Abstract

BackgroundThe primary objective of this study aims to test patient factors, with a focus on cardiometabolic disease, influencing the performance of the Cockcroft-Gault equation in estimating glomerular filtration rate.MethodsA cohort study was performed using data from adult patients with both a 24-h urine creatinine collection and a serum creatinine available. Creatinine clearance was calculated for each patient using the Cockcroft-Gault, Modified Diet in Renal Disease, and Chronic Kidney Disease Epidemiology Collaboration equations and estimates were compared to the measured 24-h urine creatinine clearance. In addition, new prediction equations were developed.ResultsIn the overall study population (n = 484), 44.2% of patients were obese, 44.0% had diabetes, and 30.8% had dyslipidemia. A multivariable model which incorporating patient characteristics performed the best in terms of correlation to measured 24-h urine creatinine clearance, accuracy, and error. The modified Cockcroft-Gault equation using lean body weight performed best in the overall population, the obese subgroup, and the dyslipidemia subgroup in terms of strength of correlation, mean bias, and accuracy.ConclusionsRegardless of strategy used to calculate creatinine clearance, residual error was present suggesting novel methods for estimating glomerular filtration rate are urgently needed.

Highlights

  • Creatinine clearance (CrCl) is used to estimate glomerular filtration rate (GFR) to assess renal function

  • The primary objective of this study aims to test patient factors, with a focus on cardiometabolic disease, influencing the performance of the Cockcroft-Gault equation in estimating GFR

  • All consecutive adult patients with both a 24-h urine creatinine collection and a serum creatinine obtained within 24 h of each other were screened for inclusion

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Summary

Introduction

Creatinine clearance (CrCl) is used to estimate glomerular filtration rate (GFR) to assess renal function. Brunetti et al BMC Nephrology (2021) 22:389 and human studies provide evidence that atherogenic lipid profile influences glomerular sclerosis and renal dysfunction, respectively, making dyslipidemia a relevant consideration in evaluating renal function estimates [5, 6]. Both obesity and diabetes are associated with altered muscle mass, [7, 8] which may influence serum creatinine a key variable in the Cockcroft-Gault equation. The primary objective of this study aims to test patient factors, with a focus on cardiometabolic disease, influencing the performance of the Cockcroft-Gault equation in estimating glomerular filtration rate

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