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Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study
PURPOSE: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. METHODS: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226197/ https://www.ncbi.nlm.nih.gov/pubmed/35765661 http://dx.doi.org/10.1016/j.ejro.2022.100431 |
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author | Fischer, Tim El Baz, Yassir Scanferla, Giulia Graf, Nicole Waldeck, Frederike Kleger, Gian-Reto Frauenfelder, Thomas Bremerich, Jens Kobbe, Sabine Schmidt Pagani, Jean-Luc Schindera, Sebastian Conen, Anna Wildermuth, Simon Leschka, Sebastian Strahm, Carol Waelti, Stephan Dietrich, Tobias Johannes Albrich, Werner C. |
author_facet | Fischer, Tim El Baz, Yassir Scanferla, Giulia Graf, Nicole Waldeck, Frederike Kleger, Gian-Reto Frauenfelder, Thomas Bremerich, Jens Kobbe, Sabine Schmidt Pagani, Jean-Luc Schindera, Sebastian Conen, Anna Wildermuth, Simon Leschka, Sebastian Strahm, Carol Waelti, Stephan Dietrich, Tobias Johannes Albrich, Werner C. |
author_sort | Fischer, Tim |
collection | PubMed |
description | PURPOSE: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. METHODS: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities. RESULTS: In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19. CONCLUSIONS: This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive. |
format | Online Article Text |
id | pubmed-9226197 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-92261972022-06-24 Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study Fischer, Tim El Baz, Yassir Scanferla, Giulia Graf, Nicole Waldeck, Frederike Kleger, Gian-Reto Frauenfelder, Thomas Bremerich, Jens Kobbe, Sabine Schmidt Pagani, Jean-Luc Schindera, Sebastian Conen, Anna Wildermuth, Simon Leschka, Sebastian Strahm, Carol Waelti, Stephan Dietrich, Tobias Johannes Albrich, Werner C. Eur J Radiol Open Article PURPOSE: To compare temporal evolution of imaging features of coronavirus disease 2019 (COVID-19) and influenza in computed tomography and evaluate their predictive value for distinction. METHODS: In this retrospective, multicenter study 179 CT examinations of 52 COVID-19 and 44 influenza critically ill patients were included. Lung involvement, main pattern (ground glass opacity, crazy paving, consolidation) and additional lung and chest findings were evaluated by two independent observers. Additional findings and clinical data were compared patient-wise. A decision tree analysis was performed to identify imaging features with predictive value in distinguishing both entities. RESULTS: In contrast to influenza patients, lung involvement remains high in COVID-19 patients > 14 days after the diagnosis. The predominant pattern in COVID-19 evolves from ground glass at the beginning to consolidation in later disease. In influenza there is more consolidation at the beginning and overall less ground glass opacity (p = 0.002). Decision tree analysis yielded the following: Earlier in disease course, pleural effusion is a typical feature of influenza (p = 0.007) whereas ground glass opacities indicate COVID-19 (p = 0.04). In later disease, particularly more lung involvement (p < 0.001), but also less pleural (p = 0.005) and pericardial (p = 0.003) effusion favor COVID-19 over influenza. Regardless of time point, less lung involvement (p < 0.001), tree-in-bud (p = 0.002) and pericardial effusion (p = 0.01) make influenza more likely than COVID-19. CONCLUSIONS: This study identified differences in temporal evolution of imaging features between COVID-19 and influenza. These findings may help to distinguish both diseases in critically ill patients when laboratory findings are delayed or inconclusive. Elsevier 2022-06-24 /pmc/articles/PMC9226197/ /pubmed/35765661 http://dx.doi.org/10.1016/j.ejro.2022.100431 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Fischer, Tim El Baz, Yassir Scanferla, Giulia Graf, Nicole Waldeck, Frederike Kleger, Gian-Reto Frauenfelder, Thomas Bremerich, Jens Kobbe, Sabine Schmidt Pagani, Jean-Luc Schindera, Sebastian Conen, Anna Wildermuth, Simon Leschka, Sebastian Strahm, Carol Waelti, Stephan Dietrich, Tobias Johannes Albrich, Werner C. Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study |
title | Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study |
title_full | Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study |
title_fullStr | Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study |
title_full_unstemmed | Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study |
title_short | Comparison of temporal evolution of computed tomography imaging features in COVID-19 and influenza infections in a multicenter cohort study |
title_sort | comparison of temporal evolution of computed tomography imaging features in covid-19 and influenza infections in a multicenter cohort study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9226197/ https://www.ncbi.nlm.nih.gov/pubmed/35765661 http://dx.doi.org/10.1016/j.ejro.2022.100431 |
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