Comparison of Chronic Kidney Disease Epidemiology Collaboration Equations with Other Accepted Equations for Estimation of Glomerular Filtration Rate in Indian Chronic Kidney Disease Patients
DOI:
https://doi.org/10.3329/bjms.v16i2.24579Keywords:
CKD, GFR, CKD-EPI, eGFR, Tc-99m-DTPAAbstract
Background and Aim: In routine clinical practice, the estimation of glomerular filtration rate (GFR) based on serum creatinine has been followed. However, the reliability of creatinine in estimation of GFR is biased and imprecise, leading to the misdiagnosis of chronic kidney disease (CKD). The serum cystatin C is an alternative marker for estimating GFR. Hence, we aimed to compare the newly proposed Chronic Kidney Disease Epidemiology Collaboration Equations (CKD-EPI) with four approved equations based on both creatinine and cystatin C with reference to Tc-99m-diethylenetriamine pentaacetate (Tc-99m-DTPA) considered as a standard.
Materials and Methods:Two hundred and one patients were enrolled in the study from a private nephrology outpatient clinic(OPD), Tiruchirappalli, India. The serum creatinine and cystatin C were measured along with routine biochemistry tests. The measurement of GFR was done by Tc-99m-DTPA gates method. The estimated GFR (eGFR) were calculated using serum cystatin C and creatinine based formulae along with the new CKD-EPI formulae. All eGFR estimations were compared with the measured GFR by gates method.
Results: The average measured GFR of end stage, severe, moderate, mild renal disease and normal patient groups were 10.17±2.47, 22.58±4.40, 39.05±7.06, 69.62±24.64 and 118.06±29.23 respectively. When comparing the diagnostic accuracy for predicting GFR using well established formulae, the cystatin C based formulae have shown to be highly accurate in all stages of CKD than creatinine based formulae. Among cystatin C based formulae, CKD-EPI Cystatin C had relatively better diagnostic accuracy for predicting GFR in all stages of CKD.
Conclusion: CKD-EPI Cystatin C formula has unbiased and more accurate to predict GFR in all stages of CKD.
Bangladesh Journal of Medical Science Vol.16(2) 2017 p.238-244
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