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Powerful Medical
17. January 2025
3 min to read

ECG Patterns of Occlusion Myocardial Infarction: a Narrative Review

Overview:

This comprehensive review highlights the limitations of the traditional STEMI/NSTEMI classification for heart attacks and advocates for a more precise approach to diagnosis and patient triage. Instead of relying solely on standard ECG criteria, this method focuses on ECG patterns that more accurately reflect the severity of underlying coronary vessel disease.

By identifying high-risk ECG changes beyond current STEMI guidelines, clinicians can detect heart attacks earlier, initiate treatment faster, and ultimately improve patient outcomes.

Introduction:

The traditional management of acute coronary syndrome has relied on the identification of ST-segment elevation myocardial infarction (STEMI) as a proxy of acute coronary occlusion. This conflation of STEMI with acute coronary occlusion has historically overshadowed non–ST-segment elevation myocardial infarction (NSTEMI), despite evidence suggesting 25% to 34% of NSTEMI cases may also include acute coronary occlusion.

Current limitations in the STEMI/NSTEMI binary framework underscore the need for a revised approach to chest pain and acute coronary syndrome management.

The emerging paradigm distinguishing occlusion myocardial infarction from nonocclusion myocardial infarction (NOMI) seeks to enhance diagnostic accuracy and prognostic effect in acute coronary syndrome care.

This approach not only emphasizes the urgency of reperfusion therapy for high-risk ECG patterns not covered by current STEMI criteria, but also emphasizes the broader transition from viewing acute coronary syndrome as a disease defined by the ECG to a disease defined by its underlying pathology, for which the ECG is an important but insufficient surrogate test.

This report outlines the emerging occlusion myocardial infarction paradigm, detailing specific ECG patterns linked to acute coronary occlusion, and proposes a new framework that could enhance triage accuracy and treatment strategies for acute coronary syndrome.

Although further validation is required, the occlusion myocardial infarction pathway holds promise for earlier acute coronary occlusion detection, timely cath lab activation, and improved myocardial salvage—offering potentially significant implications for both clinical practice and future research in acute coronary syndrome management.

Authors List:

Fabrizio Ricci, MD, PhD; Chiara Martini, MD; Davide Maria Scordo, MD; Davide Rossi, MD; Sabina Gallina, MD; Artur Fedorowski, MD, PhD; Luigi Sciarra, MD; C. Anwar A. Chahal, MD, PhD; H. Pendell Meyers, MD; Robert Herman, MD; Stephen W. Smith, MD

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Powerful Medical leads one of the most important shifts in modern medicine by augmenting human-made clinical decisions with artificial intelligence. Our primary focus is on cardiovascular diseases, the world’s leading cause of death.

About PMcardio

PMcardio is a CE-certified AI that reads ECGs and offers a complex assessment of 49 cardiac conditions. Clinically validated in 15+ studies and trusted by over 100,000 clinicians, it delivers rapid, expert‑level interpretations, empowering emergency physicians, GPs, nurses, paramedics, and cardiologists to act with confidence at the point of care. Available for Individuals and Organizations.

About Powerful Medical

Established in 2017, Powerful Medical has embarked on a mission to revolutionize the diagnosis and treatment of cardiovascular diseases. We are a medical company backed by 28 world-class cardiologists and led by our expert Scientific Board with decades of experience in daily patient care, clinical research, and medical devices. The results of our research are implemented, developed, certified, and brought to market by our 50+ strong interdisciplinary team of physicians, data scientists, AI experts, software engineers, regulatory specialists, and commercial teams.

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Relevant Publications

Artificial intelligence-enhanced ECG detection of acute coronary occlusion in chest pain patients with ST-elevation in lead aVR – A direct comparison to conventional ECG criteria

In a single‑centre retrospective study of 145 consecutive emergency‑department patients whose first ECG showed ≥1 mm ST‑elevation in lead aVR, investigators compared conventional electrocardiographic rules with a deep‑learning classifier (PMcardio “Queen of Hearts”) for recognising an acute coronary occlusion (ACO). Angiography and biomarker adjudication proved ACO in 19 patients (13 %). At an optimised probability threshold, the AI system achieved an area‑under‑the‑ROC curve of 0.918, detected 63 % of occlusions, and—crucially—generated no false‑positive calls in the 54‑patient rule‑out subgroup. By contrast, classic STEMI millimetre criteria identified only one in four occlusions and would have prompted between four and fourteen unnecessary emergency catheterisations.

AI-enhanced recognition of occlusions in acute coronary syndrome (AERO-ACS): a retrospective study

In a one‑year, single‑centre cohort of 217 cath‑lab patients (72 STEMI, 145 NSTEMI), the AERO‑ACS study tested PMcardio’s AI ECG against traditional ST‑elevation rules for detecting angiographic occlusion‑MI. The algorithm matched STEMI sensitivity (86.5 % vs 83.3 %) while raising specificity to 82.2 % (vs 66.0 %), achieved 100 % sensitivity in STEMI cases, and flagged occlusions linked to a 12‑fold higher in‑hospital mortality risk—suggesting more accurate triage with fewer unnecessary activations.

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