Powerful Medical
16. May 2024
3 min to read

Single Center Retrospective Validation of an Artificial Intelligence ECG Model Detecting Acute Coronary Occlusion

Overview:

In this single-center US-based cohort study of emergency department patients with suspected heart attacks, the PMcardio STEMI AI ECG Model outperformed standard STEMI criteria, improving detection sensitivity by 30%. Patients correctly identified by AI but missed by cardiologists faced notable treatment delays (~22 hours), underscoring the AI’s potential to enable faster diagnosis and earlier intervention.

Published In: Heart Rhythm
Presented Date: May 16, 2024

Background

STEMI criteria have low sensitivity to detect acute coronary occlusion myocardial infarction (OMI). The Queen of Hearts (QOH) is an artificial intelligence (AI) model developed by Powerful Medical (Bratislava, Slovakia) which has been shown to outperform STEMI criteria for detection of OMI. Performance in all-comer chest pain populations is not known.

We evaluated QOH in our center in consecutive patients presenting to the emergency department (ED) with suspected acute coronary syndrome (ACS).

Methods

We reviewed patients who presented to our ED in October 2023 with suspected ACS. We included patients who ruled out by serial troponin or underwent angiography. Primary outcome of OMI was defined as culprit artery with TIMI flow 0-2 or culprit artery with TIMI flow 3 and high sensitivity troponin I > 5000 ng/L. Secondary outcome was door-to-device time (D2D). QOH outputs an AI interpretation (OMI or not OMI) and confidence level (low, mid, or high). We considered OMI with mid or high confidence to be positive. For cardiologist over-read, we considered “acute MI” to be positive. We compared sensitivity using Fisher’s exact test, specificity and accuracy using Chi square, and D2D using Student’s t-test.

Results

Among 528 patients, 498 (94.3%) ruled out and 31 (17.0%) had angiography. OMI outcome was met in 10 (1.9%) and was not met in 518 (98.1%). Comparing QOH to cardiologist over-read, sensitivity was 70% vs 40%, (p=0.18), specificity was 99.2% vs 99.4% (p=NS), and accuracy was 98.7% vs 98.3% (p=0.6), respectively. For patients with QOH and cardiologist positive ECG, mean D2D was 86 ± 21 minutes. For patients with QOH positive and cardiologist negative ECG, mean D2D was 1358 ± 452 minutes (p=0.0021).

Conclusion

In our center, QOH ECG interpretation improved sensitivity for OMI by 30% without loss of specificity. QOH could expedite identification of OMI for early intervention.


Authors: William Frick, Issam Atallah, Rabya Saraf, Kuan-Yu Lin, Chien-Jung Lin, Phillip Mar

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 the market leader in AI-powered diagnostics, addressing the world’s leading cause of death – cardiovascular diseases. The innovative clinical assistant empowers healthcare professionals to detect up to 40 cardiovascular diseases. In the form of a smartphone application, the certified Class IIb medical device interprets any 12-lead ECG image in under 5 seconds to provide accurate diagnoses and individualized treatment recommendations tailored to each patient.

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

ECG Patterns of Occlusion Myocardial Infarction: a Narrative Review

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.

Artificial Intelligence–Powered Electrocardiogram Detecting Culprit Vessel Blood Flow Abnormality: AI-ECG TIMI Study Design and Rationale

The AI-ECG TIMI study is a unique, multicenter registry currently enrolling patients to evaluate an AI-powered ECG model for detecting actively obstructed arteries in acute coronary syndrome (ACS). It is the first study to collect standard 12-lead ECGs precisely at the time of coronary angiography, providing novel insights into coronary occlusion and reperfusion. By identifying high-risk ECG patterns and assessing AI’s role in predicting intervention success, it paves the way for AI-driven precision cardiology in acute care.

Join 25,000 healthcare professionals who are already taking advantage of AI