In:
PLOS ONE, Public Library of Science (PLoS), Vol. 18, No. 4 ( 2023-4-13), p. e0283506-
Abstract:
The main drivers of COVID-19 disease severity and the impact of COVID-19 on long-term health after recovery are yet to be fully understood. Medical imaging studies investigating COVID-19 to date have mostly been limited to small datasets and post-hoc analyses of severe cases. The UK Biobank recruited recovered SARS-CoV-2 positive individuals (n = 967) and matched controls (n = 913) who were extensively imaged prior to the pandemic and underwent follow-up scanning. In this study, we investigated longitudinal changes in body composition, as well as the associations of pre-pandemic image-derived phenotypes with COVID-19 severity. Our longitudinal analysis, in a population of mostly mild cases, associated a decrease in lung volume with SARS-CoV-2 positivity. We also observed that increased visceral adipose tissue and liver fat, and reduced muscle volume, prior to COVID-19, were associated with COVID-19 disease severity. Finally, we trained a machine classifier with demographic, anthropometric and imaging traits, and showed that visceral fat, liver fat and muscle volume have prognostic value for COVID-19 disease severity beyond the standard demographic and anthropometric measurements. This combination of image-derived phenotypes from abdominal MRI scans and ensemble learning to predict risk may have future clinical utility in identifying populations at-risk for a severe COVID-19 outcome.
Type of Medium:
Online Resource
ISSN:
1932-6203
DOI:
10.1371/journal.pone.0283506
DOI:
10.1371/journal.pone.0283506.g001
DOI:
10.1371/journal.pone.0283506.g002
DOI:
10.1371/journal.pone.0283506.g003
DOI:
10.1371/journal.pone.0283506.g004
DOI:
10.1371/journal.pone.0283506.t001
DOI:
10.1371/journal.pone.0283506.t002
DOI:
10.1371/journal.pone.0283506.t003
DOI:
10.1371/journal.pone.0283506.t004
DOI:
10.1371/journal.pone.0283506.t005
DOI:
10.1371/journal.pone.0283506.s001
DOI:
10.1371/journal.pone.0283506.s002
DOI:
10.1371/journal.pone.0283506.s003
DOI:
10.1371/journal.pone.0283506.s004
DOI:
10.1371/journal.pone.0283506.s005
DOI:
10.1371/journal.pone.0283506.r001
DOI:
10.1371/journal.pone.0283506.r002
DOI:
10.1371/journal.pone.0283506.r003
DOI:
10.1371/journal.pone.0283506.r004
DOI:
10.1371/journal.pone.0283506.r005
DOI:
10.1371/journal.pone.0283506.r006
DOI:
10.1371/journal.pone.0283506.r007
DOI:
10.1371/journal.pone.0283506.r008
Language:
English
Publisher:
Public Library of Science (PLoS)
Publication Date:
2023
detail.hit.zdb_id:
2267670-3
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