Affiliations 

  • 1 Department of Medicine, Nephrology Unit, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
  • 2 Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
  • 3 Department of Public Health, Universiti Kebangsaan Malaysia Medical Centre, Kuala Lumpur, Malaysia
  • 4 Department of Radiology, National Heart Institute, Kuala Lumpur, Malaysia
Saudi J Kidney Dis Transpl, 2019 6 30;30(3):587-596.
PMID: 31249222 DOI: 10.4103/1319-2442.261331

Abstract

Estimation of glomerular filtration rate (GFR) in renal transplant patients is often assessed by application of creatinine-based equations. The aim was to correlate the estimated GFR (eGFR) using creatinine-based equations [Cockroft-Gault, Modification of Diet in Renal Disease (MDRD), Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI), Nankivell] with gold standard 51Cr-EDTA in kidney transplant patients in the Asian population. This is a single-center, cross-sectional study involving adult renal transplant patients. Background demographic data, medications, office blood pressure, and baseline investigations were taken. Correlations between measured GFR and eGFR were analyzed and Pearson's correlation coefficients, bias, and accuracy were assessed. Thirty-seven renal transplant patients with a mean age of 46 ± 13 years were recruited. Majority were Chinese (68%), Malay (24%), and Indian (8%). The median duration of the transplant was 84 (interquartile range 60,132) months. The mean measured GFR was 71 ± 21 mL/min/1.73 m2. Cockroft-Gault and CKD-EPI has the best correlation with 51Cr-EDTA with Pearson correlation coefficients of 0.733 (P <0.001) and 0.711 (P < 0.001), respectively. All formulae showed >80% accuracy with eGFR lies between 30% of the measured value. CKD-EPI and MDRD had the greatest accuracy with 89.2% each. Clinician may use any of these three serum creatinine-based equations to estimate GFR in kidney transplant recipients.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.