Should the CKD EPI Equation Be Used for Estimation of the Glomerular Filtration Rate in Obese Subjects?

Abstract

Introduction: The pandemic of obesity is strongly related to increase of chronic kidney disease (CKD) prevalence. The currently recommended CKD epidemiology collaboration (CKD EPI) equation has several serious limitations, particularly in obese subjects who have high body surface area (BSA). The aim of our study was to analyze differences in the prevalence of CKD between CKD EPI and de-indexed equations where individual BSA was used. Methods: In a total of 2,058 subjects (random sample from a general rural population, 29.65% obese), BSA was estimated using DuBois and DuBois and Moesteller equations and included into the de-indexed equations (CKD DBi, CKD Mi). CKD was classified according to the KDIGO guidelines, and glomerular hyperfiltration (GHF) was defined as 95th percentile, according to the gender and age decade. Results: In obese subjects, prevalence of CKD was significantly higher with CKD EPI than with CKD DBi and CKD Mi equations (9.5%, 6.1%, 5.3%, respectively; p < 0.001), while prevalence of GHF was significantly lower (3.8%, 12.3%, 12.8%, respectively; p < 0.001). Opposite results were observed in subjects with a body mass index <25 kg/m2 for CKD (5%, 7.1%, 7.2%; p = 0.07) and GHF prevalence (6.1%, 1%, 0.6%; p < 0.001). Discussion/Conclusions: The prevalence of CKD is overestimated, and the prevalence of GHF is underestimated in obese subjects using the CKD EPI equation, i.e., the CKD EPI equation is unreliable in one-third of the population. De-indexed equations should be recommended instead of the CKD EPI equation in epidemiological studies until direct measurement of the glomerular filtration rate becomes more available.

© 2022 The Author(s). Published by S. Karger AG, Basel

References Hill NR, Fatoba ST, Oke JL, Hirst JA, O’Callaghan CA, Lasserson DS, et al. Global prevalence of chronic kidney disease: a systematic review and meta-analysis. PLoS One. 2016 Jul 6;11(7):e0158765. Mills KT, Xu Y, Zhang W, Bundy JD, Chen CS, Kelly TN, et al. A systematic analysis of world-wide population-based data on the global burden of chronic kidney disease in 2010. Kidney Int. 2015 Nov;88(5):950–7. Chronic Kidney Disease Prognosis Consortium; Matsushita K, van der Velde M, Astor BC, Woodward M, Levey AS, et al. Association of estimated glomerular filtration rate and albuminuria with all-cause and cardiovascular mortality in general population cohorts: a collaborative meta-analysis. Lancet. 2010 Jun 12;375(9731):2073–81. GBD Chronic Kidney Disease Collaboration. Global, regional, and national burden of chronic kidney disease, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2020 Feb 29;395(10225):709–33. Tonelli M, Pfeffer MA. Kidney disease and cardiovascular risk. Annu Rev Med. 2007;58:123–39. Gansevoort RT, Correa-Rotter R, Hemmelgarn BR, Jafar TH, Heerspink HJL, Mann JF, et al. Chronic kidney disease and cardiovascular risk: epidemiology, mechanisms, and prevention. Lancet. 2013 Jul 27;382(9889):339–52. Garofalo C, Borrelli S, Minutolo R, Chiodini P, De Nicola L, Conte G. A systematic review and meta-analysis suggests obesity predicts onset of chronic kidney disease in the general population. Kidney Int. 2017 May;91(5):1224–35. Wuerzner G, Pruijm M, Maillard M, Bovet P, Renaud C, Burnier M, et al. Marked association between obesity and glomerular hyperfiltration: a cross-sectional study in an African population. Am J Kidney Dis. 2010 Aug;56(2):303–12. Hsu CY, Go AS, Iribarren C, Darbinian J, Go A. Body mass index and risk for end-stage renal disease. Ann Intern Med. 2006 Jan 3;144(9):701–8. Palatini P. Glomerular hyperfiltration: a marker of early renal damage in pre-diabetes and pre-hypertension. Nephrol Dial Transplant. 2012 May;27(5):1708–14. Eriksen BO, Løchen ML, Arntzen KA, Bertelsen G, Eilertsen BAW, von Hanno T, et al. Subclinical cardiovascular disease is associated with a high glomerular filtration rate in the nondiabetic general population. Kidney Int. 2014 Jul;86(1):146–53. Rognant N, Laville M. To live with normal GFR: when higher is not better. Kidney Int. 2014 Jul;86(1):10–3. Levin A, Stevens PE. Summary of KDIGO 2012 CKD guideline: behind the scenes, need for guidance, and a framework for moving forward. Kidney Int. 2014 Jan;85(1):49–61. O’Hare AM, Bertenthal D, Covinsky KE, Landefeld CS, Sen S, Mehta K, et al. Mortality risk stratification in chronic kidney disease: one size for all ages? J Am Soc Nephrol. 2006 Mar;17(3):846–53. O’Hare AM. Measures to define chronic kidney disease. JAMA. 2013 Apr;309(13):1343–4. Wetzels JFM, Kiemeney LALM, Swinkels DW, Willems HL, den Heijer M. Age- and gender-specific reference values of estimated GFR in Caucasians: the Nijmegen Biomedical Study. Kidney Int. 2007 Sep;72(5):632–7. De Broe ME, Gharbi MB, Zamd M, Elseviers M. Why overestimate or underestimate chronic kidney disease when correct estimation is possible. Nephrol Dial Transplant. 2017 Apr 1;32(Suppl 2):ii136–41. Delanaye P, Glassock RJ, Pottel H, Rule AD. An age-calibrated definition of chronic kidney disease: rationale and benefits. Clin Biochem Rev. 2016 Feb;37(1):17–26. Levey AS, Stevens LA, Schmid CH, Zhang YL, Castro AF 3rd, Feldman HI, et al. A new equation to estimate glomerular filtration rate. Ann Intern Med. 2009 May 5;150(9):604–12. McIntosh JF, Möller E, Van Slyke DD. Studies on urea excretions: III. The influence of body size on urea output. J Clin Invest. 1928 Dec;6(3):467–83. Delanaye P, Mariat CH, Cavalier E, Krzesinski J-M. Errors induced by indexing glomerular filtration rate for body surface area: reductio ad absurdum. Nephrol Dial Transplant. 2009 Dec;24(12):3593–6. Park EJ, Pai MP, Dong T, Zhang J, Ko CW, Lawrence J, et al. The influence of body size descriptors on the estimation of kidney function in normal weight, overweight, obese, and morbidly obese adults. Ann Pharmacother. 2012 Mar;46(3):317–28. Ogden CL, Fryar CD, Carroll MD, Flegal KM. Mean body weight, height, and body mass index, United States 1960–2002. Adv Dana. 2004;(347):1–17. Heaf JG. The origin of the 1.73-m2 body surface area normalization: problems and implications. Clin Physiol Funct Imaging. 2007 May;27(3):135–7. Fryer CD, Gu Q, Ogden CL, Flegal KM. Anthropometric reference data for children and adults: United States, 2011–2014. Vital Health Stat 3 Anal Stud. 2016 Aug;3(39):1–46. Hense HW, Gneiting B, Muscholl M, Broeckel U, Kuch B, Doering A, et al. The associations of body size and body composition with left ventricular mass: impacts for indexation in adults. J Am Coll Cardiol. 1998 Aug;32(2):451–7. Friedman AN, Strother M, Quinney SK, Hall S, Perkins SM, Brizendine EJ, et al. Measuring the glomerular filtration rate in obese individuals without overt kidney disease. Nephron Clin Pract. 2010 Jul 2;116(3):c224–34. Chang AR, Zafar W, Grams ME. Kidney function in obesity-challenges in indexing and estimation. Adv Chronic Kidney Dis. 2018 Jan;25(1):31–40. Anastasio P, Spitali L, Frangiosa A, Molino D, Stellato D, Cirillo E, et al. Glomerular filtration rate in severely overweight normotensive humans. Am J Kidney Dis. 2000 Jun;35(6):1144–8. Porrini E, Ruggenenti P, Luis-Lima S, Carrara F, Jiménez A, de Vries APJ, et al. Estimated GFR: time for a critical appraisal. Nat Rev Nephrol. 2019 Mar;15(3):177–90. Jelakovic B, Zeljkovic-Vrkic T, Pecin I, Dika Z, Jovanovic A, Podobnik D, et al. Arterial hypertension in Croatia. Results of EH-UH study. Acta Med Croatica. 2007 Jun;61(3):287–92. Redal-Baigorri B, Rasmussen K, Heaf JG. Indexing glomerular filtration rate to body surface area: clinical consequences. J Clin Lab Anal. 2014 Mar;28(2):83–90. Redal-Baigorri B, Rasmussen K, Heaf JG. The use of absolute values improves performance of estimation formulae: a retrospective cross sectional study. BMC Nephrol. 2013 Dec 5;14:271–8. López-Martínez M, Luis-Lima S, Morales E, Navarro-Díaz M, Negrín-Mena N, Folgueras T, et al. The estimation of GFR and the adjustment for BSA in overweight and obesity: a dreadful combination of two errors. Int J Obes. 2020 May;44(5):1129–40. Rothberg AE, McEwen LN, Herman WH. Severe obesity and the impact of medical weight loss on estimated glomerular filtration rate. PLoS One. 2020 Feb;15(2):e0228984. Delanaye P, Radermecker RP, Rorive M, Depas G, Krzesinski JM. Indexing glomerular filtration rate for body surface area in obese patients is misleading. Concept and example. Nephrol Dial Transplant. 2005 Oct;20(10):2024–8. Demirovic JA, Pai AB, Pai MP. Estimation of creatinine clearance in morbidly obese patients. Am J Health Syst Pharm. 2009 Apr 1;66(7):642–8. The National Kidney Disease Education Program (NKEDP). CKD and drug dosing: information for providers. Available from: https://www.niddk.nih.gov/health-information/professionals/advanced-search/ckd-drug-dosing-providers (accessed on April 12, 2021). Wuerzner G, Bochud M, Giusti V, Burnier M. Measurement of glomerular filtration rate in obese patients: pitfalls and potential consequences on drug therapy. Obes Facts. 2011;4(3):238–43. Lemoine S, Guebre-Egziabher F, Sens F, Nguyen-Tu MS, Juillard L, Dubourg L, et al. Accuracy of GFR estimation in obese patients. Clin J Am Soc Nephrol. 2014 Apr;9(4):720–7. Anastasio P, Viggiano D, Zacchia M, Altobelli C, Capasso G, Gaspare De Santo N. Delay in renal hemodynamic response to a meat meal in severe obesity. Nephron. 2017;136(2):151–7. Delanaye P, Krzesinski J-M. Indexing of renal function parameters by body surface area: intelligence or folly? Nephron Clin Pract. 2011;119(4):c289–92. Article / Publication Details

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Abstract of Research Article

Received: January 25, 2022
Accepted: July 09, 2022
Published online: September 28, 2022

Number of Print Pages: 8
Number of Figures: 1
Number of Tables: 2

ISSN: 1420-4096 (Print)
eISSN: 1423-0143 (Online)

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