Performance of the MDRD, CKD-EPI, and Cockcroft-Gault Formulas in Relation to Nutritional Status in Stable Renal Transplant Recipients

Transplant Proc. 2016 Jun;48(5):1494-7. doi: 10.1016/j.transproceed.2016.01.083.

Abstract

Background: Monitoring of the function of the implanted kidney in renal transplant recipients (RTRs) is one of the superior elements of adequate therapeutic actions. The aim of this study was to assess the conventional and unconventional factors affecting the estimated glomerular filtration rate (eGFR) with the Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), and Cockcroft-Gault (C-G) formulas among the RTRs.

Methods: The study included 144 RTRs (mean age 52 years). Clinical and laboratory data were analyzed; eGFR was calculated with MDRD, CKD-EPI, and C-G formulas. We compared the results with MDRD as a reference calculating the percentage of reclassifications of chronic kidney disease (CKD) stages. Nutritional status was assessed with a body composition analyzer, Tanita BC 418.

Results: Multivariable linear regression analysis with MDRD and CKD-EPI formula as a dependent variable retained the following independent predictors: hemoglobin (Hb) (B = .365; P = .000), and red blood cell distribution width (RDW) (B = -.191; P = .024). Analysis of variance showed the existence of statistically significant differences (all P for trend <.05) between the CKD-EPI, MDRD, and C-G equations within the total scope of eGFR results (51.2 ± 21.2 vs 47.5 ± 18.7 vs 55.6 ± 20.6, respectively) as well as in quartiles of eGFR.

Conclusions: Our data indicate that (1) with a value of eGFR >60 mL/min/1.73 m(2), the MDRD formula shows values that are on average 11% lower than in the CKD-EPI and C-G formulas; (2) with a value of eGFR <60 mL/min/1.73 m(2), the MDRD and CKD-EPI formulas do not show statistically significant differences.

MeSH terms

  • Adult
  • Aged
  • Female
  • Glomerular Filtration Rate*
  • Humans
  • Kidney / physiopathology
  • Kidney Transplantation*
  • Linear Models
  • Male
  • Middle Aged
  • Nutritional Status*
  • Regression Analysis
  • Transplant Recipients