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Deep Dive into the Long Haul: Analysis of Symptom Clusters and Risk Factors for Post-Acute Sequelae of COVID-19 to Inform Clinical Care

Author

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  • Nicole H. Goldhaber

    (Department of Surgery, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA
    Division of Biomedical Informatics, Department of Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

  • Jordan N. Kohn

    (Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

  • William Scott Ogan

    (Division of Biomedical Informatics, Department of Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

  • Amy Sitapati

    (Division of Biomedical Informatics, Department of Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

  • Christopher A. Longhurst

    (Division of Biomedical Informatics, Department of Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA
    Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

  • Angela Wang

    (Division of Pulmonology, Department of Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

  • Susan Lee

    (Division of Rheumatology, Allergy, and Immunology, Department of Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

  • Suzi Hong

    (Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA
    Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA 92093, USA)

  • Lucy E. Horton

    (Division of Infectious Diseases and Global Public Health, Department of Medicine, School of Medicine, University of California San Diego, La Jolla, CA 92093, USA)

Abstract

Long COVID is a chronic condition characterized by symptoms such as fatigue, dyspnea, and cognitive impairment that persist or relapse months after an acute infection with the SARS-CoV-2 virus. Many distinct symptoms have been attributed to Long COVID; however, little is known about the potential clustering of these symptoms and risk factors that may predispose patients to certain clusters. In this study, an electronic survey was sent to patients in the UC San Diego Health (UCSDH) system who tested positive for COVID-19, querying if patients were experiencing symptoms consistent with Long COVID. Based on survey results, along with patient demographics reported in the electronic health record (EHR), linear and logistic regression models were used to examine putative risk factors, and exploratory factor analysis was performed to determine symptom clusters. Among 999 survey respondents, increased odds of Long COVID (n = 421; 42%) and greater Long COVID symptom burden were associated with female sex ( OR = 1.73, 99% CI: 1.16–2.58; β = 0.48, 0.22–0.75), COVID-19 hospitalization ( OR = 4.51, 2.50–8.43; β = 0.48, 0.17–0.78), and poorer pre-COVID self-rated health ( OR = 0.75, 0.57–0.97; β = −0.19, −0.32–−0.07). Over one-fifth of Long COVID patients screened positive for depression and/or anxiety, the latter of which was associated with younger age ( OR = 0.96, 0.94–0.99). Factor analysis of 16 self-reported symptoms suggested five symptom clusters—gastrointestinal (GI), musculoskeletal (MSK), neurocognitive (NC), airway (AW), and cardiopulmonary (CP), with older age (β = 0.21, 0.11–0.30) and mixed race (β = 0.27, 0.04–0.51) being associated with greater MSK symptom burden. Greater NC symptom burden was associated with increased odds of depression ( OR = 5.86, 2.71–13.8) and anxiety ( OR = 2.83, 1.36–6.14). These results can inform clinicians in identifying patients at increased risk for Long COVID-related medical issues, particularly neurocognitive symptoms and symptom clusters, as well as informing health systems to manage operational expectations on a population-health level.

Suggested Citation

  • Nicole H. Goldhaber & Jordan N. Kohn & William Scott Ogan & Amy Sitapati & Christopher A. Longhurst & Angela Wang & Susan Lee & Suzi Hong & Lucy E. Horton, 2022. "Deep Dive into the Long Haul: Analysis of Symptom Clusters and Risk Factors for Post-Acute Sequelae of COVID-19 to Inform Clinical Care," IJERPH, MDPI, vol. 19(24), pages 1-13, December.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:24:p:16841-:d:1004118
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    References listed on IDEAS

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    1. Ellen J. Thompson & Dylan M. Williams & Alex J. Walker & Ruth E. Mitchell & Claire L. Niedzwiedz & Tiffany C. Yang & Charlotte F. Huggins & Alex S. F. Kwong & Richard J. Silverwood & Giorgio Di Gessa , 2022. "Long COVID burden and risk factors in 10 UK longitudinal studies and electronic health records," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
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    Cited by:

    1. Janet L. Larson & Weijiao Zhou & Philip T. Veliz & Sheree Smith, 2023. "Symptom Clusters in Adults with Post-COVID-19: A Cross-Sectional Survey," Clinical Nursing Research, , vol. 32(8), pages 1071-1080, November.
    2. Radha Ambalavanan & R Sterling Snead & Julia Marczika & Karina Kozinsky & Edris Aman, 2023. "Advancing the Management of Long COVID by Integrating into Health Informatics Domain: Current and Future Perspectives," IJERPH, MDPI, vol. 20(19), pages 1-21, September.

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