Tadesse Asmamaw1, Solomon Genet2, Menakath Menon2, Getahun Tarekegn3, Endeshaw Chekol4, Zeleke Geto5, Tadesse Lejisa5, Wossene Habtu5, Tigist Getahun5, Yosef Tolcha5. 1. Department of Biochemistry, School of Medicine, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia. 2. Department of Biochemistry, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia. 3. Department of Internal Medicine, School of Medicine, College of Health Sciences, Addis Ababa University, Addis Ababa, Ethiopia. 4. Department of Biochemistry, College of Health Sciences, Debre Tabor University, Debre Tabor, Ethiopia. 5. National Reference Laboratory for Clinical Chemistry, Ethiopian Public Health Institute, Addis Ababa, Ethiopia.
Abstract
BACKGROUND: The proportion of patients with end-stage renal disease caused by diabetes has progressively increased during the last few decades. Serum creatinine level is the most commonly used biochemical parameter to estimate GFR in routine practice. However, 50% of GFR can be lost before significant elevation of serum creatinine. Cystatin C is found to be a new promising marker for early detection of renal diseases. OBJECTIVE OF THE STUDY: The aim of this study was to determine the value of serum cystatin C and serum creatinine levels for early detection of renal disease in patients with type 2 diabetes mellitus. METHODOLOGY: A hospital-based comparative cross-sectional study was conducted with a sample size of 120. For early detection of renal disease in patients with type 2 diabetes mellitus, serum creatinine and cystatin C levels were measured and compared. RESULT AND DISCUSSION: Serum creatinine and cystatin C levels were significantly increased in patients with type 2 diabetes mellitus compared to healthy controls. The mean±SD value of serum creatinine was found to be 0.87±0.44 mg/dL in patients and 0.63±0.27 mg/dL in control. Serum cystatin C level was also found to be significantly (P=0.0001) higher in patients (0.92±0.38 mg/L) compared to controls (0.52±0.20 mg/L). The mean±SD of eGFR in three equations (Creatinine Equation, Cystatin C Equation, and Creatinine-Cystatin C Equation) were 105.7±27.5 mL/min/m2, 90.4±28.2 mL/min/m2, and 100±29.5 mL/min/m2, respectively. CONCLUSION: Cystatin C-based GFR estimation equations detect renal impairment in patients with type 2 diabetes mellitus earlier than creatinine-based GFR estimation equations.
BACKGROUND: The proportion of patients with end-stage renal disease caused by diabetes has progressively increased during the last few decades. Serum creatinine level is the most commonly used biochemical parameter to estimate GFR in routine practice. However, 50% of GFR can be lost before significant elevation of serum creatinine. Cystatin C is found to be a new promising marker for early detection of renal diseases. OBJECTIVE OF THE STUDY: The aim of this study was to determine the value of serum cystatin C and serum creatinine levels for early detection of renal disease in patients with type 2 diabetes mellitus. METHODOLOGY: A hospital-based comparative cross-sectional study was conducted with a sample size of 120. For early detection of renal disease in patients with type 2 diabetes mellitus, serum creatinine and cystatin C levels were measured and compared. RESULT AND DISCUSSION: Serum creatinine and cystatin C levels were significantly increased in patients with type 2 diabetes mellitus compared to healthy controls. The mean±SD value of serum creatinine was found to be 0.87±0.44 mg/dL in patients and 0.63±0.27 mg/dL in control. Serum cystatin C level was also found to be significantly (P=0.0001) higher in patients (0.92±0.38 mg/L) compared to controls (0.52±0.20 mg/L). The mean±SD of eGFR in three equations (Creatinine Equation, Cystatin C Equation, and Creatinine-Cystatin C Equation) were 105.7±27.5 mL/min/m2, 90.4±28.2 mL/min/m2, and 100±29.5 mL/min/m2, respectively. CONCLUSION: Cystatin C-based GFR estimation equations detect renal impairment in patients with type 2 diabetes mellitus earlier than creatinine-based GFR estimation equations.
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