Predictors of Renal Damage in non diabetic Metabolic Dysfunction associated Fatty Liver Disease (MAFLD) Patients: Role of Tumor Necrosis Factor α

Autor: Mustafa Adel Ahmed Younis, Amr M Zaghloul, Marwa S. Hashim, Tasneem Mohammed Ali, Ali Hussein Mohammed, Nesma M. Ahmed
Rok vydání: 2023
Popis: Background: The risk of chronic kidney disease (CKD) has shown increasing incidence among patients with metabolic dysfunction associated fatty liver disease (MAFLD). The kidney is affected in inflammatory conditions and TNFα has been involved in different inflammatory cascade leading to renal damage. Less is known about the relation between MAFLD and the risk of CKD in Egyptian non diabetic patients. Our study explores the role of TNFα as a predictor of renal damage in those patients. Method: We evaluated 237 non diabetic patients with MAFLD using transient elastography (TE) with CAP. CKD was defined by an albumin-to creatinine ratio (A/Cr) >30 mg/g if persistent for more than 3 months. Patients were subgrouped into two groups: group (A) included patients with CKD and group (B) included patients without CKD. Human TNF levels in serum were assessed utilizing an enzyme-linked immunosorbent assay (ELISA) . In addition, logistic regression and stepwise multiple logistic regression were used for the evaluation of the factors associated with renal damage. The ROC analysis was used to assess the role of TNF in predicting renal damage and the best cut off point. Results: The prevalence of CKD among the studied group was (61.6 %.). Patients with CKD had higher values of waist circumference and BMI. They also have a significantly higher liver stiffness measurements (LSM) and CAP values. The ROC curves showed that the TNF α could predict the presence of chronic kidney disease with cut off value (23.05 ng/L) with a sensitivity of 98% and a specificity of 72%. Conclusion: In patients MAFLD and with other metabolic risk factors for CKD, TNF α could predict the presence of chronic kidney disease. However, we need more studies with a higher number of patients to confirm our results.
Databáze: OpenAIRE