New equations to estimate GFR in children with CKD

Abstract

The Schwartz formula was devised in the mid-1970s to estimate GFR in children. Recent data suggest that this formula currently overestimates GFR as measured by plasma disappearance of iohexol, likely a result of a change in methods used to measure creatinine. Here, we developed equations to estimate GFR using data from the baseline visits of 349 children (aged 1 to 16 yr) in the Chronic Kidney Disease in Children (CKiD) cohort. Median iohexol-GFR (iGFR) was 41.3 ml/min per 1.73 m(2) (interquartile range 32.0 to 51.7), and median serum creatinine was 1.3 mg/dl. We performed linear regression analyses assessing precision, goodness of fit, and accuracy to develop improvements in the GFR estimating formula, which was based on height, serum creatinine, cystatin C, blood urea nitrogen, and gender. The best equation was: GFR(ml/min per 1.73 m(2))=39.1[height (m)/Scr (mg/dl)](0.516) x [1.8/cystatin C (mg/L)](0.294)[30/BUN (mg/dl)](0.169)[1.099](male)[height (m)/1.4](0.188). This formula yielded 87.7% of estimated GFR within 30% of the iGFR, and 45.6% within 10%. In a test set of 168 CKiD patients at 1 yr of follow-up, this formula compared favorably with previously published estimating equations for children. Furthermore, with height measured in cm, a bedside calculation of 0.413*(height/serum creatinine), provides a good approximation to the estimated GFR formula. Additional studies of children with higher GFR are needed to validate these formulas for use in screening all children for CKD.

Figure 1.

Analysis of log-transformed height/Scr and iGFR, showing that 65.0% of the variation in log(iGFR) can be explained by log(height/Scr). Regression line and nonparametric spline depicted by dashed curve are superimposed.

Figure 2.

Analysis of log-transformed 1.8/cystatin C and iGFR, showing that 47.3% of the variation in log(iGFR) can be explained by the reciprocal of cystatin C. Regression line and nonparametric spline depicted by dashed curve are superimposed.

Figure 3.

Analysis of log-transformed 30/BUN and iGFR showing that 39.0% of the variation in log(iGFR) can be explained by the reciprocal of BUN concentration. Regression line and nonparametric spline depicted by dashed curve are superimposed.

Figure 4.

Bland-Altman plot of observed iGFR and model III eGFR in a testing data set of 168 individuals in the CKiD study.