Comparison of the MDRD and the CKD-EPI equations to estimate the glomerular filtration rate in the general population.
OBJECTIVE
The Chronic Kidney Disease Epidemiology Collaboration (CDK-EPI) equation has been proposed as a replacement for the Modification of Diet in Renal Disease (MDRD) equation to estimate the glomerular filtration rate, but this equation has not yet been evaluated in the general population.


METHODS
Cross-sectional analysis of a random sample of 858 participants from the general population aged 50-75 years without known kidney disease. The prevalence of low eGFR (< 60 mL/min/1.73 m(2)) was assessed with the MDRD and the CKD-EPI equations in the overall sample and in normoalbuminuric individuals.


RESULTS
With the MDRD equation the median eGFRs (interquartile range) in men/women were 63.3(12.2)/56.7(9.4)mL/min/1.73 m(2), and with the CKD-EPI equation 66.6(14.2)/61.3(11.6) mL/min/1.73 m(2). The prevalence of low eGFR in men/women was 35.2%/68.5% and 25.1%/45.7% with the MDRD and the CKD-EPI equations, respectively. Normoalbuminuric women without risk factors for CKD experienced the most pronounced reduction in the number of cases with low eGFR with the CKD-EPI equation. The prevalence of renal impairment in this subgroup still remained even greater than that in men with diabetes, hypertension, or cardiovascular disease.


CONCLUSIONS
Compared with the MDRD, the CKD-EPI equation generates a substantial reduction in the prevalence of renal impairment in subjects with diabetes, hypertension, cardiovascular disease, and in subjects without risk factors. The prevalence of renal impairment in normoalbuminuric females may be still overestimated with the CKD-EPI equation.
Internal Medicine Department, Hospital Virgen del Camino, Sanlúcar de Barrameda, Cádiz, Spain. a.lopez.ssl@gmail.com
Alejandro
A
López-Suárez
Manuel
M
Beltrán-Robles
Javier
J
Elvira-González
Fernando
F
Fernández-Palacín
Antonio
A
Bascuñana-Quirell
Julio
J
Benítez-Del-Castillo
Pablo
P
Gómez-Fernández
D000368:Aged; D000419:Albuminuria / Q000097:blood / Q000453:epidemiology / Q000503:physiopathology; D000465:Algorithms; D002318:Cardiovascular Diseases / Q000097:blood / Q000453:epidemiology / Q000503:physiopathology; D015897:Comorbidity; D003404:Creatinine / Q000097:blood; D003430:Cross-Sectional Studies; D048909:Diabetes Complications / Q000097:blood / Q000453:epidemiology / Q000503:physiopathology; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D006973:Hypertension / Q000097:blood / Q000453:epidemiology / Q000503:physiopathology; D007674:Kidney Diseases / Q000097:blood / Q000453:epidemiology / Q000503:physiopathology; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D015995:Prevalence; D012307:Risk Factors; D012494:Sampling Studies; D012907:Smoking / Q000097:blood / Q000453:epidemiology / Q000503:physiopathology
D003404:Creatinine