Liver Parameters As Part of a Non-Invasive Model for Prediction of All-Cause Mortality After Myocardial Infarction
Clinical research Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction Theodor Baars1, Jan-Peter Sowa2, Ursula Neumann3, Stefanie Hendricks1, Mona Jinawy1, Julia Kälsch2, Guido Gerken2, Tienush Rassaf1, Dominik Heider3,4, Ali Canbay2 1Department for Cardiology, West German Heart and Vascular Centre Essen, Corresponding author: University Hospital, University Duisburg-Essen, Essen, Germany Prof. Ali Canbay MD 2Department of Gastroenterology and Hepatology, University Hospital, Department University Duisburg-Essen, Essen, Germany of Gastroenterology 3Department of Bioinformatics, Straubing Center of Science, University of Applied and Hepatology Science Weihenstephan-Triesdorf, Straubing, Germany University Hospital 4Department of Mathematics and Computer Science, University of Marburg, Marburg, University Duisburg-Essen Germany Leipzigerstr. 44 39120 Magdeburg Submitted: 9 June 2017 Essen, Germany Accepted: 29 June 2017 Phone: +49 3916713100 E-mail: ali.canbay@med. Arch Med Sci 2020; 16 (1): 71–80 ovgu.de DOI: https://doi.org/10.5114/aoms.2018.75678 Copyright © 2018 Termedia & Banach Abstract Introduction: Liver parameters are associated with cardiovascular disease risk and severity of stenosis. It is unclear whether liver parameters could predict the long-term outcome of patients after acute myocardial infarction (AMI). We performed an unbiased analysis of the predictive value of serum parameters for long-term prognosis after AMI. Material and methods: In a retrospective, observational, single-center, cohort study, 569 patients after AMI were enrolled and followed up until 6 years for major adverse cardiovascular events, including cardiac death. Patients were classified into non-survivors (n = 156) and survivors (n = 413). Demographic and laboratory data were analyzed using ensemble feature se- lection (EFS) and logistic regression.
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