Wearable sensor powered by AI predicts worsening heart failure before hospitalization

A new wearable sensor that works in conjunction with artificial intelligence technology could help doctors remotely detect critical changes in heart failure patients days before a health crisis occurs and could prevent hospitalization, according to a study led by University of Utah Health and VA Salt Lake City Health Care System scientists. The researchers say the system could eventually help avert up to one in three heart failure readmissions in the weeks following initial discharge from the hospital and help patients sustain a better quality of life.

“This study shows that we can accurately predict the likelihood of hospitalization for heart failure deterioration well before doctors and patients know that something is wrong,” says the study’s lead author, Josef Stehlik, M.D., M.P.H, co-chief of the advanced heart failure program at U of U Health.

“Being able to readily detect changes in the heart sufficiently early will allow physicians to initiate prompt interventions that could prevent rehospitalization and stave off worsening heart failure,” adds Stehlik, who also serves as medical director of the heart failure and heart transplant program at George E. Wahlen VA Medical Center in Salt Lake.

The study appears in


Circulation: Heart Failure


, an American Heart Association journal.

About 6.2 million Americans live with heart failure and it is the top hospital discharge diagnosis in the U.S. Up to 30% of these patients will likely be readmitted to the hospital within 90 days of discharge with recurrent symptoms including shortness of breath, fatigue and fluid buildup. In many cases, hospitalization diminishes a patient’s ability to care for themselves independently.

“Those individuals who have repeated hospitalizations for heart failure have significantly higher mortality” says Biykem Bozkurt, M.D., Ph.D., a study co-author, director of the Winters Center for Heart Failure Research at the Baylor College of Medicine in Houston. “Even if patients survive, they have poor functional capacity, poor exercise tolerance and low quality of life after hospitalizations. This patch, this new diagnostic tool, could potentially help us prevent hospitalizations and decline in patient status.”

The researchers followed 100 heart failure patients, average age 68, who were diagnosed and treated at four VA hospitals in Salt Lake City, Utah; Houston, Texas; Palo Alto, California; and Gainesville, Florida. After discharge, participants wore an adhesive sensor patch on their chests 24 hours a day for up to three months.
The sensor monitored continuous electrocardiogram (ECG) and motion of each subject.

This information was transmitted from the sensor via Bluetooth to a smartphone and then passed on to an analytics platform, developed by PhysIQ, on a secure server, which derived heart rate, heart rhythm, respiratory rate, walking, sleep, body posture and other normal activities. Using artificial intelligence, the analytics established a normal baseline for each patient. When the data deviated from normal, the platform generated an indication that the patient’s heart failure was getting worse.

Overall, the system accurately predicted the impending need for hospitalization more than 80 percent of the time. On average, this prediction occurred 10.4 days before a readmission took place (median 6.5 days).

“There’s a high risk for readmission in the 90 days after initial discharge,” Stehlik says. “If we can decrease this readmission rate through monitoring and early intervention, that’s a big advance. We’re hoping even in patients who might be readmitted that their stays are shorter, and the overall quality of their lives will be better with the help of this technology.”

Next, the researchers plan to conduct a large clinical trial that will not only use the system to alert doctors of changes in a patient’s condition but also track if early intervention based on these alerts lead to fewer rehospitalizations for heart failure.

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In addition to Drs. Stehlik and Bozhurt, University of Utah Health researchers Jose Nativi-Nicolau, Peter Wohlfahrt and Heather Hanson contributed to this study. Collaborators from other institutions include C. Schmalfuss, S. Wegerich, K Rose, R. Ray, R. Schofield, A. Deswal, S. Anand, H. Hanson, D. Richards,M. Pipke, J. Sekaric, and M. Phram. The Department of Veterans Affairs Office of Information & Technology and VHA Innovation Ecosystem funded the study. PhysIQ, Inc developed the analytics platform. PIpke, Wegerich, Rose, Anand, Sekaric and Richards are employed by PhysIQ. Stehlik is a consultant to Medtronic and Abbott.

University of Utah Health

provides leading-edge and compassionate medicine for a referral area that encompasses 10% of the U.S., including Idaho, Wyoming, Montana and much of Nevada. A hub for health sciences research and education in the region, U of U Health touts a $356 million research enterprise and trains the majority of Utah’s physicians and more than 1,250 health care providers each year at its Schools of Medicine and Dentistry and Colleges of Nursing, Pharmacy and Health. With more than 20,000 employees, the system includes 12 community clinics and four hospitals. For nine straight years, U of U Health has ranked among the top 10 U.S. academic medical centers in the rigorous Vizient Quality and Accountability Study, including reaching No. 1 in 2010 and 2016.

The

VA Salt Lake City Health Care System

is committed to providing compassionate, state-of-the-art healthcare to Veterans of the Intermountain West. Our health care system consists of the George E. Wahlen Department of Veterans Affairs Medical Center in Salt Lake City, Utah and nine community clinics across Utah, Idaho and Nevada spanning across 125,000 square miles. We provide healthcare to over 67,000 eligible Veterans across one of the largest geographical areas in VA. The George E. Wahlen VA Medical Center is a teaching hospital, providing a full range of patient care services, holistic medicine as well as education and research in partnership with the University of Utah and other institutions of higher education.