Lu-Xi Zou1, Ling Sun2, Susanne B Nicholas3, Yan Lu4, Satyesh Sinha K5, Ruixue Hua4. 1. Xuzhou Medical University, Xuzhou, Jiangsu, China. 2. Division of Nephrology, Xuzhou Central Hospital, Medical College of Southeast University, Xuzhou, Jiangsu, China; Department of Clinical Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China. Electronic address: slpku@163.com. 3. Divisions of Nephrology and Endocrinology, Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA, USA. Electronic address: sunicholas@mednet.ucla.edu. 4. Department of Clinical Medicine, Xuzhou Medical University, Xuzhou, Jiangsu, China. 5. Division of Nephrology, Department of Medicine, David Geffen School of Medicine at University of California, Los Angeles, CA, USA.
Abstract
BACKGROUND: The directly measured glomerular filtrate rate (mGFR) is the gold standard for kidney function, but it is invasive and costly. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations have been widely used to estimate GFR, however, the comparative accuracy of estimated GFR (eGFR) using creatinine and cystatin C in CKD-EPI equations remains unclear. We performed this meta-analysis to assess the bias and accuracy of eGFR using equations of CKD-EPIcrea, CKD-EPIcys, and CKD-EPIcrea/cys in adult populations relevant to primary health care. METHODS: Pubmed, Web of Science, EMBASE, and the Cochrane Library were searched from inception until December 2019 for related studies. RESULTS: A total of 35 studies with 23,667 participants, which reported the data on the bias, and/or P30, and/or R were included. The difference in the bias of eGFR using CKD-EPIcys was 4.84 mL/min/1.73 m2 (95% CI, 1.88~7.80) lower than using CKD-EPIcrea, and 1.50 mL/min/1.73 m2 (95% CI, 0.05~2.95) lower than using CKD-EPIcrea/cys. These gaps increased in subgroups of low mGFR (<60 mL/min/1.73 m2). CKD-EPIcrea/cys eGFR achieved the highest accuracy, 7.50% higher than CKD-EPIcrea (95% CI, 4.81~10.18), and 3.21% higher than CKD-EPIcys (95% CI, -0.43~6.85); and the best correlation with mGFR, with Fisher's z transformed R of 1.20 (95% CI, 0.89-1.50). CONCLUSIONS: CKD-EPIcrea/cys and CKD-EPIcys gave less bias and more accurate estimates of mGFR than CKD-EPIcrea. More variables and coefficients could be added in CKD-EPI equations to achieve less bias and more accuracy in future research.
BACKGROUND: The directly measured glomerular filtrate rate (mGFR) is the gold standard for kidney function, but it is invasive and costly. The Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations have been widely used to estimate GFR, however, the comparative accuracy of estimated GFR (eGFR) using creatinine and cystatin C in CKD-EPI equations remains unclear. We performed this meta-analysis to assess the bias and accuracy of eGFR using equations of CKD-EPIcrea, CKD-EPIcys, and CKD-EPIcrea/cys in adult populations relevant to primary health care. METHODS: Pubmed, Web of Science, EMBASE, and the Cochrane Library were searched from inception until December 2019 for related studies. RESULTS: A total of 35 studies with 23,667 participants, which reported the data on the bias, and/or P30, and/or R were included. The difference in the bias of eGFR using CKD-EPIcys was 4.84 mL/min/1.73 m2 (95% CI, 1.88~7.80) lower than using CKD-EPIcrea, and 1.50 mL/min/1.73 m2 (95% CI, 0.05~2.95) lower than using CKD-EPIcrea/cys. These gaps increased in subgroups of low mGFR (<60 mL/min/1.73 m2). CKD-EPIcrea/cys eGFR achieved the highest accuracy, 7.50% higher than CKD-EPIcrea (95% CI, 4.81~10.18), and 3.21% higher than CKD-EPIcys (95% CI, -0.43~6.85); and the best correlation with mGFR, with Fisher's z transformed R of 1.20 (95% CI, 0.89-1.50). CONCLUSIONS: CKD-EPIcrea/cys and CKD-EPIcys gave less bias and more accurate estimates of mGFR than CKD-EPIcrea. More variables and coefficients could be added in CKD-EPI equations to achieve less bias and more accuracy in future research.
Authors: Giuseppe Boriani; Saverio Iacopino; Giuseppe Arena; Paolo Pieragnoli; Roberto Verlato; Massimiliano Manfrin; Giulio Molon; Giovanni Rovaris; Antonio Curnis; Giovanni Battista Perego; Antonio Dello Russo; Maurizio Landolina; Marco Vitolo; Claudio Tondo Journal: J Cardiovasc Dev Dis Date: 2022-04-21
Authors: Yeli Wang; Andrew S Levey; Lesley A Inker; Saleem Jessani; Rasool Bux; Zainab Samad; Ali Raza Khan; Amy B Karger; John C Allen; Tazeen H Jafar Journal: Kidney Int Rep Date: 2021-01-16