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 .
Authors
- Jennifer M. Radin (ORCID: https://orcid.org/0000-0003-3843-0842)
- Jay Pandit (ORCID: https://orcid.org/0000-0003-0119-0881)
- Felipe Delgado (ORCID: https://orcid.org/0009-0006-6042-187X)
- Erin Coughlin
- Julia Moore Vogel (ORCID: https://orcid.org/0000-0002-4902-3540)
- Steven R. Steinhubl (ORCID: https://orcid.org/0000-0002-9256-7914)
- Matteo Gadaleta (ORCID: https://orcid.org/0000-0001-6470-6537)
Institutions
- Scripps Research Institute (US)
- Purdue University West Lafayette (US)
Publication Details
- Journal
- npj Digital Medicine
- Published
- 2024-09-13
- DOI
- https://doi.org/10.1038/s41746-024-01238-x
- Citations
- 17
- Primary Topic
- Long-Term Effects of COVID-19
- Type
- article
- Field-Weighted Citation Impact
- 6.28
Funders
- National Institutes of Health
- National Center for Advancing Translational Sciences