دورية أكاديمية
Abdominal imaging associates body composition with COVID-19 severity.
| العنوان: | Abdominal imaging associates body composition with COVID-19 severity. |
|---|---|
| المؤلفون: | Nicolas Basty, Elena P Sorokin, Marjola Thanaj, Ramprakash Srinivasan, Brandon Whitcher, Jimmy D Bell, Madeleine Cule, E Louise Thomas |
| المصدر: | PLoS ONE, Vol 18, Iss 4, p e0283506 (2023) |
| بيانات النشر: | Public Library of Science (PLoS), 2023. |
| سنة النشر: | 2023 |
| المجموعة: | LCC:Medicine LCC:Science |
| مصطلحات موضوعية: | Medicine, Science |
| الوصف: | 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. |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1932-6203 |
| العلاقة: | https://doaj.org/toc/1932-6203Test |
| DOI: | 10.1371/journal.pone.0283506 |
| الوصول الحر: | https://doaj.org/article/2ff79284e3be4a60980fd06f706c3bd6Test |
| رقم الانضمام: | edsdoj.2ff79284e3be4a60980fd06f706c3bd6 |
| قاعدة البيانات: | Directory of Open Access Journals |
Full Text Finder | تدمد: | 19326203 |
|---|---|
| DOI: | 10.1371/journal.pone.0283506 |