Serum creatinine: conventional and compensated kinetic method with enzymatic method
Journal Title: International Journal of Clinical Biochemistry and Research - Year 2017, Vol 4, Issue 2
Abstract
Introduction: The overall magnitude and pattern of chronic kidney disease (CKD) in India has been studied sporadically. The estimated glomerular filtration rate (eGFR) is valuable in identifying patients at risk of developing nephropathy. However, calculation of the eGFR from serum creatinine levels is not without limitations. Aim: The aim of this study was to compare analytical performance and workability of the enzymatic method vs kinetic method(both conventional and compensated) for serum creatinine for routine use and to compare the effects of some common interfering substances like bilirubin on the enzymatic method vs kinetic Jaffe’s method. Materials and Method: We measured Serum creatinine by enzymatic, conventional and compensated kinetic creatinine measurement method in 120 samples having bilirubin >1mg/dl. Results: Relationship between Jaff’s kinetic semi-automated method and enzymatic method on Cobas Integra 400 plus for serum creatinine shows regression coefficient 0.88 which means two methods are not correlate with each other. Compensated Jaff’s kinetic method and enzymatic method shows regression coefficient 0.95 which means two methods are correlate with each other and the differences between two methods in Bland-Altman plot shows that compensated Jaff’s kinetic method have negative bias but differences between two methods are less (scatter reading) and constant throughout concentration range. Conclusion: There is good agreement and good comparability of the compensated kinetic Jaffe's method with the enzymatic method than conventional picric acid Jaff’s kinetic method we found that when serum bilirubin was high and serum creatinine was measure with conventional picric acid Jaff’s kinetic method and compensated picric acid Jaff’s kinetic method gives false low creatinine.
Authors and Affiliations
Kiran Chauhan, Dhara Kanani, Priya Patel, N. Haridas
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