Retrospective Cohort Study
Copyright ©The Author(s) 2017. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Transplant. Feb 24, 2017; 7(1): 49-56
Published online Feb 24, 2017. doi: 10.5500/wjt.v7.i1.49
Cardiovascular disease: Risk factors and applicability of a risk model in a Greek cohort of renal transplant recipients
Nikolaos-Andreas Anastasopoulos, Evangelia Dounousi, Evangelos Papachristou, Charalampos Pappas, Eleni Leontaridou, Eirini Savvidaki, Dimitrios Goumenos, Michael Mitsis
Nikolaos-Andreas Anastasopoulos, Evangelia Dounousi, Michael Mitsis, Department of Medicine, School of Health Sciences, University of Ioannina, 45110 Ioannina, Greece
Nikolaos-Andreas Anastasopoulos, Evangelia Dounousi, Charalampos Pappas, Michael Mitsis, Renal Transplant Unit, University Hospital of Ioannina, 45500 Ioannina, Greece
Charalampos Pappas, Department of Nephrology, University Hospital of Ioannina, 45500 Ioannina, Greece
Evangelos Papachristou, Eleni Leontaridou, Eirini Savvidaki, Dimitrios Goumenos, School of Health Science, University of Patras, 26504 Patras, Greece
Evangelos Papachristou, Eleni Leontaridou, Eirini Savvidaki, Dimitrios Goumenos, Department of Nephrology and Transplantation, Patras University Hospital, 26504 Patras, Greece
Author contributions: Anastasopoulos NA performed the study, collected data, wrote the paper; Dounousi E designed the study, analyzed data, wrote the paper; Papachristou E contributed important reagents; Pappas C contributed important reagents; Leontaridou E and Savvidaki E collected data; Goumenos D contributed important reagents; Mitsis M designed the study, contributed important reagents.
Institutional review board statement: The study was reviewed and approved by the Institutional Scientific Council and the Review Board of the University General Hospital of Ioannina, 6th District Health (Peloponnese, Ionian Islands, Epirus and Western Greece), Greece. All patients provided written inform consent.
Informed consent statement: All participants were informed of the study and its anonymity and provided written informed consent prior to study enrolment.
Conflict-of-interest statement: The authors declare no conflict of interest.
Data sharing statement: Technical appendix, statistical code, and dataset available from the corresponding author at evangeldou@gmail.com. Patients’ consent on sharing data was not obtained but the presented data are anonymized and risk of identification is low.
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: Evangelia Dounousi, MD, PhD, Department of Medicine, School of Health Sciences, University of Ioannina, Stavrou Niarchou Avenue, 45110 Ioannina, Greece. evangeldou@gmail.com
Telephone: +30-26-51099653 Fax: +30-26-51099890
Received: August 25, 2016
Peer-review started: August 26, 2016
First decision: October 20, 2016
Revised: December 14, 2016
Accepted: January 2, 2017
Article in press: January 4, 2017
Published online: February 24, 2017
Processing time: 180 Days and 13.4 Hours
Core Tip

Core tip: Cardiovascular disease being the leading cause of death with a functioning graft following renal transplantation. The aim of this study was to investigate the incidence and the determinants of cardiovascular morbidity in prevalent Greek renal transplant recipients (RTRs) expressed as major adverse cardiac event (MACE) rate. Additionally, we examined the applicability of a recently developed risk prediction model in our population. According to our results older age of recipient and pre-existing cardiovascular disease were the main risk factors for MACE. The applied risk model can be used for risk stratification in this database of RTRs.