Analytics 4 Life® Presents Early Data Supporting Novel, Non-Invasive Method of Predicting Elevated Left Ventricular Pressure at the American College of Cardiology’s (ACC) 69th Annual Scientific Session Together with World Congress of Cardiology

Analytics 4 Life® Presents Early Data Supporting Novel, Non-Invasive Method of Predicting Elevated Left Ventricular Pressure at the American College of Cardiology’s (ACC) 69th Annual Scientific Session Together with World Congress of Cardiology

RESEARCH TRIANGLE PARK, NC and TORONTO, ON, March 30, 2020 — Analytics 4 Life, a digital health company dedicated to improving existing diagnostic pathways, today reported data for the first time on its heart failure research at the American College of Cardiology’s (ACC) 69th Annual Scientific Session Together with World Congress of Cardiology. The data suggest that a machine-learned approach performs highly in predicting elevated left ventricular end-diastolic pressure (LVEDP) and could potentially serve as a novel, non-invasive diagnostic for identifying patients with elevated filling pressures at point-of-care.

“There is a profound need to reduce cardiovascular disease-related deaths through earlier detection and timely diagnosis with non-invasive testing,” said William E. Sanders, MD, Vice President of Medical Affairs and Chief Medical Officer, Analytics 4 Life. “We are encouraged by these initial results that the CorVista® platform, which has demonstrated feasibility in assessment of coronary artery disease, also has significant clinical promise in identifying patients with impaired left ventricular function at point-of-care.”

Dr. Rola Khedraki, MD, lead author and Cardiology Fellow at Scripps Prebys Cardiovascular Institute, presented early results demonstrating that a machine-learned approach is highly accurate for predicting LVEDP greater than or equal to 20 mmHg. In a study population of 890 patients, the algorithm demonstrated an average AUC of 0.97 for predicting LVEDP with a sensitivity of 94% and specificity of 89%.

Details of the poster presentation at the ACC.20 Virtual Session is as follows:

Title: First-in-man development of a machine learning cardiac phase space analytic approach to predict elevated left ventricular pressures
Presenter: Dr. Rola Khedraki, MD, Cardiology Fellow at Scripps Prebys Cardiovascular Institute
Session Title: Breakthroughs in Cardiac Computational and Imaging Technologies
Authors: Khedraki, R. Burton, T., Cohoon, T., Khosousi, A., Lange, E., Ramchandani, S., Sanders, W., Bhavnani, S.

The presentation can be viewed here.

About the CorVista® System
The CorVista System is a non-invasive cardiac diagnostic platform to diagnose heart disease point-of-care without radiation or cardiac stress. The System acquires patients’ cardiac electrical and blood flow data using its handheld, digital device, processes these data with proprietary machine-learned algorithms, and delivers a report for clinicians in a secure web portal. It is currently being tested in coronary artery disease, heart failure, and pulmonary hypertension. The CorVista System is an investigational device limited by federal law to investigational use and is not available for commercial distribution.

About Analytics 4 Life®
Analytics 4 Life is combining digital health and machine learning to develop a novel, non-invasive cardiac diagnostic modality. With an initial focus on coronary artery disease, heart failure, and pulmonary hypertension, Analytics 4 Life is advancing the CorVista System, a point-of-care, radiation-free, and exercise-free diagnostic platform aimed at improving existing care pathways. Analytics 4 Life is based in Toronto with U.S. headquarters in Research Triangle Park, NC. For more information, visit www.analytics4life.com.

Contacts

Analytics 4 Life
Jon Slebodnick
919-241-8736
info@analytics4life.com

W2Opure
Christiana Pascale
212-257-6722
cpascale@w2ogroup.com

SOURCE: Business Wire