Publication: The impact of different GFR estimating equations on the prevalence of CKD and risk groups in a Southeast Asian cohort using the new KDIGO guidelines
No. of Pages/File Size
BMC Nephrology. Vol.13, No.1 (2012)
Chagriya Kitiyakara, Sukit Yamwong, Prin Vathesatogkit, Anchalee Chittamma, Sayan Cheepudomwit, Somlak Vanavanan, Bunlue Hengprasith, Piyamitr Sritara (2012). The impact of different GFR estimating equations on the prevalence of CKD and risk groups in a Southeast Asian cohort using the new KDIGO guidelines. Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/15018.
The impact of different GFR estimating equations on the prevalence of CKD and risk groups in a Southeast Asian cohort using the new KDIGO guidelines
Background: Recently, the Kidney Disease: Improving Global Outcomes (KDIGO) group recommended that patients with CKD should be assigned to stages and composite relative risk groups according to GFR (G) and proteinuria (A) criteria. Asians have among the highest rates of ESRD in the world, but establishing the prevalence and prognosis CKD is a problem for Asian populations since there is no consensus on the best GFR estimating (eGFR) equation. We studied the effects of the choice of new Asian and Caucasian eGFR equations on CKD prevalence, stage distribution, and risk categorization using the new KDIGO classification. Methods. The prevalence of CKD and composite relative risk groups defined by eGFR from with Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI); standard (S) or Chinese(C) MDRD; Japanese CKD-EPI (J-EPI), Thai GFR (T-GFR) equations were compared in a Thai cohort (n = 5526). Results: There was a 7 fold difference in CKD 3-5 prevalence between J-EPI and the other Asian eGFR formulae. CKD 3-5 prevalence with S-MDRD and CKD-EPI were 2 - 3 folds higher than T-GFR or C-MDRD. The concordance with CKD-EPI to diagnose CKD 3-5 was over 90% for T-GFR or C-MDRD, but they only assigned the same CKD stage in 50% of the time. The choice of equation also caused large variations in each composite risk groups especially those with mildly increased risks. Different equations can lead to a reversal of male: female ratios. The variability of different equations is most appa rent in older subjects. Stage G3aA1 increased with age and accounted for a large proportion of the differences in CKD 3-5 between CKD-EPI, S-MDRD and C-MDRD. Conclusions: CKD prevalence, sex ratios, and KDIGO composite risk groupings varied widely depending on the equation used. More studies are needed to define the best equation for Asian populations. © 2012Kitiyakara et al; licensee BioMed Central Ltd.