Predictors of the post-COVID condition following mild SARS-CoV-2 infection
(2023) In Nature Communications 14(1).- 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... (More)
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.
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- author
- Reme, B. A. ; Gjesvik, J. and Magnusson, K. LU
- organization
- publishing date
- 2023-12
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Nature Communications
- volume
- 14
- issue
- 1
- article number
- 5839
- publisher
- Nature Publishing Group
- external identifiers
-
- pmid:37730740
- scopus:85171812610
- ISSN
- 2041-1723
- DOI
- 10.1038/s41467-023-41541-x
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2023, Springer Nature Limited.
- id
- 760a2a25-5245-463f-837b-54f1f6b524ff
- date added to LUP
- 2024-01-12 09:47:52
- date last changed
- 2024-04-27 05:13:56
@article{760a2a25-5245-463f-837b-54f1f6b524ff,
abstract = {{<p>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.</p>}},
author = {{Reme, B. A. and Gjesvik, J. and Magnusson, K.}},
issn = {{2041-1723}},
language = {{eng}},
number = {{1}},
publisher = {{Nature Publishing Group}},
series = {{Nature Communications}},
title = {{Predictors of the post-COVID condition following mild SARS-CoV-2 infection}},
url = {{http://dx.doi.org/10.1038/s41467-023-41541-x}},
doi = {{10.1038/s41467-023-41541-x}},
volume = {{14}},
year = {{2023}},
}