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BACKGROUND AND OBJECTIVES: The Modification of Diet in Renal Disease (MDRD) study equation and the Cockcroft-Gault (CG) equation perform poorly in the (near-) normal range of GFR. Whether this is due to the level of GFR as such or to differences in individual characteristics between healthy individuals and patient with chronic kidney disease (CKD) is unknown. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We evaluated the performance of MDRD, CG per BSA (CG/(BSA)) and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations compared with measured GFR (mGFR; I-iothalamate) at 4 months before and 2 months after donation in 253 consecutive living kidney donors. RESULTS: mGFR declined from 103 ± 15 to 66 ± 11 ml/min per 1.73 m(2) after donation. All equations underestimated mGFR at both time points. Arithmetic performance analysis showed improved performance after donation of all equations, with significant reduction of bias after donation. Expressed as percentage difference, mGFR-estimated GFR (eGFR) bias was reduced after donation only for CG/(BSA). Finally, in 295 unselected individuals who were screened for donation, mGFR was below the cutoff for donation of 80 ml/min per 1.73 m(2) in 19 individual but in 166, 98, and 74 for MDRD, CDK-EPI, and CG/(BSA), respectively. CONCLUSIONS: A higher level of GFR as such is associated with larger absolute underestimation of true GFR by eGFR. For donor screening purposes, eGFR should be interpreted with great caution; when in doubt, true GFR should be performed to prevent unjustified decline of prospective kidney donors.

Original publication

DOI

10.2215/CJN.08761209

Type

Journal article

Journal

Clin J Am Soc Nephrol

Publication Date

11/2010

Volume

5

Pages

1960 - 1968

Keywords

Adult, Biomarkers, Blood Pressure, Body Surface Area, Body Weight, Chronic Disease, Creatinine, Donor Selection, Female, Glomerular Filtration Rate, Health Status Indicators, Humans, Iothalamic Acid, Kidney, Kidney Diseases, Kidney Transplantation, Living Donors, Male, Middle Aged, Models, Biological, Netherlands, Predictive Value of Tests, Regression Analysis, Sex Factors, Time Factors, Treatment Outcome