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A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography

BACKGROUND: Typical features differentiate COVID-19-associated lung injury from acute respiratory distress syndrome. The clinical role of chest computed tomography (CT) in describing the progression of COVID-19-associated lung injury remains to be clarified. We investigated in COVID-19 patients the...

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Autores principales: Pellegrini, Mariangela, Larina, Aleksandra, Mourtos, Evangelos, Frithiof, Robert, Lipcsey, Miklos, Hultström, Michael, Segelsjö, Monica, Hansen, Tomas, Perchiazzi, Gaetano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8334337/
https://www.ncbi.nlm.nih.gov/pubmed/34348797
http://dx.doi.org/10.1186/s13054-021-03685-4
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author Pellegrini, Mariangela
Larina, Aleksandra
Mourtos, Evangelos
Frithiof, Robert
Lipcsey, Miklos
Hultström, Michael
Segelsjö, Monica
Hansen, Tomas
Perchiazzi, Gaetano
author_facet Pellegrini, Mariangela
Larina, Aleksandra
Mourtos, Evangelos
Frithiof, Robert
Lipcsey, Miklos
Hultström, Michael
Segelsjö, Monica
Hansen, Tomas
Perchiazzi, Gaetano
author_sort Pellegrini, Mariangela
collection PubMed
description BACKGROUND: Typical features differentiate COVID-19-associated lung injury from acute respiratory distress syndrome. The clinical role of chest computed tomography (CT) in describing the progression of COVID-19-associated lung injury remains to be clarified. We investigated in COVID-19 patients the regional distribution of lung injury and the influence of clinical and laboratory features on its progression. METHODS: This was a prospective study. For each CT, twenty images, evenly spaced along the cranio-caudal axis, were selected. For regional analysis, each CT image was divided into three concentric subpleural regions of interest and four quadrants. Hyper-, normally, hypo- and non-inflated lung compartments were defined. Nonparametric tests were used for hypothesis testing (α = 0.05). Spearman correlation test was used to detect correlations between lung compartments and clinical features. RESULTS: Twenty-three out of 111 recruited patients were eligible for further analysis. Five hundred-sixty CT images were analyzed. Lung injury, composed by hypo- and non-inflated areas, was significantly more represented in subpleural than in core lung regions. A secondary, centripetal spread of lung injury was associated with exposure to mechanical ventilation (p < 0.04), longer spontaneous breathing (more than 14 days, p < 0.05) and non-protective tidal volume (p < 0.04). Positive fluid balance (p < 0.01), high plasma D-dimers (p < 0.01) and ferritin (p < 0.04) were associated with increased lung injury. CONCLUSIONS: In a cohort of COVID-19 patients with severe respiratory failure, a predominant subpleural distribution of lung injury is observed. Prolonged spontaneous breathing and high tidal volumes, both causes of patient self-induced lung injury, are associated to an extensive involvement of more central regions. Positive fluid balance, inflammation and thrombosis are associated with lung injury. Trial registration Study registered a priori the 20th of March, 2020. Clinical Trials ID NCT04316884. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-021-03685-4.
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spelling pubmed-83343372021-08-04 A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography Pellegrini, Mariangela Larina, Aleksandra Mourtos, Evangelos Frithiof, Robert Lipcsey, Miklos Hultström, Michael Segelsjö, Monica Hansen, Tomas Perchiazzi, Gaetano Crit Care Research BACKGROUND: Typical features differentiate COVID-19-associated lung injury from acute respiratory distress syndrome. The clinical role of chest computed tomography (CT) in describing the progression of COVID-19-associated lung injury remains to be clarified. We investigated in COVID-19 patients the regional distribution of lung injury and the influence of clinical and laboratory features on its progression. METHODS: This was a prospective study. For each CT, twenty images, evenly spaced along the cranio-caudal axis, were selected. For regional analysis, each CT image was divided into three concentric subpleural regions of interest and four quadrants. Hyper-, normally, hypo- and non-inflated lung compartments were defined. Nonparametric tests were used for hypothesis testing (α = 0.05). Spearman correlation test was used to detect correlations between lung compartments and clinical features. RESULTS: Twenty-three out of 111 recruited patients were eligible for further analysis. Five hundred-sixty CT images were analyzed. Lung injury, composed by hypo- and non-inflated areas, was significantly more represented in subpleural than in core lung regions. A secondary, centripetal spread of lung injury was associated with exposure to mechanical ventilation (p < 0.04), longer spontaneous breathing (more than 14 days, p < 0.05) and non-protective tidal volume (p < 0.04). Positive fluid balance (p < 0.01), high plasma D-dimers (p < 0.01) and ferritin (p < 0.04) were associated with increased lung injury. CONCLUSIONS: In a cohort of COVID-19 patients with severe respiratory failure, a predominant subpleural distribution of lung injury is observed. Prolonged spontaneous breathing and high tidal volumes, both causes of patient self-induced lung injury, are associated to an extensive involvement of more central regions. Positive fluid balance, inflammation and thrombosis are associated with lung injury. Trial registration Study registered a priori the 20th of March, 2020. Clinical Trials ID NCT04316884. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13054-021-03685-4. BioMed Central 2021-08-04 /pmc/articles/PMC8334337/ /pubmed/34348797 http://dx.doi.org/10.1186/s13054-021-03685-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Pellegrini, Mariangela
Larina, Aleksandra
Mourtos, Evangelos
Frithiof, Robert
Lipcsey, Miklos
Hultström, Michael
Segelsjö, Monica
Hansen, Tomas
Perchiazzi, Gaetano
A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography
title A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography
title_full A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography
title_fullStr A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography
title_full_unstemmed A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography
title_short A quantitative analysis of extension and distribution of lung injury in COVID-19: a prospective study based on chest computed tomography
title_sort quantitative analysis of extension and distribution of lung injury in covid-19: a prospective study based on chest computed tomography
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8334337/
https://www.ncbi.nlm.nih.gov/pubmed/34348797
http://dx.doi.org/10.1186/s13054-021-03685-4
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