Ulster University Logo

Ulster Institutional Repository

Improved detection of acute myocardial infarction using a diagnostic algorithm based on calculated epicardial potentials

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Owens, C, Navarro, C, McClelland, A, Riddell, J, Escalona, OJ, Anderson, JMCC and Adgey, JAA (2006) Improved detection of acute myocardial infarction using a diagnostic algorithm based on calculated epicardial potentials. INTERNATIONAL JOURNAL OF CARDIOLOGY, 111 (2). pp. 292-301. [Journal article]

[img]PDF - Published Version
Restricted to Repository staff only

403Kb

DOI: 10.1016/j.ijcard.2005.09.050

Abstract

Background: New methods for detecting myocardial infarction in patients with suspected acute coronary syndromes are needed particularly in an era where the majority of patients with myocardial infarction present with non-diagnostic 12-lead electrocardiograms (ECG). We compared a novel epicardial diagnostic algorithm using epicardial potentials from the 80-lead body surface map with other electrocardiographic techniques in detection of myocardial infarction. Methods: Between February 1999 and February 200 1, consecutive patients (n = 427) with ischemic type chest pain had an initial 12-lead ECG and body surface map recorded. Detecting myocardial infarction using an epicardial algorithm was first performed in a training set (n = 213) and tested in a validation set of patients (n = 214). The results from this epicardial algorithm in myocardial infarction detection were compared with the physician's interpretation of the 12-lead ECG, the body surface map algorithm (PRIME (TM)) and physician's interpretation of the body surface map. Results: Myocardial infarction occurred in 205 patients (creatine kinase >= 2 x upper limit of normal with creatine kinase-MB >= 7% CK). The physician's interpretation of the 12-lead ECG identified 122 with myocardial infarction (sensitivity 60%, specificity 99%), the body surface map algorithm 137 (sensitivity 67%, specificity 89%), the physician's interpretation of the body surface map 153 (sensitivity 75%, specificity 91%) and the epicardial algorithm 158 (sensitivity 77% specificity 99%). Combining the physician's interpretation of the 12-lead ECG with the epicardial algorithm increased significantly the detection of myocardial infarction (sensitivity 85%, specificity 98%, p < 0.001) compared with the 12-lead ECG. Conclusions: An epicardial algorithm based on epicardial potentials increases significantly the detection of myocardial infarction particularly among those with non-diagnostic 12-lead ECG's. (c) 2005 Elsevier Ireland Ltd. All rights reserved.

Item Type:Journal article
Keywords:myocardial infarction; epicardial algorithm; ventricular hypertrophy; epicardial potentials
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Engineering
Research Institutes and Groups:Engineering Research Institute > Nanotechnology & Integrated BioEngineering Centre (NIBEC)
ID Code:6014
Deposited By:Professor Omar Escalona
Deposited On:14 Jan 2010 09:18
Last Modified:07 Apr 2014 14:41

Repository Staff Only: item control page