Study demonstrates MyoVista® wavECG™ ability to cost-effectively detect LV Dysfunction
SOUTHLAKE, Texas, August 18, 2020 – HeartSciences, a medical device company focused on advancing the field of electrocardiology through innovation, announced today the results of a multicenter prospective study conducted at 4 centers in North America enrolling a total of 1,202 subjects. The study was supported in part by funds from HeartSciences and the National Science Foundation. The results are provided at online JACC.org and will be published in the August 25, 2020 issue of Journal of the American College of Cardiology (JACC), a peer-reviewed journal in cardiovascular medicine. The participating centers are The Icahn School of Medicine, Mount Sinai Hospital, New York, NY, The West Virginia University (WVU) Heart and Vascular Institute, Morgantown, WV, The Windsor Cardiac Centre, Windsor, Ontario, Canada and the David Geffen School of Medicine at UCLA, Los Angeles, California.
The article titled “Machine Learning Assessment of Left Ventricular Diastolic Function Based on Electrocardiographic Features” presents the results from evaluating the feasibility of MyoVista® wavECGTM Technology to provide quantitative estimates related to myocardial relaxation that can be used to identify left ventricular diastolic dysfunction (LVDD). Diastolic dysfunction is recognized as playing a major role in the pathophysiology of heart failure. Heart disease is a global pandemic affecting at least 26 million people worldwide and continues to increase in prevalence due to increasing life expectancy in the general population. New tools are needed that can assist in identifying patients earlier while also lowering costs for health systems around the world.
The study was performed using machine learning analysis often described as artificial intelligence or AI. Machine-learning models were developed to estimate e’ (e-prime) using signal-processed ECG features, traditional ECG features and clinical information. Patients from 3 institutions (n= 814) formed a development cohort and were randomly divided into training and internal test sets (80:20). Data from the fourth institution was reserved as an external test set (n = 388) to evaluate model performance.
The study results demonstrated that the estimated e’ values discriminated the guideline-recommended thresholds for abnormal myocardial relaxation, LVDD and systolic dysfunction (LV ejection fraction) with an AUC of 0.84, 0.80, and 0.81 respectively in the external test set. Moreover, the estimated e’ allowed prediction of LV diastolic dysfunction based on multiple age and sex-adjusted reference limits with an AUC of 0.94 in the external test set.
Conclusions of the study include: “This cost-effective strategy may be a valuable first clinical step for assessing the presence of LV dysfunction and potentially aid in the early diagnosis and management of heart failure patients” and “This novel approach has the potential to serve as a cost-effective screening tool for early detection of LVDD.”
Partho Sengupta, MD, Professor, Chief of Cardiology and Chair of Cardiac Innovation, WVU Heart & Vascular Institute, the principal investigator commented “The study focused on developing a quantitative estimation of a key echocardiographic measure. The results demonstrate a potentially significant new role for electrocardiography in cardiac testing and reducing overall healthcare costs”
“This large-scale study using MyoVista wavECG Technology, demonstrates that new LV dysfunction detection capabilities developed using advanced signal processing and AI can provide improved low-cost testing for heart disease.” stated Mark Hilz, President and CEO of HeartSciences.
Andrew Simpson, Chairman of HeartSciences, stated “This study indicates that HeartSciences MyoVista wavECGs innovative technology has the capability and opportunity to bridge the diagnostic gap in heart disease”.
HeartSciences sits at the forefront of innovation and technological development focused on advancing the field of electrocardiology to provide early heart disease detection. Its first product, the MyoVista® Wavelet ECG (wavECG™) Cardiac Testing Device, is a resting 12-lead electrocardiograph that uses AI and continuous wavelet transform (CWT) signal processing to provide cardiac information associated with left ventricular diastolic disfunction (LVDD), a condition which has previously not been possible to detect using conventional electrocardiology. LVDD is associated with almost all forms and co-morbidities of heart disease and may include hypertension, diabetes, valvular disease, ischemia, and reduced systolic function among others.
The MyoVista Device additionally provides all the information and capabilities of a full-featured conventional resting 12-lead ECG within the same test and follows the same clinical AHA/IEC lead placement protocol.
HeartSciences is a privately held U.S. corporation based in Southlake, Texas.
The MyoVista Device is not currently FDA cleared and is not available in the United States.
For more information visit www.heartsciences.com.
HeartSciences’ AI-ECG products are currently in development and not commercially available in the United States.
wavECG and wavEKG are trademarks of HeartSciences.
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