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Artificial intelligence-enhanced six-lead portable electrocardiogram device for detecting left ventricular systolic
Jaehyun Lim1, Hak Seung Lee2,3, Ga In Han2,3
1Division of Cardiology and Cardiovascular Centre, Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Artificial intelligence-electrocardiogram (AI-ECG) models using portable devices show effectiveness in detecting left ventricular systolic dysfunction (LVSD). This AI-ECG approach demonstrates accuracy comparable to traditional 12-lead ECG for early LVSD screening.
Area of Science:
- Cardiology
- Artificial Intelligence
- Medical Devices
Background:
- Left ventricular systolic dysfunction (LVSD) is a critical condition requiring early detection.
- Portable electrocardiogram (ECG) devices integrated with artificial intelligence (AI) offer potential for remote and accessible cardiac assessments.
- The real-world effectiveness of AI-ECG models from portable devices for LVSD detection needs validation.
Purpose of the Study:
- To evaluate the diagnostic performance of an AI-ECG model using a six-lead portable device for detecting LVSD.
- To compare the accuracy of the portable AI-ECG model with a conventional 12-lead ECG-based AI-ECG model.
- To assess the potential of portable AI-ECG devices for early LVSD screening.
Main Methods:
- A prospective, single-centre study involving patients aged 19 years and older undergoing six-lead ECG recording during transthoracic echocardiography.
- Retraining of a previously validated 12-lead AI-ECG model to interpret six-lead ECG inputs from a hand-held portable device (AliveCor KardiaMobile 6L).
- Primary outcome was the area under the receiver operating characteristic curve (AUROC) for LVSD detection (ejection fraction < 40%).
Main Results:
- The AI-ECG model using the six-lead portable device achieved an AUROC of 0.924 (95% CI 0.903-0.944), with 83.4% sensitivity and 88.7% specificity.
- The AI-ECG model based on the conventional 12-lead ECG showed an AUROC of 0.962 (95% CI 0.947-0.977), with 90.1% sensitivity and 91.1% specificity.
- A total of 1635 patients were included in the final analysis, with 163 diagnosed with LVSD.
Conclusions:
- The AI-ECG model utilizing a six-lead hand-held portable ECG device effectively identifies LVSD.
- The diagnostic accuracy of the portable AI-ECG model is comparable to that of the conventional 12-lead ECG.
- Portable AI-ECG devices hold significant potential as efficient tools for early LVSD screening.
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