©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Nephrol. Jul 6, 2015; 4(3): 345-353
Published online Jul 6, 2015. doi: 10.5527/wjn.v4.i3.345
Published online Jul 6, 2015. doi: 10.5527/wjn.v4.i3.345
Estimating glomerular filtration rate in kidney transplantation: Still searching for the best marker
Josefina Santos, La Salete Martins, Nephrology and Transplant Department, Centro Hospitalar do Porto, Hospital de Santo António, 4099-001 Porto, Portugal
Author contributions: Both authors contributed equally to this article.
Conflict-of-interest statement: The authors have read and understood BPG policy on declaration of interests and declare that they have no competing interests.
Correspondence to: Josefina Santos, MD, Nephrology and Transplant Department, Centro Hospitalar do Porto, Hospital de Santo António, Largo Prof. Abel Salazar, 4099-001 Porto, Portugal. josefina.sts@gmail.com
Telephone: +351-22-2074685 Fax: +351-22-2033189
Received: January 26, 2015
Peer-review started: January 28, 2015
First decision: March 6, 2015
Revised: May 6, 2015
Accepted: May 7, 2015
Article in press: May 8, 2015
Published online: July 6, 2015
Processing time: 161 Days and 13 Hours
Peer-review started: January 28, 2015
First decision: March 6, 2015
Revised: May 6, 2015
Accepted: May 7, 2015
Article in press: May 8, 2015
Published online: July 6, 2015
Processing time: 161 Days and 13 Hours
Core Tip
Core tip: An accurate evaluation of allograft function is essential in the management of kidney transplant. Glomerular filtration rate (GFR), is generally considered the best index of graft function. Endogenous markers, such as serum creatinine or cystatin C, are used to estimate kidney function, and equations using these markers adjusted to other variables, are an attempt to improve accuracy in estimation of GFR. This article will review and discuss the performance and limitations of these endogenous markers and their equations as estimators of GFR in the kidney transplant recipients, and their ability in predicting clinical outcomes.