Imperial College London Study Finds Eko Health AI Predicts Patients With High Risk of Major Adverse Cardiac Events

Press Releases

Oct 02, 2024

Patients identified with reduced ejection fraction using Eko Health AI were twice as likely to experience heart attacks, heart failure, hospitalization, and all-cause mortality over two years.

SAN FRANCISCO, Oct. 2, 2024 /PRNewswire/ — Eko Health, a pioneer in applying artificial intelligence (AI) for early detection of heart and lung diseases, today announced a new independent study from researchers at Imperial College London (Imperial) that demonstrated how AI can identify patients with significantly higher risk of experiencing major adverse cardiac events (MACE), including heart attacks and heart failure. Researchers used Eko Health’s FDA-cleared and UKCA-marked Low Ejection Fraction AI to conduct the study, which reinforced the power of Eko’s AI for early detection while also showing its potential to improve cardiovascular care in both clinical and remote settings.

Imperial researchers unveiled three significant studies at the European Society of Cardiology (ESC) Congress 2024, demonstrating:

Eko AI Predictive of Major Adverse Cardiac Events and Mortality
In a pivotal study involving over 1,000 patients, Eko’s AI was shown to predict MACE—including heart attacks, heart failure, and hospitalization—as well as all-cause mortality. Patients flagged by the AI for low ejection fraction were twice as likely to experience MACE compared to those without a positive AI result. These patients also faced a 65% higher mortality rate, even after adjusting for traditional risk factors.

“These findings underscore the power of AI-ECG in identifying patients at a significantly higher risk of MACE and mortality, even when traditional markers like left ventricular ejection fraction appear normal. In our study, patients with a positive AI-ECG result had more than double the risk of MACE and a 65% higher risk of mortality. This technology represents a critical advancement in early cardiac risk stratification, offering the potential for more targeted interventions through the simple addition of a single-lead ECG,” said Dr. Patrik Bächtiger, one of the co-leads of this research at Imperial.

“Notably, the AI identified at-risk patients who had unremarkable results from traditional diagnostic tools, such as echocardiograms. This highlights the technology’s ability to detect hidden risk factors, offering healthcare providers a powerful tool for early intervention and improved patient outcomes,” said Prof. Nicholas S. Peters, Director of the Health Impact Lab at Imperial.

Eko AI Expands Remote Care Capabilities for Heart Failure Patients
In another Imperial study presented at ESC 2024, Eko’s AI technology demonstrated its potential for remote patient monitoring, particularly for individuals with heart failure. The study found that Eko’s AI could accurately predict changes in left ventricular ejection fraction (LVEF), which is a critical indicator of heart function in heart failure patients. By being able to monitor changes in LVEF from home, patients could benefit from earlier interventions and personalized adjustments to their treatment plans, reducing the need for frequent hospital visits and providing peace of mind.

Eko AI Demonstrates Scalability for Widespread Clinical Integration
Over a 12-week period, the Imperial team successfully integrated Eko’s AI across 71 primary care sites in the UK. The study highlighted both the consistent and seamless adoption of the technology by healthcare providers, in addition to its ability to enhance patient care without straining existing healthcare systems. “This demonstrates the technology’s practicality and scalability for widespread clinical use, paving the way for broader implementation in routine medical practice,” said Dr. Mihir Kelshiker, one of the co-leads of this program at Imperial.

Together, these findings further solidify Eko’s Low EF AI technology as an important innovation for early detection and management of cardiovascular disease, reinforcing its role as an essential tool in advancing patient care.

“This important research from Imperial College London highlights the transformative potential of Eko’s AI technology in the fight against heart disease,” said Connor Landgraf, co-founder and CEO of Eko Health. “By identifying patients at elevated risk for major cardiac events with a simple, non-invasive test, we are empowering clinicians worldwide to take action earlier, ultimately saving lives and improving care outcomes on a global scale.”

About Eko Health

Eko Health is a leading digital health company advancing how healthcare professionals detect and monitor heart and lung disease with its portfolio of digital stethoscopes, patient and provider software, and AI-powered analysis. Its FDA-cleared platform, used by over 500,000 healthcare professionals worldwide, allows them to detect earlier and with higher accuracy, diagnose with more confidence, manage treatment effectively, and ultimately give their patients the best care possible. Eko Health is headquartered in Emeryville, California, with over $165 million in funding from ARTIS Ventures, DigiTx Partners, Double Point Ventures, EDBI, Highland Capital Partners, LG Technology Ventures, Mayo Clinic, Morningside Technology Ventures Limited, NTTVC, Questa Capital, and others.

Media Contact
Sam Moore
sam.moore@ekohealth.com

Cision View original content to download multimedia:https://www.prnewswire.com/news-releases/imperial-college-london-study-finds-eko-health-ai-predicts-patients-with-high-risk-of-major-adverse-cardiac-events-302265566.html

SOURCE Eko Health

YOU MAY ALSO LIKE

AGM Group Holdings Inc. Announces Strategic Partnership…

Patients identified with reduced ejection fraction using Eko Health AI were twice as likely to experience heart attacks, heart failure, hospitalization, and all-cause mortality over…

read more

Zimmer Biomet to Present at the 43rd…

Patients identified with reduced ejection fraction using Eko Health AI were twice as likely to experience heart attacks, heart failure, hospitalization, and all-cause mortality over…

read more

Earth AI Discovers New Gold System Close…

Patients identified with reduced ejection fraction using Eko Health AI were twice as likely to experience heart attacks, heart failure, hospitalization, and all-cause mortality over…

read more