Can AI Boost A-Fib Detection and Diagnose Over Standard Monitoring?

Atrial fibrillation is a common heart rhythm disorder that causes a rapid, irregular heartbeat and can lead to stroke and heart failure. The condition affects nearly 5% of the population, or 10.5 million U.S. adults, but often goes undiagnosed because there are no obvious symptoms.

To improve detection of atrial fibrillation (A-Fib), UC San Francisco researchers have designed an innovative clinical trial that seeks to advance diagnosis using remote A-Fib detection technology. The “Out-of-Office Monitoring for Rhythms of Normal Versus Atrial Fibrillation” (OMRON-AF) trial is a fully remote, national clinical trial and registry that will evaluate a new model for the early detection of A-Fib in hypertension patients using home blood pressure monitoring.

“We know that atrial fibrillation can be asymptomatic,” said Gregory Marcus, MD, MAS, OMRON-AF principal investigator and associate chief of Cardiology for Research at UCSF Health. “And yet, it substantially heightens the risk for stroke, heart failure, and death. The good news is that if it’s discovered, things can be done to prevent all of those serious complications, but we first have to know someone has the disease.”

The randomized controlled trial, being undertaken in collaboration with OMRON Healthcare Co., Ltd., is enrolling approximately 1,900 hypertension patients aged 60 and older who have risk factors for A-Fib but have not been diagnosed with the condition. Participants will be randomly assigned to either a blood pressure monitor with an AFib detection feature (intervention group) or a conventional blood pressure monitor (control group). The intervention group’s blood pressure monitor is a Bluetooth-enabled blood pressure cuff, using OMRON’s Intellisense AFib algorithm which has been trained to detect possible AFib.

“While our previous research showed that consumer-facing devices like smart watches could detect AFib, the challenge is that smartwatches tend to be worn by younger, healthier people, where the incidence of heart disease and high blood pressure is much lower and the risk of a false positive diagnosis is higher,” said Marcus. “This trial is designed to focus on individuals with hypertension at risk for A-Fib and to determine if the AI-enabled blood pressure cuff will enhance a clinical diagnosis of A-Fib compared to diagnosis by regular blood pressure monitoring.”

A gap in the data

During the first six months of the study, participants assigned to the AFib detection blood pressure (BP) monitor will be asked to answer short weekly mobile app-based surveys and take daily blood pressure measurements using their assigned device. If an intervention group participant is notified by their device that potential AFib has been detected, they will be asked to wear a continuous ECG recording device for two weeks and to complete a blood test measuring NT-proBNP levels (an indicator of heart failure).

Those in the control group will also be asked to take daily blood pressure measurements and answer short weekly mobile app-based surveys. During the first six months only, control group participants may be randomly assigned to wear a continuous ECG recording device for two weeks and to complete a blood test measuring NT-proBNP levels.

Following the first six months, participants will enter a 12-month registry phase. Participants in the control arm will receive a BP cuff with AFib detection technology. All the participants will be asked to take daily measurements using the BP monitor with AFib detection and answer monthly mobile-app surveys. These surveys will be used to assess cardiovascular-related events and any AFib occurrence.

Marcus recently served as vice chair of the AHA/ACC Clinical Performance and Quality Measures for Patients with Atrial Fibrillation, which determined how clinical practice guidelines related to atrial fibrillation should be implemented. He believes that the OMRON-AF trial will help inform current practice guidelines since there has not been adequate data about when to best diagnose A-Fib.

“There has been an absence of sufficient data to provide clear recommendations regarding screening for atrial fibrillation or use of devices for atrial fibrillation,” said Marcus. “The current guidelines, quite deliberately, do not include any recommendations to use these devices or screen, because of the lack of data to provide that guidance. Such data relies on randomized controlled trials just like this one, so OMRON-AF is actually contributing to and will, hopefully, provide improved guidance for the A-Fib practice guidelines.”

The OMRON-AF trial began in April 2026 and will conclude in April 2029. For more information about enrolling in the clinical trial, please text omronaf19 to 833-258-7623, or download the study app from this link: https://eureka-app.eurekaplatform.org/omronaf19

Funding: Omron Healthcare Co., Ltd.

Disclosures: Marcus is a consultant for and owns equity in InCarda and receives research funding from the National Institutes of Health and PCORI.

About UCSF Health: UCSF Health is recognized worldwide for its innovative patient care, reflecting the latest medical knowledge, advanced technologies and pioneering research. It includes the flagship UCSF Medical Center, which is a highly-ranked hospital, as well as UCSF Benioff Children’s Hospitals, with campuses in San Francisco and Oakland; two community hospitals, UCSF Health Stanyan Hospital and UCSF Health Hyde Hospital; Langley Porter Psychiatric Hospital; UCSF Benioff Children’s Physicians; and the UCSF Faculty Practice. These hospitals serve as the academic medical center of the University of California, San Francisco, which is world-renowned for its graduate-level health sciences education and biomedical research. UCSF Health has affiliations with hospitals and health organizations throughout the Bay Area. Visit http://www.ucsfhealth.org/. Follow UCSF Health on Facebook, Threads or LinkedIn.