Journal
REVIEWS IN CARDIOVASCULAR MEDICINE
Volume 23, Issue 3, Pages -Publisher
IMR PRESS
DOI: 10.31083/j.rcm2303091
Keywords
cardiovascular complications; liver transplantation; heart failure; cirrhotic cardiomyopathy; arrhythmias; ventricular dys-function
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This review discusses the factors that contribute to the development of major adverse cardiovascular events (MACE) after liver transplantation and explores methods for predicting these events in the post-transplant period. It reviews the roles of metabolic syndrome, renal dysfunction, non-alcoholic fatty liver disease, diagnostic tests such as imaging and biomarkers, as well as parameters such as systolic and diastolic dysfunction, and QT interval prolongation in cardiovascular events. The review also summarizes the current literature on scoring systems for predicting cardiovascular events.
The curative therapy for patients with end-stage liver disease is liver transplantation. However, liver transplantation challenges the cardiovascular system, and is associated with major adverse cardiovascular events (MACE). Immediately after implantation of the liver graft, changes in cardiac preload and afterload increase the cardiac workload. Longer-term postoperatively, a more sedentary lifestyle and enhanced appetite increase obesity and body mass index. Immunosuppressants may also affect the cardiovascular system. All these factors that liver recipients encounter impact the function of the cardiovascular system. Cardiac events are the third-leading cause of death in liver recipients. This review describes the pertinent factors that predispose to development of MACE after liver transplantation, and how to predict these cardiovascular events in the post-transplant period. We review the roles of metabolic syndrome, renal dysfunction, non-alcoholic fatty liver disease, diagnostic tests such as imaging and biomarkers, and parameters such as systolic and diastolic dysfunction, and QT interval prolongation in cardiovascular events. We summarize the current literature on scoring systems to predict cardiovascular events.
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