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CorVista Health Announces AHA Presentation of Machine Learning to Detect Pulmonary Hypertension at Point-of-Care

2023-11-13 05:46
WASHINGTON--(BUSINESS WIRE)--Nov 12, 2023--
CorVista Health Announces AHA Presentation of Machine Learning to Detect Pulmonary Hypertension at Point-of-Care

WASHINGTON--(BUSINESS WIRE)--Nov 12, 2023--

CorVista Health, Inc., a leading digital health company dedicated to improving cardiovascular disease diagnosis, is pleased to announce the presentation of Machine Learning to Detect Pulmonary Hypertension data at AHA.

This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20231112489250/en/

CorVista Health AHA Presentation--Machine Learning to Detect Pulmonary Hypertension at Point of Care. Presented by Dr. Charles Bridges. (Photo: Business Wire)

“We are pleased to present this important data at this year’s AHA meeting.” said Don Crawford, President and CEO of CorVista Health. “Pulmonary hypertension is a challenging condition to diagnose, especially early in the disease progression. This presentation follows the FDA’s Breakthrough Designation for the CorVista System Add-On to detect pulmonary hypertension and the recent FDA clearance of the coronary artery disease platform.”

Pulmonary hypertension (PH), a life-threatening condition with significant morbidity and mortality, affects an estimated 1% of the world population. It is present in 10% of people over age 65 and 50% of patients with heart failure. Further, the subgroup of pulmonary arterial hypertension (PAH) is frequently diagnosed years after symptom onset, at a point when the pathophysiologic changes have become irreversible.

Existing diagnostics for PH are insufficient; for instance, the sensitivity and specificity of Transthoracic Echocardiography (TTE) varies over a wide range. Moreover, TTE requires specialized equipment and technical support that is often unavailable. Herein we present the results of a machine-learned model addressing the need for an improved point-of-care test for PH in newly symptomatic subjects.

The presentation demonstrates the ability to develop a point of care method to detect PH, based on cardiac orthogonal voltage gradient (OVG) signals and photoplethysmographic (PPG) signals. A machine learned (ML) algorithm was developed to discriminate subjects with no evidence of diastolic dysfunction nor PH on TTE vs. those with mPAP≥25 mmHg from right heart catheterization.

The AUC of the algorithm was 0.93, the sensitivity 87%, and the specificity 83%. Further, the performance is preserved in all subgroups, including pre-capillary PH. This supervised machine-learned model therefore provides strong preliminary evidence that an algorithm can be developed to assess the likelihood of PH in patients with new onset symptoms of cardiovascular disease.

“This important data demonstrates the feasibility to detect pulmonary hypertension, as well as enabling potentially earlier diagnosis in the progression of the disease.” said Charles Bridges, M.D. Sc.D., Executive Vice President and Chief Scientific Officer, CorVista Health. “We believe the CorVista System ® can make a tremendous impact to patients suffering from pulmonary hypertension, especially in rural and underserved populations.”

About CorVista® Health

CorVista Health, Inc. is applying machine learning to deliver novel cardiac detection algorithms to enhance the CorVista System platform over time, with the aim of transforming cardiovascular care and the patient experience. For more information, visit corvista.com. CorVista Health is dedicated to addressing the FDA’s call to action for leveraging health technologies to advance health equity, as presented by FDA Commissioner, Dr. Robert Califf. Particularly, the decline in life expectancy in rural areas has been cited as key evidence of disparate health outcomes. CorVista System has the potential to enable 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.

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 CorVista® System with CAD add-on has been cleared to market as a 510(k) device. Additional CorVista System Add-Ons for Pulmonary Hypertension and LV Filling Pressure are currently investigational devices limited by federal law (or United States) law to investigational use and are not available for commercial distribution. CorVista System is developed and manufactured by Analytics 4 Life, Inc., and licensed exclusively to CorVista Health, Inc.

  1. Janda S, et al. Diagnostic accuracy of echocardiography for pulmonary hypertension: a systematic review and metanalysis. Heart 2011; 97-612-22.

View source version on businesswire.com:https://www.businesswire.com/news/home/20231112489250/en/

CONTACT: Chris Bing Ernst

415-710-9445

cernst@corvista.com

KEYWORD: DISTRICT OF COLUMBIA UNITED STATES NORTH AMERICA

INDUSTRY KEYWORD: WOMEN SENIORS PARENTING RESEARCH SOFTWARE FAMILY CONSUMER SCIENCE SOCIAL MEDIA TECHNOLOGY SEARCH ENGINE OPTIMIZATION SEARCH ENGINE MARKETING CARDIOLOGY BLOGGING GENERAL HEALTH PUBLISHING PUBLIC RELATIONS/INVESTOR RELATIONS HEALTH COMMUNICATIONS

SOURCE: CorVista Health, Inc.

Copyright Business Wire 2023.

PUB: 11/12/2023 04:30 PM/DISC: 11/12/2023 04:30 PM

http://www.businesswire.com/news/home/20231112489250/en