Commentary: Renal Function Estimation and Cockcroft–Gault Formulas for Predicting Cardiovascular Mortality in Population-Based, Cardiovascular Risk, Heart Failure and Post-Myocardial Infarction Cohorts: The Heart ‘OMics’ in AGEing (HOMAGE) and the High-Risk Myocardial Infarction Database Initiatives

In a recent study, Ferreira and colleagues describe the association of common equations to estimate renal function via “estimated glomerular filtration rate” (eGFR) with mortality. The authors suggest that while the Cockcroft–Gault-body surface area (BSA) method is more accurate in predicting cardiovascular mortality in patients with existing cardiovascular risk, the CKD-EPI (Chronic Kidney Disease Epidemiology Collaboration equation) provides the best compromise between renal function and cardiovascular mortality prediction. As the authors state, the measurement of accurate renal function is important in the diagnosis and treatment of chronic kidney disease (CKD), adjustment of drug doses, and decision-making regarding renal replacement therapy initiation. In all methods described by Ferreira et al., eGFR measurement is based on serum creatinine clearance. Creatinine is a 113-kDa breakdown product of muscle metabolism and is the most commonly used filtration marker and indicator of renal function. However, its measurement suffers from a variety of analytical interferences and standardization problems. Such non-GFR determinants include age, sex, and ethnicity. Muscle mass and dietary protein intake can also affect creatinine concentrations; both these factors are often concomitant with exercise levels. In a population where muscle wasting and inadequate physical activity and protein intake is problematic, we feel it is important to highlight the critique of creatinine-based eGFR in CKD, and how creatinine can be influenced by difference factors, principally muscle mass, and exercise. We also examine the role of cystatin C (CysC) and its role as a confirmatory biomarker in these patients