Comparison of the Cockcroft-Gault and MDRD equations with the endogenous creatinine clearance to estimate renal function in ambulatory adult patients treated in a peruvian reference hospital
Abstract
Introduction: The estimation of renal function is an important component of hospital care. To do this, estimates are usually used, based on serum creatinine levels. The most widely used equations are MDRD and Cockcroft-Gault. Objective: To evaluate the correlation of the Cockcroft-Gault and MDRD equations with the creatinine clearance value, based on 24-hour urine collection. Methods: In order to carry out this study, the records of the Clinical Pathology Service of Hospital Nacional Hipólito Unanue, a reference hospital in Lima (Peru), were used. Serum creatinine was measured using the Jaffe’s method. Creatinine clearance was performed by simultaneous determinations of serum creatinine and urinary creatinine, obtained through 24-hour urine collection. Correlations were calculated using Pearson coefficient, considering significant values of p<0.05. Results: 426 patients were included. The average age was 58.36 +/- 16.21 years, with a minimum age of 15 and a maximum of 91. There was a slight female predominance (51.2%). The correlation between creatinine clearance and that estimated by the MDRD equation was 0.57 (p<0.001); when restricting the analysis to those patients with clearance values lower than 60 ml/min, the correlation was 0.55 (p <0.001). The correlation between creatinine clearance and that estimated by the Cockcroft-Gault equation was 0.53 (p<0.001); when the analysis was limited to patients with purification values lower than 60 ml/min, the correlation was 0.55 (p <0.001). The correlation between Cockcroft-Gault and MDRD equations was 0.84 (p<0.01). In patients with purifications below 60, it was 0.87 (p<0.01). The results showed no differences when restricting observations to patients under 70. Conclusion: Although Cockcroft-Gault and MDRD equations keep a good correlation between them, this correlation is suboptimal with creatinine clearance performed through 24-hour collection, under usual clinical conditions.References
Stevens LA, Levey AS. Use of the MDRD study equation to estimate kidney function for drug dosing. Clin Pharmacol Ther. 2009;86(5):465-7.
National Kidney foundation. KDIGO 2012 Clinical Practice Guideline for the Evaluation and Management of Chronic Kidney Disease. Kidney Int Suppl. 2013;3(1):1-150.
Levey AS, Eckardt KU, Tsukamoto Y, Levin A, Coresh J, Rossert J, et al. Definition and classification of chronic kidney disease: a position statement from Kidney Disease: Improving Global Outcomes (KDIGO). Kidney Int. 2005;67(6):2089-100.
Inker LA, Shaffi K, Levey AS. Estimating glomerular filtration rate using the chronic kidney disease-epidemiology collaboration creatinine equation: better risk predictions. Circ Heart Fail. 2012;5(3):303-6.
Stevens LA, Coresh J, Greene T, Levey AS. Assessing kidney function--measured and estimated glomerular filtration rate. N Engl J Med. 2006;354(23):2473-83.
Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31-41.
Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D. A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999;130(6):461-70.
Levey AS, Coresh J, Greene T, Marsh J, Stevens LA, Kusek JW, et al. Expressing the Modification of Diet in Renal Disease Study equation for estimating glomerular filtration rate with standardized serum creatinine values. Clin Chem. 2007;53(4):766-72.
Mulay A, Gokhale S. Comparison of serum creatinine-based estimating equations with gates protocol for predicting glomerular filtration rate in indian population. Indian J Nephrol. 2017; 27(2):124-8.
Chen J, Tang H, Huang H, Lv L, Wang Y, Liu X, et al. Development and validation of new glomerular filtration rate predicting models for Chinese patients with type 2 diabetes. J Transl Med. 2015;13:317.
Ma YC, Zuo L, Chen JH, Luo Q, Yu XQ, Li Y, et al. Modified glomerular filtration rate estimating equation for Chinese patients with chronic kidney disease. J Am Soc Nephrol. 2006;17(10):2937-44.
Zuo L, Ma YC, Zhou YH, Wang M, Xu GB, Wang HY. Application of GFR-estimating equations in Chinese patients with chronic kidney disease. Am J Kidney Dis. 2005;45(3):463-72.
Hernández Ocampo J, Torres Rosalesa A, Rodríguez Castellanosa F. Comparación de cuatro métodos de medición de la tasa de filtración glomerular con depuración de inulina en individuos sanos y en pacientes con insuficiencia renal. Nefrologia. 2010;30(3):324-30.
Arreola-Guerra JM, Rincón-Pedrero R, Cruz-Rivera C, Belmont-Péreza T, Correa-Rotter R, Niño-Cruza JA. Funcionamiento de las fórmulas MDRD-IDMS y CKD-EPI, en individuos mexicanos con función renal normal. Nefrologia. 2014;34(5):545-692.
Delanaye P, Mariat C. The applicability of eGFR equations to different populations. Nat Rev Nephrol. 2013;9(9):513-22.
Teruel JL, Sabater J, Galeano C, Rivera M, Merino JL, Fernández Lucas M, et al. La ecuación de Cockcroft.Gault es preferible a la ecuación MDRD para medir el filtrado glomerular en la insuficiencia renal crónica avanzada. Nefrologia. 2007;27(3):313-9.
Vart P, Grams ME. Measuring and assessing kidney function. Semin Nephrol. 2016;36(4):262-72.
Delanaye P, Cavalier E, Cristol JP, Delanghe JR. Calibration and precision of serum creatinine and plasma cystatin C measurement: impact on the estimation of glomerular filtration rate. J Nephrol. 2014;27(5):467-75.
Harmoinen A, Lehtimäki T, Korpela M, Turjanmaa V, Saha H. Diagnostic accuracies of plasma creatinine, cystatin C, and glomerular filtration rate calculated by the Cockcroft-Gault and Levey (MDRD) formulas. Clin Chem. 2003;49(7):1223-5.
Gracia García S, Montañés Barmudez R, Bover Sanjuan J, Cases Amenós A, Deulofeu Piquet R, Martin de Fran AL. Recomendaciones sobre la utilización de ecuaciones para la estimación del filtrado glomerular en adultos. Nefrologia. 2006;26(6):651-759.
