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Detection of acute ischemia episodes from QRS angles changes using a laplacian noise model

Abstract:

Ischemia detectors represent a useful diagnosis tool to identify acute ischemic episodes in coronary artery disease patients. In this paper, a detector of acute ischemic events based on the analysis of the QRS angles is presented. This acute ischemia detector has been developed by modelling the ischemia-induced changes in the QRS angles as an abrupt change with a certain transition time, assuming a Laplacian noise-model. The standard 12-lead electrocardiogram was used to test the proposed detector. For such proposal, we analyzed 79 patients undergoing a PCI procedure during about 5-min occlusion duration in one of the major coronary artery (LAD=25. RCA=38 and LCX= 16). The three detector at the groups of patients presented good outcomes in terms of sensitivity and specificity achieving up to Se=72.7%. Sp=95.5% in the LAD group. Se=75.2%, Sp=97.2% in the RCA group and Se=72.2%, Sp=100%. in the LCX group. We conclude that the QRS angles can be used as a trigger for detecting acute myocardial ischemia although this must be further validated with other contexts in which ischemic events occur more gradually.