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Common and Unique Factors and the Bidirectional Relationship Between Chronic Kidney Disease and Nonalcoholic Fatty Liver in Type 2 Diabetes Patients

PURPOSE: This study aimed to investigate the common and unique risk factors and bidirectional relationship between chronic kidney disease (CKD) and nonalcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes mellitus (T2DM). PATIENTS AND METHODS: This was a cross-sectional study of pat...

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Detalles Bibliográficos
Autores principales: Lee, Yau-Jiunn, Wang, Chao-Ping, Hung, Wei-Chin, Tang, Wei-Hua, Chang, Yu-Hung, Hu, Der-Wei, Lu, Yung-Chuan, Yu, Teng-Hung, Wu, Cheng-Ching, Chung, Fu-Mei, Hsu, Chia-Chang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7173841/
https://www.ncbi.nlm.nih.gov/pubmed/32368113
http://dx.doi.org/10.2147/DMSO.S237700
Descripción
Sumario:PURPOSE: This study aimed to investigate the common and unique risk factors and bidirectional relationship between chronic kidney disease (CKD) and nonalcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes mellitus (T2DM). PATIENTS AND METHODS: This was a cross-sectional study of patients with T2DM enrolled in a disease management program at two specialized diabetes outpatient clinics. Common and unique risk factors for CKD and NAFLD were examined using structural equation models (SEMs). SEMs were also used to examine direct and indirect effects of NAFLD on CKD and those of CKD on NAFLD. RESULTS: A total of 1992 subjects with T2DM were enrolled in this study. In multivariate analysis, NAFLD was independently associated with the odds of CKD (adjusted odds ratio=1.59, 95% confidence interval=1.12–2.25, P=0.009). SEMs showed that age, triglyceride, uric acid (UA), albumin, and HbA1c levels had statistically significant direct effects on CKD, and the final model could explain 22% of the variability in CKD. Age, triglycerides, body mass index (BMI), UA, white blood cell (WBC) count, serum glutamic pyruvic transaminase (SGPT) level, and smoking status had statistically significant direct effects on NAFLD, and the final model could explain 43% of the variability in NAFLD. The common risk factors contributing to both CKD and NAFLD were age, triglycerides, and UA. The unique risk factors were albumin and HbA1c for CKD, and BMI, WBC, SGPT, and smoking for NAFLD. In addition, SEM analysis also confirmed the bidirectional causal relationship between NAFLD and CKD. CONCLUSION: Common and unique risk factors and a bidirectional relationship existed between CKD and NAFLD in our patients with T2DM.