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Detalles Bibliográficos
Autores principales: Gao, Yuanyuan, Xu, Baofeng, Yang, Yanyan, Zhang, Mei, Yu, Tian, Zhang, Qiujuan, Sun, Jianwei, Liu, Rui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9197240/
https://www.ncbi.nlm.nih.gov/pubmed/35712254
http://dx.doi.org/10.3389/fendo.2022.899241
Descripción
Sumario:Our objective was to analyze the correlation between serum uric acid (SUA) levels and carotid intima-media thickness (CIMT) and explore the relationship between SUA and carotid atherosclerosis in different glucose metabolism patterns. A total of 614 patients were enrolled in this case-control study, including 406 in the normouricemia group and 208 in the hyperuricemia group. The two groups were each divided into three groups according to fasting blood glucose (FBG) level: normal, impaired fasting glucose (IFG), and diabetes mellitus (DM). CIMT and the CIMT thickening rate in the hyperuricemia group were significantly higher than those in the normouricemia group: 0.17 (0.11–0.24) cm vs. 0.12 (0.08–0.15) cm and 73.56% vs. 51.97% (p < 0.001). Pearson’s correlation analysis showed that age, systolic blood pressure (SBP), diastolic blood pressure, FBG, triglyceride, SUA, creatinine, and blood urea nitrogen were positively correlated with CIMT, whereas high-density lipoprotein cholesterol and total cholesterol were negatively correlated with CIMT. Multiple linear regression analysis showed that age, SUA, FBG, and SBP were independent factors that affected CIMT. Furthermore, age and SBP were independent factors in the normouricemia group, and FBG was an independent factor that affected CIMT in the hyperuricemia group (p < 0.05). In the hyperuricemia group, CIMT in the DM group was significantly higher than that in the normal group [0.20 (0.14–0.25)cm vs. 0.15 (0.1–0.25); p < 0.05], and the CIMT thickening rate in the DM group was significantly higher than those in the IFG and normal groups (90.38% vs. 78.38%, 90.38% vs. 65.81%; p < 0.05). The ROC curve analysis showed that uric acid combined with age, SBP, and FBG had the highest area under the curve (AUC) for predicting CIMT thickening [0.855 (95% confidence interval (CI): 0.804–0.906)], followed by uric acid combined with FBG [AUC: 0.767 (95% CI: 0.726–0.808)]. In conclusion, SUA was closely associated with an increase in CIMT in patients with specific FBG metabolic patterns and may be an independent risk factor for carotid atherosclerosis. SUA, especially in combination with other factors (such as age, SBP, FBG), may serve as a specific model to help predict the incidence of CIMT thickening. Clinical Trial Registration: http://www.chictr.org.cn, identifier ChiCTR2000039124.