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Published on: May 10, 2013
Comparability of serum creatinine-Based glomerular filtration rate equations in West African adult communities
E E Akpan1, U E Ekrikpo1, A I A Udo1
1Department of Internal Medicine, University of Uyo Teaching Hospital, Uyo, Akwa Ibom State, Nigeria.
Background:
The clinical diagnosis of chronic kidney disease (CKD) is based on estimated glomerular filtration rate (GFR) using serum creatinine-based equations. Many formulas are used in estimating GFR.
Objectives:
We set out to determine the degree of agreement between the Cockcroft-Gault (CG), 4-variable Modification of diet in renal disease (MDRD). Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations in our indigenous population.
Patients And Methods:
Adult participants were recruited across all sectors of life, education, and occupation. Blood pressure, fasting blood glucose, lipid profile, urinalysis, serum creatinine, and anthropometry were measured. Estimated GFR (eGFR) was computed using CG, MDRD, and CKD-EPI equations with and without the race factor. The Lin's concordance index (rho_c) and Bland-Altman analysis were used to determine the degree of agreement between various pairs of creatinine-based eGFR equations [MDRD with the race factor (MDRDw)]; MDRD without the race factor (MDRD); CKD-EPI with race factor (CKD-EPIw); CKD-EPI without the race factor (CKD-EPI), and the CG equation.
Results:
Two hundred and sixty-one adults, mean age 47.5 ± 9.9 years, 45.2% females participated in the study. Hypertension prevalence in the study population was 41.4 (95% CI 35.3-47.6%) while diabetes mellitus was 8.1% (95% CI 5.0-12.0%). The proportion of individuals with eGFRCKD-EPI less than 60 ml/min/1.73 m2 was 17.6 (95% CI 13.2-22.8%). All pairs of rho_c were lower than the threshold of 0.9 except for eGFRCKD-EPI versus eGFRCKD-EPw.
Conclusion:
There is significant discordance in the eGFR obtained from the various serum creatinine-based GFR equations in our population suggesting the need to validate these equations and determine the best equation for our general population.
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