skip to content
Dovepress - Open Access to Scientific and Medical Research
View our mobile site

8121

Estimating glomerular filtration rate in a population-based study

Original Research

(1700) Views  (528) Full article downloads

Authors: Anoop Shankar, Kristine E Lee, Barbara EK Klein, et al

Published Date July 2010 Volume 2010:6 Pages 619 - 627
DOI: http://dx.doi.org/10.2147/VHRM.S11269

Anoop Shankar1, Kristine E Lee2, Barbara EK Klein2, Paul Muntner3, Peter C Brazy4, Karen J Cruickshanks2,5, F Javier Nieto5, Lorraine G Danforth2, Carla R Schubert2,5, Michael Y Tsai6, Ronald Klein2

1Department of Community Medicine, West Virginia University School of Medicine, Morgantown, WV, USA; 2Department of Ophthalmology and Visual Sciences, 4Department of Medicine, 5Department of Population Health Sciences, University of Wisconsin, School of Medicine and Public Health, Madison, WI, USA; 3Department of Community Medicine, Mount Sinai School of Medicine, NY, USA; 6Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA

Background: Glomerular filtration rate (GFR)-estimating equations are used to determine the prevalence of chronic kidney disease (CKD) in population-based studies. However, it has been suggested that since the commonly used GFR equations were originally developed from samples of patients with CKD, they underestimate GFR in healthy populations. Few studies have made side-by-side comparisons of the effect of various estimating equations on the prevalence estimates of CKD in a general population sample.

Patients and methods: We examined a population-based sample comprising adults from Wisconsin (age, 43–86 years; 56% women). We compared the prevalence of CKD, defined as a GFR of <60 mL/min per 1.73 m2 estimated from serum creatinine, by applying various commonly used equations including the modification of diet in renal disease (MDRD) equation, Cockcroft–Gault (CG) equation, and the Mayo equation. We compared the performance of these equations against the CKD definition of cystatin C >1.23 mg/L.

Results: We found that the prevalence of CKD varied widely among different GFR equations. Although the prevalence of CKD was 17.2% with the MDRD equation and 16.5% with the CG equation, it was only 4.8% with the Mayo equation. Only 24% of those identified to have GFR in the range of 50–59 mL/min per 1.73 m2 by the MDRD equation had cystatin C levels >1.23 mg/L; their mean cystatin C level was only 1 mg/L (interquartile range, 0.9–1.2 mg/L). This finding was similar for the CG equation. For the Mayo equation, 62.8% of those patients with GFR in the range of 50–59 mL/min per 1.73 m2 had cystatin C levels >1.23 mg/L; their mean cystatin C level was 1.3 mg/L (interquartile range, 1.2–1.5 mg/L). The MDRD and CG equations showed a false-positive rate of >10%.

Discussion: We found that the MDRD and CG equations, the current standard to estimate GFR, appeared to overestimate the prevalence of CKD in a general population sample.

Keywords: chronic kidney disease, glomerular filtration rate, MDRD equation, Cockcroft–Gault equation, Mayo equation




 

Other articles by Dr Anoop Shankar

Perfluoroalkyl chemicals and elevated serum uric acid in US adults
  • Join ISVH

    Be part of the World's leading experts in vascular health by joining the International Society of Vascular Health (ISVH)

  • Testimonials

    "... I was impressed at the rapidity of publication from submission to final acceptance." Dr Edwin Thrower, PhD, Yale University