Clinical Implications of Estimating Glomerular Filtration Rate with Three Different Equations Among Older People. Preliminary Results of the Project "Screening for Chronic Kidney Disease among Older People across Europe (SCOPE)"

Abstract

We aimed at investigating to what extent CKD may be staged interchangeably by three different eGFR equations in older people, and evaluating the source of discrepancies among equations in a population of 2257 patients older than 75 years enrolled in a multicenter observational study. eGFR was calculated by CKD-EPI, BIS and FAS equations. Statistical analysis was carried out by Bland-Altman analysis. κ statistic was used to quantify the agreement between equations in classifying CKD stages. The impact of selected variables on the difference among equations was graphically explored. The average difference between BIS and FAS was -0.24 (95% limits of agreement (95%LA = -4.64-4.14) mL/min/1.73 m². The difference between CKD-EPI and BIS and between CKD-EPI and FAS was 8.97 (95%LA = -2.90-20.84) and 8.72 (95%LA = -2.11-19.56) mL/min/1.73 m², respectively. As regards CKD stage classification, κ value was 0.47 for both CKD-EPI vs. FAS and CKD-EPI vs. BIS, while BIS and FAS had similar classificatory properties (κ = 0.90). Muscle mass was found related to the difference between CKD-EPI and BIS (R² = 0.11) or FAS (R² = 0.14), but not to the difference between BIS and FAS. In conclusion, CKD-EPI and BIS/FAS equations are not interchangeable to assess eGFR among older people. Muscle mass may represent a relevant source of discrepancy among eGFR equations.

Keywords: Berlin Initiative Study (BIS); Full Age Spectrum (FAS); chronic kidney disease (CKD); estimated glomerular filtration rate (eGFR); muscle mass; older patients; sarcopenia; sex.

Figure 1

Crude correlations among eGFR equations (panels A,B,C) and Bland–Altman analysis (Panels D,E,F). Figure 1 shows the correlation of GFR values obtained when applying different equations for eGFR calculation. When testing CKD-EPI values towards the dynamic for BIS and FAS equations in the SCOPE cohort (Panels E,F), a relevant bias of 8.97 mL/min/1.73 m² for the BIS equation and 8.72 mL/min/1.73 m² for the FAS equation was detected, while the bias was much lower (−0.24 mL/min/1.73 m²). Negative values may be explained by the methodology chosen to plot the distribution of values.

Figure 2

Graphical analysis of the impact of BMI (panels A–C), physical performance (Panels D–F) and muscle mass* (Panels G–I) on the difference among eGFR equations studied. *N = 1462. Figure 2 shows the graphic analysis referring to the point distribution of selected study variables in relation to the difference between two equations and the correlation of BMI, SPPB and muscle mass on different calculation models of glomerular filtration rate. The choice of design was adapted on the basis of the regression curve best fitting the distribution of values. As may be seen from the figure, there is no impact of BMI and physical performance quantified by SPPB in this model on sensitivity of BIS and FAS related calculation models as well as CKD-EPI including in the models. Muscle mass seems to have no impact in models including FAS and BIS (panel D), however, as soon as CKD-EPI is included muscle mass is negatively correlated to eGFR values (CKD-EPI and BIS; R² = 0.14 panel H-CKD-EPI and BIS; R² = 0.11 panel I).