In Acute Myocardial Infarction Liver Parameters Are Associated With Stenosis Diameter. Issue 6 (February 2016)

• Record Type: Journal Article
• Authors: Baars, Theodor; Neumann, Ursula; Jinawy, Mona; Hendricks, Stefanie; Sowa, Jan-Peter; Kälsch, Julia; Riemenschneider, Mona; Gerken, Guido; Erbel, Raimund; Heider, Dominik; Canbay, Ali
• Other Names: Gotthardt. Daniel section editor.
• Is Part Of: Medicine. Volume 95:Issue 6(2016)
• Publication Date: 2016-02
• Subjects: Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000002807
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: Detection 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 viahttp://stenosis.heiderlab.de . Abstract : Supplemental Digital Content is available in the text