Predictors of the post-COVID condition following mild SARS-CoV-2 infection
B-A. Reme (),
J. Gjesvik and
K. Magnusson
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B-A. Reme: Norwegian Institute of Public Health
J. Gjesvik: Norwegian Institute of Public Health
K. Magnusson: Norwegian Institute of Public Health
Nature Communications, 2023, vol. 14, issue 1, 1-9
Abstract:
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.
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41541-x
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DOI: 10.1038/s41467-023-41541-x
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