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

Institutions

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

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Long-term changes in wearable sensor data in people with and without Long Covid

Jennifer M. Radin, Jay Pandit, Felipe Delgado, Erin Coughlin et al.
17 citations
npj Digital Medicine
Long-Term Effects of COVID-19
6.28
article

Long-term changes in wearable sensor data in people with and without Long Covid

Jennifer M. Radin, Jay Pandit, Felipe Delgado, Erin Coughlin, Julia Moore Vogel, Steven R. Steinhubl, Matteo Gadaleta
article en
17 citations

Abstract

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 .

npj Digital MedicineVol. 7(1)
Scripps Research Institute (US), Purdue University West Lafayette (US)
National Institutes of Health, National Center for Advancing Translational Sciences
Good health and well-being
Openalex Percentile: Top 3%
Long-Term Effects of COVID-19
6.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Long-term changes in wearable sensor data in people with and without Long Covid — Jennifer M. Radin, Jay Pandit, et al. · npj Digital Medicine (2024) | TGRS Research Map | TGRS