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DOI: https://doi.org/10.22263/2312-4156.2026.4.29

V.A. Lollini, S.V. Lollini
Modern ECG patterns of occlusion myocardial infarction: what general practitioners need to know
Vitebsk State Order of Peoples’ Friendship Medical University, Vitebsk, Republic of Belarus

Vestnik VGMU. 2026;25(4):29-36.

Abstract.
Objectives. To systematize current electrocardiographic patterns of occlusion myocardial infarction (OMI) as a practical guide for general practitioners to reduce diagnostic errors and improve patient outcomes. Material and methods. An analytical review of the literature from 2008 to 2025 was conducted using PubMed, Scopus, and eLibrary databases. Original studies, meta-analyses, and clinical guidelines on ECG diagnosis of acute coronary occlusion without ST-segment elevation were analyzed. Data on the prevalence, sensitivity, specificity, and anatomical associations of each pattern were synthesized. Results. Traditional STEMI criteria fail to detect 30-40% of acute coronary occlusions. Six major OMI ECG patterns are described: de Winter (upsloping ST depression + tall T waves in V1–V6; sensitivity 80%, specificity 95-99%), Aslanger 30 (ST elevation in III and aVR with depression in V4–V6), Wellens’ syndrome (biphasic or deep negative T waves in V2– V3 in the pain-free period), South African flag sign (elevation in I, aVL, V2), shark fin (monomorphic elevation with QRS deformation), and modified Sgarbossa criteria for left bundle branch block. Detection of any of these patterns in a patient with anginal pain is a direct indication for emergency coronary angiography without waiting for troponin results. Delayed diagnosis of OMI increases in-hospital mortality by 2–3 times and one-year mortality up to 18.1% vs. 9.9% for verified STEMI. Conclusions. Implementation of the OMI ECG pattern recognition algorithm into clinical practice reduces decision-toreperfusion time and improves outcomes in patients with acute coronary syndrome. The integration of artificial intelligence into ECG analysis for automated detection of occlusion patterns is the most promising direction.

Keywords: occlusion myocardial infarction, electrocardiography, de Winter pattern, Wellens' syndrome, Aslanger pattern, STEMI equivalents, acute coronary occlusion, artificial intelligence.

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Submitted 11.05.2026
Accepted 27.08.2026

Information about authors:

V.A. Lollini – Doctor of Medical Sciences, Professor, Professor of the Department of Hospital Therapy and Cardiology with the Advanced Training and Refresher Course, Vitebsk State Order of Peoples’ Friendship Medical University.
Svetlana V. Lollini – Candidate of Biological Sciences, Associate Professor, Head of the Department of Pathological Physiology, Vitebsk State Order of Peoples’ Friendship Medical University, email: Этот адрес электронной почты защищён от спам-ботов. У вас должен быть включен JavaScript для просмотра. .

 

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