Jennifer M. Radin, Julia Moore Vogel, Felipe Delgado, Erin Coughlin, Matteo Gadaleta, Jay A. Pandit, Steven R. Steinhubl
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Long-term changes in wearable sensor data in people with and without Long Covid
To better understand the impact of Long COVID on an individual, we explored changes in daily wearable data (step count, resting heart rate (RHR), and sleep quantity) for up to one year in individuals relative to their pre-infection baseline among 279 people with and 274 without long COVID. Participants with Long COVID, defined as symptoms lasting for 30 days or longer, following a SARS-CoV-2 infection had significantly different RHR and activity trajectories than those who did not report Long COVID and were also more likely to be women, younger, unvaccinated, and report more acute-phase (first 2 weeks) symptoms than those without Long COVID. Demographic, vaccine, and acute-phase sensor data differences could be used for early identification of individuals most likely to develop Long COVID complications and track objective evidence of the therapeutic efficacy of any interventions. Trial Registration: https://classic.clinicaltrials.gov/ct2/show/NCT04336020 .
期刊介绍:
npj Digital Medicine is an online open-access journal that focuses on publishing peer-reviewed research in the field of digital medicine. The journal covers various aspects of digital medicine, including the application and implementation of digital and mobile technologies in clinical settings, virtual healthcare, and the use of artificial intelligence and informatics.
The primary goal of the journal is to support innovation and the advancement of healthcare through the integration of new digital and mobile technologies. When determining if a manuscript is suitable for publication, the journal considers four important criteria: novelty, clinical relevance, scientific rigor, and digital innovation.