PMcardio receives FDA Breakthrough Device Designation — read the full story
Powerful Medical
9. November 2023
3 min to read

Diagnostic Accuracy of a Smartphone Application for Artificial Intelligence-based Interpretation of 12-lead ECG in Primary Care (AMSTELHEART-1)

Overview:

Accurately interpreting 12-lead ECGs in primary care can be challenging for clinicians due to limited training, time constraints, and variability in expertise. This study validated the PMcardio Core AI ECG Model for AI-driven ECG analysis, demonstrating 86% sensitivity and 92% specificity for major abnormalities, along with near-perfect accuracy for atrial fibrillation, highlighting its potential to enhance early case detection.

Published In: European Heart Journal
Presented Date: November 9, 2023

Background

The use of 12-lead electrocardiogram (ECG) is common in routine primary care, however it can be difficult for less experienced ECG readers to adequately interpret the ECG.

We sought to validate a novel smartphone application as a stand-alone interpretation tool for 12-lead ECG in primary care.

Methods

We recruited consecutive patients who underwent 12-lead ECG as part of routinely indicated primary care in the Netherlands. All ECGs were assessed by a smartphone application that analyses a photographed image of a 12-lead ECG for automated interpretation, installed on an Android platform and an iOS platform.

We validated the application for detecting: 1) any major ECG abnormality (MEA, primary outcome) defined as atrial fibrillation/flutter (AF), markers of (past) myocardial ischemia or clinically relevant impulse and/or conduction abnormalities; or 2) AF (key secondary outcome). The reference standard was a blinded expert panel.

Results

We included 290 patients from 11 Dutch general practices with median age 67 (IQR 55-74) years, 48% were female. On reference ECG, 71 patients (25%) had MEA, 35 (12%) had AF. The app’s sensitivity and specificity for MEA were 86% (95%CI:76-93) and 92% (95%CI:87-95), respectively.

For AF, sensitivity and specificity were 97% (95%CI:85-100) and 99% (95%CI:97-100), respectively. Performance was comparable between Android and iOS platform (Kappa=0.95, 95%CI:0.91-0.99 and Kappa=1.00, 95%CI:1.00-1.00 for MEA and AF, respectively).

Conclusion

A smartphone application that interprets photographed 12-lead ECG images had good diagnostic accuracy in a primary care setting for major ECG abnormalities, and near-perfect properties for diagnosing AF.

Authors: J C L Himmelreich, R E Harskamp
 

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

Artificial Intelligence Based Detection of Acute Coronary Occlusion Compared to STEMI Criteria – External Validation Study in a Consecutive All-Comer German Chest Pain Unit Cohort

2nd place - DGK Young Investigator Awards 2025, Germany: In a real-world cohort of over 4,000 chest pain patients presenting to a German CPU, excluding obvious STEMI heart attacks diagnosed before arrival, an AI ECG model detected serious artery blockages (ACO) with 97.8% accuracy. It outperformed traditional STEMI criteria, achieving higher sensitivity (70.2% vs 28.8%) and fewer false positives.

Precordial Swirl Sign: A New ECG Pattern of Left Anterior Descending Artery Occlusion Myocardial Infarction

This study identifies the novel “precordial swirl sign,” a distinct ECG pattern that can uncover critical LAD coronary artery blockages often missed by standard STEMI criteria. It offers a promising step toward earlier and more accurate detection of high-risk heart attacks.

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