Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction

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 p...

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Autores principales:	Theodor Baars, Jan-Peter Sowa, Ursula Neumann, Stefanie Hendricks, Mona Jinawy, Julia Kälsch, Guido Gerken, Tienush Rassaf, Dominik Heider, Ali Canbay
Formato:	article
Lenguaje:	EN
Publicado:	Termedia Publishing House 2019
Materias:	liver enzymes percutaneous coronary intervention non-invasive prediction troponin Medicine R
Acceso en línea:	https://doaj.org/article/08464551f1f64ee48708edfc6e9c22a9
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spelling	oai:doaj.org-article:08464551f1f64ee48708edfc6e9c22a92021-12-02T19:15:42ZLiver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction1734-19221896-915110.5114/aoms.2018.75678https://doaj.org/article/08464551f1f64ee48708edfc6e9c22a92019-12-01T00:00:00Zhttps://www.archivesofmedicalscience.com/Liver-parameters-as-part-of-a-non-invasive-model-for-prediction-of-all-cause-mortality,75581,0,2.htmlhttps://doaj.org/toc/1734-1922https://doaj.org/toc/1896-9151Introduction 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 selection (EFS) and logistic regression. Correlations were performed for serum parameters. Results Age (73; 64; p < 0.01), alanine aminotransferase (ALT; 93 U/l; 40 U/l; p < 0.01), aspartate aminotransferase (AST; 162 U/l; 66 U/l; p < 0.01), C-reactive protein (CRP; 4.7 U/l; 1.6 U/l; p < 0.01), creatinine (1.6; 1.3; p < 0.01), -glutamyltransferase (GGT; 71 U/l; 46 U/l; p < 0.01), urea (29.5; 20.5; p < 0.01), estimated glomerular filtration rate (eGFR; 49.6; 61.4; p < 0.01), troponin (13.3; 7.6; p < 0.01), myoglobin (639; 302; p < 0.01), and cardiovascular risk factors (hypercholesterolemia p < 0.02, family history p < 0.01, and smoking p < 0.01) differed significantly between non-survivors and survivors. Age, AST, CRP, eGFR, myoglobin, sodium, urea, creatinine, and troponin correlated significantly with death (r = –0.29; 0.14; 0.31; –0.27; 0.20; –0.13; 0.33; 0.24; 0.12). A prediction model was built including age, CRP, eGFR, myoglobin, and urea, achieving an AUROC of 77.6% to predict long-term survival after AMI. Conclusions Non-invasive parameters, including liver and renal markers, can predict long-term outcome of patients after AMI.Theodor BaarsJan-Peter SowaUrsula NeumannStefanie HendricksMona JinawyJulia KälschGuido GerkenTienush RassafDominik HeiderAli CanbayTermedia Publishing Housearticleliver enzymespercutaneous coronary interventionnon-invasive predictiontroponinMedicineRENArchives of Medical Science, Vol 16, Iss 1, Pp 71-80 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	liver enzymes percutaneous coronary intervention non-invasive prediction troponin Medicine R
spellingShingle	liver enzymes percutaneous coronary intervention non-invasive prediction troponin Medicine R Theodor Baars Jan-Peter Sowa Ursula Neumann Stefanie Hendricks Mona Jinawy Julia Kälsch Guido Gerken Tienush Rassaf Dominik Heider Ali Canbay Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction
description	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 selection (EFS) and logistic regression. Correlations were performed for serum parameters. Results Age (73; 64; p < 0.01), alanine aminotransferase (ALT; 93 U/l; 40 U/l; p < 0.01), aspartate aminotransferase (AST; 162 U/l; 66 U/l; p < 0.01), C-reactive protein (CRP; 4.7 U/l; 1.6 U/l; p < 0.01), creatinine (1.6; 1.3; p < 0.01), -glutamyltransferase (GGT; 71 U/l; 46 U/l; p < 0.01), urea (29.5; 20.5; p < 0.01), estimated glomerular filtration rate (eGFR; 49.6; 61.4; p < 0.01), troponin (13.3; 7.6; p < 0.01), myoglobin (639; 302; p < 0.01), and cardiovascular risk factors (hypercholesterolemia p < 0.02, family history p < 0.01, and smoking p < 0.01) differed significantly between non-survivors and survivors. Age, AST, CRP, eGFR, myoglobin, sodium, urea, creatinine, and troponin correlated significantly with death (r = –0.29; 0.14; 0.31; –0.27; 0.20; –0.13; 0.33; 0.24; 0.12). A prediction model was built including age, CRP, eGFR, myoglobin, and urea, achieving an AUROC of 77.6% to predict long-term survival after AMI. Conclusions Non-invasive parameters, including liver and renal markers, can predict long-term outcome of patients after AMI.
format	article
author	Theodor Baars Jan-Peter Sowa Ursula Neumann Stefanie Hendricks Mona Jinawy Julia Kälsch Guido Gerken Tienush Rassaf Dominik Heider Ali Canbay
author_facet	Theodor Baars Jan-Peter Sowa Ursula Neumann Stefanie Hendricks Mona Jinawy Julia Kälsch Guido Gerken Tienush Rassaf Dominik Heider Ali Canbay
author_sort	Theodor Baars
title	Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction
title_short	Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction
title_full	Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction
title_fullStr	Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction
title_full_unstemmed	Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction
title_sort	liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction
publisher	Termedia Publishing House
publishDate	2019
url	https://doaj.org/article/08464551f1f64ee48708edfc6e9c22a9
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Liver parameters as part of a non-invasive model for prediction of all-cause mortality after myocardial infarction

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