Oct. 2, 2024 — Eko Health recently 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 study involving more than 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.
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.
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.
"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," said Connor Landgraf, co-founder and CEO of Eko Health.
December 05, 2024 
