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- Theodor Baars, Ursula Neumann, Mona Jinawy, Stefanie Hendricks, Jan-Peter Sowa, Julia Kälsch, Mona Riemenschneider, Guido Gerken, Raimund Erbel, Dominik Heider, and Ali Canbay.
- From the Department for Cardiology, West German Heart and Vascular Centre Essen, University Hospital, University Duisburg-Essen, Essen, Germany (TB, MJ, SH, RE); Department of Bioinformatics, Straubing Center of Science, University of Applied Science Weihenstephan-Triesdorf, Straubing, Germany (UN, MR, DH); and Department of Gastroenterology and Hepatology, University Hospital, University Duisburg-Essen (J-PS, JK, GG, AC), Essen, Germany.
- Medicine (Baltimore). 2016 Feb 1; 95 (6): e2807e2807.
AbstractDetection of high-risk subjects in acute myocardial infarction (AMI) by noninvasive means would reduce the need for intracardiac catheterization and associated complications. Liver enzymes are associated with cardiovascular disease risk. A potential predictive value for liver serum markers for the severity of stenosis in AMI was analyzed.Patients with AMI undergoing percutaneous coronary intervention (PCI; n = 437) were retrospectively evaluated. Minimal lumen diameter (MLD) and percent stenosis diameter (SD) were determined from quantitative coronary angiography. Patients were classified according to the severity of stenosis (SD ≥ 50%, n = 357; SD < 50%, n = 80). Routine heart and liver parameters were associated with SD using random forests (RF). A prediction model (M10) was developed based on parameter importance analysis in RF.Age, alkaline phosphatase (AP), aspartate aminotransferase (AST), and MLD differed significantly between SD ≥ 50 and SD < 50. Age, AST, alanine aminotransferase (ALT), and troponin correlated significantly with SD, whereas MLD correlated inversely with SD. M10 (age, BMI, AP, AST, ALT, gamma-glutamyltransferase, creatinine, troponin) reached an AUC of 69.7% (CI 63.8-75.5%, P < 0.0001).Routine liver parameters are associated with SD in AMI. A small set of noninvasively determined parameters can identify SD in AMI, and might avoid unnecessary coronary angiography in patients with low risk. The model can be accessed via http://stenosis.heiderlab.de.
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