Graphs show mean deviation from baseline (lines) with 95% CIs (shaded areas) for daily resting heart rate (RHR), sleep quantity, and step count during −7 to 133 days after symptom onset for COVID-19–positive vs COVID-19–negative participants (panels A, C, and E) and for COVID-19–positive participants grouped by mean change in RHR during days 28 to 56 after symptom onset (panels B, D, and F).
eAppendix. Supplemental Methods
eFigure. Flow Chart of Selecting Participants for Final Dataset
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Radin JM, Quer G, Ramos E, et al. Assessment of Prolonged Physiological and Behavioral Changes Associated With COVID-19 Infection. JAMA Netw Open. 2021;4(7):e2115959. doi:10.1001/jamanetworkopen.2021.15959
Long-term COVID symptoms marked by autonomic dysfunction1 and cardiac damage2 following COVID-19 infection have been noted for up to 6 months after symptom onset,3 but to date have not been quantified, to our knowledge. Previous studies have found that wearable data can improve real-time detection of viral illness4 or discrimination of individuals with COVID-19 vs other viral infections.5 Wearable devices provide a way to continuously track an individual’s physiological and behavioral metrics beginning when healthy (ie, before infection), during the course of infection, and recovery back to baseline. In this cohort study, we aimed to examine the duration and variation of recovery among COVID-19–positive vs COVID-19–negative participants.
DETECT (Digital Engagement and Tracking for Early Control and Treatment) is a remote, app-based, longitudinal research study enrolling adult participants from all over the US and collecting their wearable data to better understand individual changes associated with viral illness, including COVID-19. All participants provided informed consent electronically. The protocol for this study was reviewed and approved by the Scripps Office for the Protection of Research Subjects. This study follows the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline.
From March 25, 2020, through January 24, 2021, 37 146 participants were enrolled. This analysis focuses on 875 individuals who reported symptoms of an acute respiratory illness and underwent swab testing for COVID-19 and were found to be either positive (234 individuals) or negative (641 individuals) (eFigure in the Supplement).
The following calculation was used for resting heart rate (RHR): deviation from baseline = daily RHR − baseline RHR mean. Individuals with COVID-19 were also grouped by their mean RHR deviation from baseline 28 to 56 days after symptom onset (<1, 1-5, or >5 beats per minute).
Data analysis was conducted in SAS statistical software version 9.4 (SAS Institute). Significance was set at P < .05. P values were calculated with 1-way ANOVA (for mean age) or χ2 tests. Additional details about our methods can be found in the eAppendix in the Supplement.
For this analysis, our study population consisted of 234 COVID-19–positive individuals (mean [range] age, 45.3 [18-76] years; 164 women [70.9%]) and 641 COVID-19–negative symptomatic individuals (mean [range] age, 44.7 [19-75] years; 455 women [71.1%]). Individuals with COVID-19 took longer to return to their RHR (Figure, A and B), sleep (Figure, C and D), and activity (Figure, E and F) baselines compared with symptomatic individuals who were COVID-19 negative. This difference was most marked for RHR, with COVID-19–positive individuals initially experiencing a transient bradycardia followed by a prolonged relative tachycardia that did not return to baseline, on average, until 79 days after symptom onset. Step count and sleep quantity returned to baseline sooner than RHR at 32 and 24 days, respectively. During recovery, individuals with COVID-19 experienced different trajectories in the return of their RHR to their normal compared with COVID-19–negative individuals (Figure, B). A small subset of COVID-19–positive participants (32 participants [13.7%]) maintained an RHR more than 5 beats per minute greater than their baseline RHR that did not return to their normal for more than 133 days. During the acute phase of COVID-19, individuals in this group reported higher frequencies of cough (27 participants [84.4%] vs 57 participants [55.3%] in the <1 beat per minute group and 57 participants [57.6%] in the 1-5 beats per minute group), body ache (20 participants [62.5%] vs 42 participants [40.8%] in the <1 beat per minute group and 35 participants [35.4%] in the 1-5 beats per minute group), and shortness of breath (9 participants [28.1%] vs 9 participants [8.7%] in the <1 beat per minute group and 6 participants [6.1%] in the 1-5 beats per minute group) compared with the other groups (Table).
To our knowledge, this is the first study to examine longer duration wearable sensor data. We found a prolonged physiological impact of COVID-19 infection, lasting approximately 2 to 3 months, on average, but with substantial intraindividual variability, which may reflect various levels of autonomic nervous system dysfunction or potentially ongoing inflammation. Transient bradycardia has been noted in a case study6 approximately 9 to 15 days after symptom onset, which was also seen in our population. Our data suggest that early symptoms and larger initial RHR response to COVID-19 infection may be associated with the physiological length of recovery from this virus.
Symptom data were collected only during the acute phase of infection, which limited our ability to compare long-term physiological and behavioral changes with long-term symptoms. In the future, with larger sample sizes and more comprehensive participant-reported outcomes, it will be possible to better understand factors associated with interindividualized variability in COVID-19 recovery.
Accepted for Publication: May 3, 2021.
Published: July 7, 2021. doi:10.1001/jamanetworkopen.2021.15959
Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2021 Radin JM et al. JAMA Network Open.
Corresponding Author: Jennifer M. Radin, PhD, MPH, Scripps Research Translational Institute, 3344 N Torrey Pines Ct, Plaza Level, La Jolla, CA 92037 (email@example.com).
Author Contributions: Dr Radin had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Concept and design: Radin, Ramos, Baca-Motes, Steinhubl.
Acquisition, analysis, or interpretation of data: All authors.
Drafting of the manuscript: Radin, Steinhubl.
Critical revision of the manuscript for important intellectual content: All authors.
Statistical analysis: Radin, Quer, Gadaleta.
Obtained funding: Baca-Motes, Topol.
Administrative, technical, or material support: Quer, Baca-Motes, Gadaleta, Topol.
Supervision: Ramos, Steinhubl.
Conflict of Interest Disclosures: Dr Steinhubl reports being employed part time with PhysIQ, which is not involved in this study. No other disclosures were reported.
Funding/Support: This work was funded by grant UL1TR002550 from the National Center for Advancing Translational Sciences at the National Institutes of Health (support to Drs Topol, Radin, and Steinhubl).
Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
Additional Contributions: Lauren Ariniello, BS, Erin Coughlin, RN, Royan Kamyar, MD, MBA, Danny Oran, MS, Sasri Dedigama, BS, and Katie Quartuccio, BA (Scripps Research Translational Institute); Tyler Peters, BA (Wondros); and Vik Kheterpol, MD, and Chris Nowak, BA (Care Evolution), helped make the DETECT study (http://www.detectstudy.org) a success. They were not compensated for their contributions beyond their normal salaries.
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