Diagnostic Advances
Copyright ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Methodol. Sep 26, 2017; 7(3): 73-92
Published online Sep 26, 2017. doi: 10.5662/wjm.v7.i3.73
Establishing the presence or absence of chronic kidney disease: Uses and limitations of formulas estimating the glomerular filtration rate
Ahmed Alaini, Deepak Malhotra, Helbert Rondon-Berrios, Christos P Argyropoulos, Zeid J Khitan, Dominic S C Raj, Mark Rohrscheib, Joseph I Shapiro, Antonios H Tzamaloukas
Ahmed Alaini, Christos P Argyropoulos, Mark Rohrscheib, Division of Nephrology, Department of Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87131, United States
Deepak Malhotra, Division of Nephrology, Department of Medicine, University of Toledo School of Medicine, Toledo, OH 43614-5809, United States
Helbert Rondon-Berrios, Renal and Electrolyte Division, Department of Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, United States
Zeid J Khitan, Division of Nephrology, Department of Medicine, Joan C. Edwards School of Medicine, Huntington, WV 25701, United States
Dominic S C Raj, Division of Nephrology, Department of Medicine, George Washington University, Washington, DC 20037, United States
Joseph I Shapiro, Marshall University Joan C. Edwards School of Medicine, Huntington, WV 25701, United States
Antonios H Tzamaloukas, Nephrology Section, Medicine Service, Raymond G. Murphy VA Medical Center, Albuquerque, NM 87108, United States
Antonios H Tzamaloukas, Department of Medicine, University of New Mexico School of Medicine, Albuquerque, NM 87108, United States
Author contributions: Alaini A, Rondon-Berrios H and Argyropoulos CP reviewed the literature and wrote parts of the report; Malhotra D reviewed the literature and made critical changes in the manuscript; Khitan ZJ added important revisions and constructed figures; Raj DSC made critical additions to the report; Rohrscheib M reviewed the literature and made important additions to this report; Shapiro JI made important revisions and constructed figures; Tzamaloukas AH conceived this report and wrote parts of it.
Conflict-of-interest statement: Dominic S C Raj is supported by RO1 DK073665-01A1, 1U01DK099914-01 and IU01DK09924-01 from the National Institutes of Health. Joseph I Shapiro is supported by HL105649, HL071556 and HL109015 from the National Institutes of Health. The rest of the authors declare no conflicts of interest. This report was not supported by a grant.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Antonios H Tzamaloukas, MD, MACP, Nephrology Section, Medicine Service, Raymond G. Murphy VA Medical Center, 1501 San Pedro, SE, Albuquerque, NM 87108, United States. antonios.tzamaloukas@va.gov
Telephone: +1-505-2651711-4733 Fax: +1-505-2566441
Received: January 31, 2017
Peer-review started: February 6, 2017
First decision: March 6, 2017
Revised: May 17, 2017
Accepted: May 30, 2017
Article in press: May 31, 2017
Published online: September 26, 2017
Processing time: 237 Days and 4.1 Hours
Core Tip

Core tip: Detection of the presence and severity of chronic kidney disease (CKD) is currently based on estimates of glomerular filtration rate based on serum creatinine and cystatin C concentrations plus factors that affect the rate of production of these two biomarkers, and on albuminuria. This scheme has improved detection of CKD and monitoring its course and the effects of therapeutic interventions. However, the scheme’s performance in detecting early stages of CKD and in predicting its course is poor, in general. Research in this field is directed towards finding better biomarkers of glomerular filtration rate and, particularly, biomarkers indicating early injury of the renal tissues.