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Related Experiment Video

Updated: Jun 10, 2026

Physiology Lab Demonstration: Glomerular Filtration Rate in a Rat

Physiology Lab Demonstration: Glomerular Filtration Rate in a Rat

Published on: July 26, 2015

Estimating glomerular filtration rate in a population-based study.

Anoop Shankar¹, Kristine E Lee, Barbara E K Klein

¹Department of Community Medicine, West Virginia University School of Medicine, Morgantown, WV 26506, USA. ashankar@hsc.wvu.edu

Vascular Health and Risk Management

|August 24, 2010

Summary

Commonly used equations like MDRD and Cockcroft-Gault may overestimate chronic kidney disease (CKD) prevalence in general populations. The Mayo equation provides a more accurate CKD prevalence estimate in healthy adults.

Keywords:

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

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Last Updated: Jun 10, 2026

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Area of Science:

Nephrology
Epidemiology
Biostatistics

Background:

Glomerular filtration rate (GFR) estimating equations are crucial for determining chronic kidney disease (CKD) prevalence.
Concerns exist that widely used GFR equations, developed in CKD patient cohorts, may overestimate GFR in healthy individuals.
Limited research compares the impact of various GFR equations on CKD prevalence in general populations.

Purpose of the Study:

To compare the prevalence of CKD estimated by different GFR equations in a general population sample.
To evaluate the accuracy of commonly used GFR equations (MDRD, Cockcroft-Gault, Mayo) against a cystatin C-based definition of CKD.

Main Methods:

Analysis of a population-based sample of adults aged 43-86 years from Wisconsin.
Comparison of CKD prevalence (GFR <60 mL/min per 1.73 m(2)) using Modification of Diet in Renal Disease (MDRD), Cockcroft-Gault (CG), and Mayo equations.
Validation against CKD definition using cystatin C levels >1.23 mg/L.

Main Results:

CKD prevalence varied significantly across GFR equations: MDRD (17.2%), CG (16.5%), and Mayo (4.8%).
MDRD and CG equations exhibited high false-positive rates for CKD, with only 24% of individuals in the 50-59 mL/min per 1.73 m(2) range having elevated cystatin C.
The Mayo equation showed a higher concordance with cystatin C, with 62.8% of individuals in the 50-59 mL/min per 1.73 m(2) range having elevated cystatin C.

Conclusions:

The MDRD and CG equations, currently standard for GFR estimation, appear to overestimate CKD prevalence in the general population.
The Mayo equation demonstrates better performance in identifying true CKD in a general population compared to MDRD and CG.
Rethinking the standard GFR equations for CKD prevalence estimation in healthy populations is warranted.