CorVista Health to Present New Data on the Use of Machine Learning as a Non-Invasive Point-of-Care Rule-out Test for Heart Failure at ACC 2024

• New data support the feasibility of machine learned algorithms to detect elevated left ventricular end-diastolic pressure (LVEDP)
• Data collected using the CorVista System®, the world’s first non-invasive point-of-care solution approved for evaluating the presence of coronary artery disease and pulmonary hypertension

BETHESDA, Md.--(BUSINESS WIRE)--CorVista Health, Inc., a leading digital health company dedicated to improving cardiovascular disease diagnosis, will present new data exploring the potential of a Non-Invasive Point-of-Care Rule-out Test for Heart Failure using Machine Learning at the American College of Cardiology 73^rd Annual Scientific Session and Exposition in Atlanta, GA on April 7.

The CorVista System is the world’s first non-invasive point-of-care solution for evaluating the presence of coronary artery disease and pulmonary hypertension. The developmental model to be presented, intended to assess left ventricular end-diastolic pressure (LVEDP), exhibits the potential to serve as an effective rule-out test, with a sensitivity of 92% (≥25 mmHg) and 86% (≥20 mmHg) and specificity of 68% (TTE group), with a negative predictive value of 99.5% (≥25 mmHg) and 99.1% (≥20 mmHg), at a disease prevalence of 4%.

Timely identification of left ventricular dysfunction plays a pivotal role in effective heart failure management, however, measuring elevated LVEDP currently relies on invasive left heart catheterization. While echocardiographic indices can be used to indicate potential diastolic dysfunction, they pose challenges in data collection and interpretation, creating a need for a non-invasive, point-of-care method to identify patients with elevated LVEDP.

“This data exemplifies CorVista Health’s commitment to advancing novel machine learned diagnostic solutions to identify patients with CAD (coronary artery disease), PH (pulmonary hypertension) (both now FDA-cleared) and elevated LVEDP at point of care.” Both PH and elevated LVEDP, particularly when due to Heart Failure with Preserved Ejection Fraction (HFpEF), are vastly underrecognized and underdiagnosed often delaying life-saving treatments” said Charles Bridges, M.D. Sc.D., Executive Vice President and Chief Scientific Officer, CorVista Health. “We believe the CorVista System can uniquely and effectively address these important unmet needs for people living with cardiovascular disease, especially in rural and underserved populations.”

Lead Author	Abstract Title	Presentation Details
Navid Nemati	Development of a Non-Invasive Point-Of-Care Rule-Out Test for Heart Failure using Machine Learning	Session 1462 - Innovation, Digital Health, and Technology 14 April 7, 2024 - 3:15pm EST Location: Hall B4-5 (Georgia World Congress Center)

About CorVista® System

CorVista System is an Rx only, non-invasive point-of-care solution that is intended to synchronously collect and apply machine learning to a symptomatic patient's cardiac and hemodynamic signals to predict the likelihood of cardiovascular diseases without the use of radiation, contrast agents, injections, fasting, or exercise. Within minutes of the test, the CorVista® Analysis is available in a secure web portal to aid physicians in rapidly diagnosing and treating patients with suspected cardiovascular disease, answering important clinical questions to guide better treatment decisions. The CorVista System with CAD and PH Add-Ons has been cleared by FDA to market within the US. CorVista System is developed and manufactured by Analytics For Life, Inc. and licensed to CorVista Health, Inc.

About CorVista Health

CorVista Health, Inc. is applying machine learning to deliver novel cardiac disease detection algorithms using the proprietary CorVista System platform to transform cardiovascular care and the patient experience. CorVista Health is dedicated to enabling more equitable care by providing access to immediately actionable, high-quality cardiovascular status results in low-resource settings where access to capital-intensive equipment and the qualified specialists needed to operate them may not be available. In this way, the CorVista System is uniquely positioned to advance the quality of care in rural and low-resource settings.

For more information, visit: www.corvista.com