Comparison of creatinine-based estimations of glomerular filtration rate in endurance athletes at rest

Several creatinine-based estimates of the glomerular filtration rate (GFR) have been advocated as reliable alternatives to the urinary clearance of exogenous filtration markers. The Cockcroft-Gault (C-G) equation requires a body weight parameter, which was not included in the Modification of Diet in Renal Disease (MDRD) Study and the Mayo Clinic Quadratic Equation (MCQE) formulas. However, there is little information on the lifestyle influences on these equations, especially the intensity and the type of physical activity.

We evaluated the differences in the GFR, as estimated by the MDRD, MCQE and C-G equations, in 60 professional male cyclists at rest and 60 healthy sedentary matched controls.

Professional cyclists had significantly lower body weight, body mass index and serum creatinine concentration than healthy sedentary individuals. We also observed a significantly higher MDRD-estimated GFR in athletes than in controls (119 mL/min/1.73 m2 vs. 104 mL/min/1.73 m2, p<0.001), whereas the GFR values estimated by both the MCQE (137 vs. 135, p=0.128) and C-G (127 vs. 127, p=0.490) formulas did not differ significantly. As compared to the MDRD values, the mean GFR calculated by the MCQE and C-G formulas was overestimated by 29% and 23% in the sedentary population, and by 17% and 7% in athletes, respectively. A lower bias was observed when comparing C-G with MCQE-estimated values in both the sedentary [mean: -5%, 95% confidence interval (CI): -32% to 22%] and athlete (mean: -6%, 95% CI: -41% to 29%) populations. The correlation among the different equations in healthy sedentary individuals was always significant, whereas the only significant association in the athletes was that between MCQE and C-G values.

The results of this study attest that the three most widely used creatinine-based formulas produce significant variations in the estimated GFR in a population of endurance athletes at rest. Probably, the use of C-G or MCQE formulas might be more suitable in this context, as they globally appear more robust against variations of the training regimen.