Electrocardiographic classification of acute coronary syndromes: a review by a committee of the International Society for Holter and Non-Invasive Electrocardiology☆

The electrocardiogram (ECG) remains the most immediately accessible and widely used diagnostic tool for guiding emergency treatment strategies. The ECG recorded during acute myocardial ischemia is of diagnostic, therapeutic, and prognostic significance. In patients with myocardial ischemia as a result of decreased blood supply, the initial 12-lead ECG typically shows (1) predominant ST-segment elevation (STE) as part of STE acute coronary syndrome (STE-ACS), or (2) no predominant STE, that is, non–STE ACS (NSTE-ACS). Patients with predominant STE are classified as having either aborted myocardial infarction (MI) or ST-elevation MI (STEMI) based on the absence or presence of biomarkers of myocardial necrosis. The MI may be aborted either by spontaneous or therapeutic reperfusion of the ischemic myocardium before development of myocardial cell necrosis. NSTE-ACS patients are classified as having either unstable angina or NSTE-MI, based also on the absence or presence of biomarkers of mycardial necrosis.

The information obtained from the 12-lead ECG at presentation should be complemented by repeated ECGs especially during symptoms indicative of ischemia and, if applicable, by comparing the findings with reference ECGs. Also, continuous ECG recording in a coronary care setting, including the comparison of ECGs with and without pain, adds to the information gained at patient presentation.

In this article, mechanisms of ischemic ECG changes and the ECG patterns recorded in both STE-ACS and NSTE-ACS are described. ECG patterns of NSTE-ACS, which include ST depression, negative T wave, and even normal ECG, need to be better defined in future studies to correlate them with the severity and extent of ischemia and to explore to what extent they are explained by acute active ischemia or represent consequences of ischemia. One of the aims of this article is to propose a classification of the ECG patterns encountered in different clinical scenarios of ACS. How these patterns will aid in guiding the diagnostic and therapeutic process is discussed.