A fitness tracker is like Santa Claus: It knows when you’re sleeping, when you’re awake, and whether you’ve been bad or good – about meeting your daily step goal, that is. It may not bring you presents, but it could provide important insights to help manage chronic disease.
According to Johns Hopkins researchers, fitness tracker metrics, including heart rate and step count, may be closely linked to several key biomarkers – things to be measured to tell how the body is doing.
The researchers collected 405 weeks’ worth of heart rate measurements and minute-to-minute step counts – more than 10,000 data points – from Fitbits worn by 22 people with pulmonary arterial hypertension, when blood flow is constricted in the arteries traveling from the heart to the lungs. Then they compared that data to the patients’ vitals and blood test results from two clinic visits.
“This was a small study, so it is difficult to make generalizations,” says study author Peter Searson, PhD, a professor of engineering at Johns Hopkins University. “However, the results suggest that Fitbit data could be used to predict clinical parameters.”
The study, published in Nature’s NPJ Digital Medicine journal, builds on emerging research tackling an increasingly relevant question, especially as wearable devices are getting more popular: Could fitness tracker data be useful in clinical care?
Unlike traditional methods used only at the doctor’s office, wearables gather data as patients go about their lives – no prescribed activities or doctor visits needed. These findings suggest that doctors could potentially use that data to remotely monitor patients with chronic conditions, perhaps heading off a heart attack or other dire emergency.
“If we can identify patients at high risk for acute episodes, they could be scheduled for more frequent clinic visits,” Searson says. “Similarly, we could identify individuals who need fewer clinic visits.”
Step counts could also serve in place of the 6-minute walk test – how far a patient can walk in 6 minutes – an indicator of overall health in chronically ill patients.
Normally, the test requires cones set up 100 feet apart so patients can walk laps for 6 minutes. Walking less than 320 meters (1,050 feet) has been linked to worse outcomes. But the patient must travel to a clinic with enough space to take the test.
In the study, the researchers combed the patients’ weekly Fitbit data for the 6-minute period with the most steps. Using a standard formula for predicting a person’s step length based on height and age, the researchers estimated the distance walked in that 6 minutes. The results closely matched those from walk tests done in the clinic.
Other findings: Logging less than 5,000 steps a day was linked to lower hemoglobin levels, or red blood cell count, while higher step counts predicted higher hemoglobin.
A patient’s average heart rate when active was closely associated with their albumin levels, an indicator of kidney and liver function. A lower heart rate-to-step rate ratio (or “fitness slope”) was linked to higher levels of N-terminal pro b-type natriuretic peptide, an indicator of cardiac stress.
“Since Fitbit metrics reflect, in part, the function of many organ systems, we believe that we may be able to use artificial intelligence to understand how the function of different organs is reflected in heart rate and step rate,” Searson says.
Collecting the fitness tracker data is pretty straightforward, Searson says. Anyone can access their own Fitbit data, and Searson’s team used open-source software to download the information with the participants’ consent.
Previous studies have explored step counts from fitness trackers as a way to measure the well-being of patients with multiple sclerosis and cardiovascular disease. A 2020 study from Ireland used Fitbits to promote physical activity among cancer survivors.
Yet little research has examined how that data could be a proxy for important clinical metrics. Using fitness trackers clinically is a “long-term goal,” Searson says, but more research is needed to verify the data and to develop artificial intelligence to analyze it. Next the researchers plan to investigate how tracker data could be used to treat patients with chronic obstructive pulmonary disease (COPD) and scleroderma, an autoimmune disease.
Peter Searson, PhD, professor of materials science and engineering, Johns Hopkins University.
NPJ Digital Medicine: “Evaluation of physical health status beyond daily step count using a wearable activity sensor.”
Source: Read Full Article