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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

An AI Model for Electrocardiogram Detection of Occlusion Myocardial Infarction: A Retrospective Study to Reduce False Positive Cath Lab Activations

This single-centre retrospective study examined whether an AI-powered ECG model (PMcardio’s Queen of Hearts OMI model) can better detect acute occlusion myocardial infarction (OMI) and reduce false-positive cardiac catheterization laboratory (CCL) activations compared with traditional STEMI millimetre criteria. The authors analysed 304 consecutive STEMI pathway activations over a 2-year period at a tertiary academic centre and applied the AI model to pre-angiography 12-lead ECGs, comparing its performance against standard STEMI criteria. The AI model showed higher sensitivity (89.2% vs 68.3%), higher specificity (72.9% vs 51.7%), greater overall accuracy (82.9% vs 61.8%), and a high AUROC of 0.884 for identifying true OMI, while correctly flagging nearly three-quarters of false-positive activations as non-OMI. These findings suggest that integrating a specialized AI-ECG model into existing STEMI alert pathways could meaningfully reduce unnecessary CCL activations without compromising the detection of true occlusions.

Bifascicular Block Associated With Myocardial Infarction: A Marker of Proximal Left Anterior Descending Artery Occlusion Confirmed by the Artificial Intelligence-Based Smartphone App Queen of Hearts

This single-patient case report describes an elderly man presenting with chest pain, hypotension, and bifascicular block (BFB)—a combination of right bundle branch block (RBBB) and left anterior fascicular block (LAFB)—whose ECG showed QRS‑concordant anterior and lateral ST‑segment elevation consistent with a STEMI‑equivalent / occlusive myocardial infarction (OMI) pattern. Urgent coronary angiography revealed a long, severely calcified, near‑occlusive proximal left anterior descending (LAD) artery lesion, successfully treated with primary PCI and drug‑eluting stent implantation, achieving TIMI 3 flow. The Queen of Hearts (PMcardio) AI‑based smartphone app correctly classified the ECG as STEMI‑equivalent, identified atrial flutter and BFB, and predicted reduced left ventricular ejection fraction, later confirmed by echocardiography (EF 38%). This case underscores BFB with concordant anterior ST elevation as a high‑risk marker of proximal LAD‑culprit OMI and provides anecdotal evidence that specialized AI‑enabled ECG interpretation can support rapid, accurate decision‑making in ACS. 

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