Universal GFR determination based on two time points during plasma iohexol disappearance

Abstract

An optimal measurement of glomerular filtration rate (GFR) should minimize the number of blood draws, and reduce procedural invasiveness and the burden to study personnel and cost, without sacrificing accuracy. Equations have been proposed to calculate GFR from the slow compartment separately for adults and children. To develop a universal equation, we used 1347 GFR measurements from two diverse groups consisting of 527 men in the Multicenter AIDS Cohort Study and 514 children in the Chronic Kidney Disease in Children cohort. Both studies used nearly identical two-compartment (fast and slow) protocols to measure GFR. To estimate the fast component from markers of body size and of the slow component, we used standard linear regression methods with the log-transformed fast area as the dependent variable. The fast area could be accurately estimated from body surface area by a simple parameter (6.4/body surface area) with no residual dependence on the slow area or other markers of body size. Our equation measures only the slow iohexol plasma disappearance curve with as few as two time points and was normalized to 1.73 m2 body surface area. It is of the form: GFR=slowGFR/[1+0.12(slowGFR/100)]. In a random sample utilizing a third of the patients for validation, there was excellent agreement between the calculated and measured GFR with low root mean square errors being 4.6 and 1.5 ml/min per 1.73 m2 for adults and children, respectively. Thus, our proposed simple equation, developed in a combined patient group with a broad range of GFRs, may be applied universally and is independent of the injected amount of iohexol.

Figures

Figure 1

Figure 1a. Relationships between fast area, BSA, and slow area. Regression of fast area (y axis) on body surface area (x axis) in the log scale for the combined MACS and CKiD training dataset. The dashed line represents the nonparametric spline. Figure 1b. Non-relationship of residuals from the regression of fast area on body surface area presented in Figure 1A (y axis) and slow area (x axis) from the training dataset.

Figure 1

Figure 1a. Relationships between fast area, BSA, and slow area. Regression of fast area (y axis) on body surface area (x axis) in the log scale for the combined MACS and CKiD training dataset. The dashed line represents the nonparametric spline. Figure 1b. Non-relationship of residuals from the regression of fast area on body surface area presented in Figure 1A (y axis) and slow area (x axis) from the training dataset.

Figure 2

Relationship between GFR0,2 (x axis) and (GFR0,2/GFR2,2) −1 (y axis) in the log scale, for the combined MACS and CKiD training dataset. The equation, (GFR0,2/GFR2,2) − 1= 0.12 x (GFR0,2/100), is depicted as the solid line.

Figure 3

Comparison of GFR^2,2 based on GFR0,2 and proposed equation with four-point GFR2,2 in the validation datasets for MACS (n=177) and CKiD (n=274). Percentile (2.5th, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97.5th) box plots showing a high agreement within each study validation dataset.