Accurate assessment of kidney function is critical to evaluate living kidney donors. Direct glomerular filtration rate measurement using isotopes is currently the gold standard but it is complex and costly. We evaluated the performance of surrogate markers of the glomerular filtration rate in living kidney donors by comparing direct measurement of the rate to the creatinine based equation estimated rate, the kidney volume based estimated rate using a newly developed equation and creatinine clearance. We first statistically compared direct glomerular filtration rate measurement to the results of the Modification of Diet in Renal Disease (MDRD) and Chronic Kidney Disease-Epidemiology Collaboration (CKD-EPI) creatinine based equations, and to creatinine clearance in 54 potential renal donors from 2006 to 2010. In 32 donors with cross-sectional computerized tomography available we used measured functional renal volume with age, gender, weight and serum creatinine to estimate the rate based on kidney volume according to a previously reported model. Kidney volume based measurement was compared to direct glomerular filtration rate measurement and assessed against the results of the best performing creatinine based equation. In the first group of 54 donors the correlation index of the estimated glomerular filtration rate according to MDRD and CKD-EPI creatinine based equations, and to creatinine clearance was low compared to direct measurement. In the subset of 32 potential donors the kidney volume based estimated rate correlated better with direct measurement than MDRD equation results with higher accuracy (estimated 87.5% and 75.0% within 30% and 10% of direct rate measurement, respectively). To estimate the glomerular filtration rate in healthy individuals a volume based model correlated better than the MDRD equation, which is the best performing creatinine based equation used to estimate the rate. By providing a more robust estimation of the glomerular filtration rate in healthy potential kidney donors, the volume based model adds value to routine preoperative computerized tomography above that of anatomical evaluation.
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