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Abstract Introduction: Hepatitis C virus infection and DM are two major public health problems associated with increasing complications and mortality rates. Patients with DM may suffer from a variety of complications, of these, DKD is most common representing an important leading cause of ESRD worldwide. Moreover, the spectrum of renal affection in chronic HCV infection is widely described. The nature of kidney disease in DM-HCV patients is not sufficiently studied. NThe aim of work: The aim of this study was to clarify the potential diagnostic and prognostic usefulness of renal biopsy in diabetic HCV-infected patients with evidence of kidney injury. Also, spot the significant associations between certain clinical and histopathological parameters in the renal biopsy, and evaluate the predictive value of these clinical parameters for final histopathological diagnosis. Research Plan: The present study is a renal biopsy-based pilot study to spot the differences in renal histological changes between three groups of patients who were presented with evidence of kidney injury in the form of deteriorated kidney function and/or active urinary sediments. The main study group comprised twenty patients who were DM-HCV and another two groups were included as diseased control groups, the first of them was twenty HCV-only patients, and the second group was DM-only patients. Results: Classic DKD pattern was diagnosed in 40% of DM-HCV patients versus 52% in DM-only group. However, NDKD was diagnosed in 50% and 40%, respectively. Univariate logistic regression analysis was applied on DM-HCV patients, none of the predictors showed a statistically significant relationship with DKD diagnosis. Conclusion: The current study shows proof that renal biopsy might represent an important diagnostic and prognostic tool in DM-HCV patients particularly for identifying patients with NDKD, assumed to be associated with HCV infection, who would benefit from personalized treatment for retarding ESRD. It is difficult to rely on the clinical parameters in predicting the nature of kidney disease in those patients. |