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Predictors of the post-COVID condition following mild SARS-CoV-2 infection

Author

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  • B-A. Reme

    (Norwegian Institute of Public Health
    University of Oslo)

  • J. Gjesvik

    (Norwegian Institute of Public Health
    Cancer Registry of Norway)

  • K. Magnusson

    (Norwegian Institute of Public Health
    Lund University)

Abstract

Whereas the nature of the post-COVID condition following mild acute COVID-19 is increasingly well described in the literature, knowledge of its risk factors, and whether it can be predicted, remains limited. This study, conducted in Norway, uses individual-level register data from 214,667 SARS-CoV-2 infected individuals covering a range of demographic, socioeconomic factors, as well as cause-specific healthcare utilization in the years prior to infection to assess the risk of post-COVID complaints ≥3 months after testing positive. We find that the risk of post-COVID was higher among individuals who prior to infection had been diagnosed with psychological (OR = 2.12, 95% CI 1.84–2.44), respiratory (OR = 2.03, 95% CI 1.78–2.32), or general and unspecified health problems (OR = 1.78, 95% CI 1.52–2.09). To assess the predictability of post-COVID after mild initial disease, we use machine learning methods and find that pre-infection characteristics, combined with information on the SARS-CoV-2 virus type and vaccine status, to a considerable extent (AUC = 0.79, 95% CI 0.75–0.81) could predict the occurrence of post-COVID complaints in our sample.

Suggested Citation

  • B-A. Reme & J. Gjesvik & K. Magnusson, 2023. "Predictors of the post-COVID condition following mild SARS-CoV-2 infection," Nature Communications, Nature, vol. 14(1), pages 1-9, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41541-x
    DOI: 10.1038/s41467-023-41541-x
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    References listed on IDEAS

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    1. Karin Magnusson & Doris Tove Kristoffersen & Andrea Dell’Isola & Ali Kiadaliri & Aleksandra Turkiewicz & Jos Runhaar & Sita Bierma-Zeinstra & Martin Englund & Per Minor Magnus & Jonas Minet Kinge, 2022. "Post-covid medical complaints following infection with SARS-CoV-2 Omicron vs Delta variants," Nature Communications, Nature, vol. 13(1), pages 1-9, December.
    2. Carlo Cervia & Yves Zurbuchen & Patrick Taeschler & Tala Ballouz & Dominik Menges & Sara Hasler & Sarah Adamo & Miro E. Raeber & Esther Bächli & Alain Rudiger & Melina Stüssi-Helbling & Lars C. Huber , 2022. "Immunoglobulin signature predicts risk of post-acute COVID-19 syndrome," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. 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.
    4. Heidi Ledford, 2022. "How common is long COVID? Why studies give different answers," Nature, Nature, vol. 606(7916), pages 852-853, June.
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