CorVista Health receives Breakthrough Device Designation for The CorVista® System

Washington DC—October 25, 2022—CorVista Health, Inc, a digital health company dedicated to improving cardiovascular disease diagnosis, announces that the U.S. Food and Drug Administration (FDA) has granted Breakthrough Device Designation for the CorVista System as a first non-invasive point of care diagnostic solution for patients with suspected pulmonary hypertension.

The FDA’s Breakthrough Devices Program is a voluntary program available to therapeutic devices that establish they have the potential to provide more effective treatment or diagnosis of life threatening or irreversibly debilitating diseases or conditions. Breakthrough designation provides several important benefits, including prioritized review of future regulatory submissions and greater opportunity to interact with FDA experts throughout the review process.

“We’re very pleased for the opportunity to continue to work closely with the FDA to fulfill our mission to improve the diagnosis and treatment of cardiovascular diseases and importantly our solution for pulmonary hypertension for which the Breakthrough Designation was awarded.” said President and CEO Don Crawford. “While the CorVista System is not yet FDA cleared, we are hopeful that Breakthrough Device Designation will help expedite patient access to the CorVista System as a non-invasive point of care diagnostic solution.”

The CorVista System offers two important improvements to the current standard of care for diagnosing pulmonary hypertension – expansion of the population for use of a non-invasive, point-of-care test and potential for significant reduction in time to diagnosis and treatments thereby allowing improved patient outcomes. The CorVista System Breakthrough Device Designation was supported by prospective clinical studies which allow for a highly accurate labeling of subjects with and without the disease of interest, and the application of novel machine learning techniques which have provided clear evidence the system is likely to improve the current standard of care.

“Unfortunately, there have not been any meaningful advancements to facilitate the early diagnosis of pulmonary hypertension in decades,” said Vallerie V McLaughlin, M.D. Kim A Eagle MD Endowed Professor of Cardiovascular Medicine and Director Pulmonary Hypertension at the University of Michigan Ann Arbor and CorVista Health Medical Advisory Board member. “I am hopeful the non-invasive CorVista System will enable clinicians to diagnose patients suffering from pulmonary hypertension at an earlier stage, ultimately improving patient care and outcomes.”

Importantly, a critical impediment to correctly diagnosing PH patients results from their frequent presentation with symptoms similar to other common cardiovascular disease states such as, coronary artery disease and heart failure, further increasing the complexity of its recognition and ultimately diagnosis. The CorVista System with its novel PH Add-On is intended to indicate the likelihood of elevated mean pulmonary arterial pressure at point-of-care so that by identifying patients with PH earlier in the clinical pathway, patient care can be better triaged, and treatment outcomes can be maximized by patient type and need.


About Pulmonary Hypertension
Pulmonary hypertension is challenging to diagnose, affecting an estimated 1% of the world population and up to 10% of people greater than 65 years of age as well as 50% of patients with heart failure. The vast majority of those persons with this disorder (80%) live in areas with limited access to appropriate medical and surgical care. Pulmonary arterial hypertension is an aggressive disease resulting in right ventricular pressure/volume overload, right ventricular failure, and, in many cases, early death.

About CorVista® System
CorVista System is a non-invasive point-of-care solution that is intended to synchronously collect and apply machine learning to a 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 PH Add-On is just one of the CorVista System algorithms under development. The CorVista System (which includes easily portable hardware and software) is designed as a platform device to be complimented over time with other AI/ML cardiovascular disease detection algorithms or “Add-ons” for indicating the likelihood of CAD, elevated Left-Ventricular Filling Pressure and other disease indicators. The CorVista System (and its Add-Ons) is an investigational device limited by federal law to investigational use. CorVista System is not currently available for commercial distribution.

CorVista Health is focused on FDA’s recent call to action to better leverage health technologies to advance health equity as presented by FDA Commissioner, Dr. Robert Califf. Particularly, the decline of life expectancy in rural and disadvantaged urban areas has been cited as key evidence of disparate health outcomes. CorVista System has potential to enable more equitable care by providing access to immediately actionable, high quality cardiovascular status results in lowresource settings, where access to capital-intensive equipment and the qualified specialists needed to operate them may not be available. In doing so, the CorVista System is uniquely poised to advance the quality of care in rural and disadvantaged urban settings.

About CorVista® Health
CorVista Health, Inc. is applying machine learning using real world test data to develop a novel cardiac diagnostic platform, CorVista® System, with the aim of transforming cardiovascular care and the patient experience. For more information, visit

CorVista Health, Inc.
Chris Bing Ernst
(415) 710-9445
[email protected]

CorVista provides actionable cardiac diagnostics at the point of care by applying advanced machine learning for more rapid and accurate diagnosis of cardiac disease.
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