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Long-term changes in wearable sensor data in people with and without Long Covid
Jennifer M Radin1, Julia Moore Vogel2, Felipe Delgado2
1Scripps Research Translational Institute, La Jolla, CA, 92037, USA. Jennifer.radin@modernatx.com.
NPJ Digital Medicine
|September 13, 2024
Summary
Long COVID significantly alters daily wearable data, including resting heart rate and activity levels, for up to a year post-infection. These changes, along with demographic factors, can help identify individuals at higher risk for Long COVID complications.
Area of Science:
- Digital Health
- Infectious Disease Epidemiology
- Cardiovascular Physiology
Background:
- Long COVID, characterized by persistent symptoms beyond 30 days post-SARS-CoV-2 infection, presents a significant public health challenge.
- Understanding objective physiological changes associated with Long COVID is crucial for diagnosis and management.
- Wearable sensor data offers a promising avenue for monitoring health status and disease progression in real-time.
Purpose of the Study:
- To investigate longitudinal changes in wearable sensor data (step count, resting heart rate, sleep quantity) in individuals with and without Long COVID.
- To identify objective biomarkers associated with Long COVID development and persistence.
- To explore demographic and acute-phase symptom predictors of Long COVID.
Main Methods:
- A cohort study comparing 279 individuals with Long COVID to 274 controls, analyzing wearable data up to one year post-SARS-CoV-2 infection against pre-infection baselines.
- Utilized data on step count, resting heart rate (RHR), and sleep quantity from wearable devices.
- Collected demographic information, vaccination status, and acute-phase symptom data.
Main Results:
- Individuals with Long COVID exhibited significantly different resting heart rate and activity trajectories compared to controls.
- Women, younger individuals, the unvaccinated, and those reporting more acute-phase symptoms were more likely to develop Long COVID.
- Objective data from wearables showed distinct patterns in the Long COVID group over the study period.
Conclusions:
- Wearable sensor data provides objective insights into the physiological impact of Long COVID.
- Demographic and acute-phase symptom data can aid in the early identification of individuals at risk for Long COVID.
- Objective data tracking may be valuable for assessing the efficacy of future Long COVID interventions.
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