Powerful Medical Receives €40 Million IPCEI Grant — read the full story

Powerful Medical
1. August 2025
3 min to read

Accuracy of cath lab activation decisions for STEMI-equivalent and mimic ECGs: Physicians vs. AI (PMcardio, queen of hearts)

Overview

This study aimed to measure physician accuracy for interpreting STEMI-equivalent and STEMI-mimic ECGs for catheterization laboratory activation (CLA) and compare their performance to a machine learning-based artificial intelligence algorithm, Queen of Hearts AI (QoH AI).

Published in: The American Journal of Emergency Medicine
Published on: 30 July 2025

Background

Accurate ECG interpretation is crucial to identify occlusive myocardial infarction (OMI) to determine the need for immediate catheterization laboratory activation (CLA). STEMI-equivalent and STEMI-mimic ECG patterns deviate from conventional STEMI criteria, risking misclassification of OMI cases. The diagnostic accuracy for these complex ECGs is unknown.

Methods

Fifty-three EPs and 42 cardiologists interpreted 18 ECGs (eight STEMI-equivalents, eight STEMI-mimics, with one STEMI, and a normal ECG as controls) to determine the presence of OMI requiring immediate CLA. The same ECGs were analyzed by QoH AI. Interpretations were compared against a reference standard based on angiography, troponin, echocardiography, and clinical follow-up.

Results

Interpretation accuracies were similar between EPs and cardiologists (65.6 %, 95 % CI [51, 78]; 65.5 %, 95 % CI [51, 77], respectively; p = 0.969), and significantly lower than QoH AI (88.9 %, 95 % CI [82, 93]) vs. physicians overall, 65.6 %, 95 % CI [52, 77]; p < 0.001). Physicians most frequently misclassified de Winter, Transient STEMI, Hyperacute T-wave OMI, and bundle branch block ECGs. QoH AI only misclassified left bundle branch block with OMI and left ventricular aneurysm without OMI.

Conclusion

Physicians frequently misinterpret STEMI-equivalent and STEMI-mimic ECGs, potentially impacting CLA decisions. QoH AI demonstrated superior accuracy, suggesting a potential to reduce missed OMIs and unnecessary catheterization laboratory activations. Prospective studies are needed to validate these findings in clinical practice.

Accuracy of cath lab activation decisions for STEMI-equivalent and mimic ECGs: Physicians vs. AI (PMcardio, queen of hearts)
Authors: Steven Shroyer M.D., Sumeru Mehta M.D. M.P.H, Nandish Thukral M.D.
Kyle Smiley M.D., Nathaniel Mercaldo PhD, H. Pendell Meyers M.D., Stephen W. Smith M.D. 

Author-Logo_PM
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.

Share this article

Relevant Publications

AI-Enhanced Electrocardiogram for Detection of Occlusive Myocardial Infarction in High-Risk Non–ST-Segment Elevation Acute Coronary Syndrome

This study evaluates an AI-enhanced ECG model for detecting occlusive myocardial infarction (OMI) in patients with high-risk non–ST-segment elevation acute coronary syndrome, using angiography as the reference. The model improved rule-in accuracy with high specificity (78%) and reduced false-positive cath lab activations compared with standard care, while rule-out sensitivity remained limited on the initial ECG. Serial ECG analysis improved detection, supporting the use of AI as a triage aid alongside clinical judgment rather than a standalone diagnostic tool.

Detecting Occlusion Myocardial Infarction with an AI-Powered ECG Model: A Retrospective Cohort Study

This study investigates the clinical utility of personalized medicine approaches in a specific disease context, focusing on identifying relevant biomarkers, patient characteristics, and tailored management strategies. The authors highlight how integrating clinical, molecular, and patient-specific data can improve diagnosis, risk stratification, and treatment selection, while also addressing current limitations such as heterogeneity of evidence and challenges in implementation. Overall, the findings emphasize the growing role of precision medicine in optimizing outcomes and supporting more individualized, data-driven clinical decision-making.

Join over 100,000 healthcare professionals who are already taking advantage of AI

Discover the future of medical work with us.

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.