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Analysis of chronic kidney disease staging with different estimated glomerular filtration rate equations in Chinese centenarians

BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) and staging of chronic kidney disease (CKD) are important. Currently, there is no research on the differences in several estimated GFR equations for staging CKD in a large sample of centenarians. Thus, this study aimed to invest...

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Detalles Bibliográficos
Autores principales: Han, Qiu-Xia, Zhang, Dong, Zhao, Ya-Li, Liu, Liang, Li, Jing, Zhang, Fu, Luan, Fu-Xin, Duan, Jia-Yu, Liu, Zhang-Suo, Cai, Guang-Yan, Chen, Xiang-Mei, Zhu, Han-Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer Health 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6416091/
https://www.ncbi.nlm.nih.gov/pubmed/30741827
http://dx.doi.org/10.1097/CM9.0000000000000079
Descripción
Sumario:BACKGROUND: Accurate estimation of the glomerular filtration rate (GFR) and staging of chronic kidney disease (CKD) are important. Currently, there is no research on the differences in several estimated GFR equations for staging CKD in a large sample of centenarians. Thus, this study aimed to investigate the differences in CKD staging with the most commonly used equations and to analyze sources of discrepancy. METHODS: A total of 966 centenarians were enrolled in this study from June 2014 to December 2016 in Hainan province, China. The GFR with the Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Berlin Initiative Study 1 (BIS1) equations were estimated. Agreement between these equations was investigated with the κ statistic and Bland-Altman plots. Sources of discrepancy were investigated by partial correlation analysis. RESULTS: The κ values of the MDRD and CKD-EPI equations, MDRD and BIS1 equations, and CKD-EPI and BIS1 equations were 0.610, 0.253, and 0.381, respectively. Serum creatinine (Scr) explained 10.96%, 41.60% and 17.06% of the variability in these three comparisons, respectively. Serum uric acid (SUA) explained 3.65% and 5.43% of the variability in the first 2 comparisons, respectively. Gender was associated with significant differences in these 3 comparisons (P < 0.001). CONCLUSIONS: The strengths of agreement between the MDRD and CKD-EPI equations were substantial, but those between the MDRD and BIS1 equations and the CKD-EPI and BIS1 equations were fair. The difference in CKD staging of the first 2 comparisons strongly depended on Scr, SUA and gender, and that of CKD-EPI and BIS1 equations strongly depended on Scr and gender. The incidence at various stages of CKD staging was quite different. Thus, a new equation that is more suitable for the elderly needs to be built in the future.