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Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study.
Background Acute respiratory distress syndrome (ARDS) is a severe form of acute lung injury commonly associated with pneumonia, including coronavirus disease-19 (COVID-19). The resultant effect can be persistent lung damage, but its extent is not known. We used quantitative high resolution computed...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
F1000 Research Limited
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10182379/ https://www.ncbi.nlm.nih.gov/pubmed/37224317 http://dx.doi.org/10.12688/f1000research.75311.3 |
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author | Dolinay, Tamas Jun, Dale Maller, Abigail Chung, Augustine Grimes, Brandon Hsu, Lillian Nelson, David Villagas, Bianca Kim, Grace Hyun J Goldin, Jonathan |
author_facet | Dolinay, Tamas Jun, Dale Maller, Abigail Chung, Augustine Grimes, Brandon Hsu, Lillian Nelson, David Villagas, Bianca Kim, Grace Hyun J Goldin, Jonathan |
author_sort | Dolinay, Tamas |
collection | PubMed |
description | Background Acute respiratory distress syndrome (ARDS) is a severe form of acute lung injury commonly associated with pneumonia, including coronavirus disease-19 (COVID-19). The resultant effect can be persistent lung damage, but its extent is not known. We used quantitative high resolution computed tomography (QHR-CT) lung scans to radiographically characterize the lung damage in COVID-19 ARDS (CARDS) survivors. Methods Patients with CARDS (N=20) underwent QHR-CT lung scans 60 to 90 days after initial diagnosis, while hospitalized at a long-term acute care hospital (LTACH). QHR-CT assessed for mixed disease (QMD), ground glass opacities (QGGO), consolidation (QCON) and normal lung tissue (QNL). QMD was correlated with respiratory support on admission, tracheostomy decannulation and supplementary oxygen need on discharge. Results Sixteen patients arrived with tracheostomy requiring invasive mechanical ventilation. Four patients arrived on nasal oxygen support. Of the patients included in this study 10 had the tracheostomy cannula removed, four remained on invasive ventilation, and two died. QHR-CT showed 45% QMD, 28.1% QGGO, 3.0% QCON and QNL=23.9%. Patients with mandatory mechanical ventilation had the highest proportion of QMD when compared to no mechanical ventilation. There was no correlation between QMD and tracheostomy decannulation or need for supplementary oxygen at discharge. Conclusions Our data shows severe ongoing lung injury in patients with CARDS, beyond what is usually expected in ARDS. In this severely ill population, the extent of mixed disease correlates with mechanical ventilation, signaling formation of interstitial lung disease. QHR-CT analysis can be useful in the post-acute setting to evaluate for interstitial changes in ARDS. |
format | Online Article Text |
id | pubmed-10182379 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | F1000 Research Limited |
record_format | MEDLINE/PubMed |
spelling | pubmed-101823792023-05-14 Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study. Dolinay, Tamas Jun, Dale Maller, Abigail Chung, Augustine Grimes, Brandon Hsu, Lillian Nelson, David Villagas, Bianca Kim, Grace Hyun J Goldin, Jonathan F1000Res Research Article Background Acute respiratory distress syndrome (ARDS) is a severe form of acute lung injury commonly associated with pneumonia, including coronavirus disease-19 (COVID-19). The resultant effect can be persistent lung damage, but its extent is not known. We used quantitative high resolution computed tomography (QHR-CT) lung scans to radiographically characterize the lung damage in COVID-19 ARDS (CARDS) survivors. Methods Patients with CARDS (N=20) underwent QHR-CT lung scans 60 to 90 days after initial diagnosis, while hospitalized at a long-term acute care hospital (LTACH). QHR-CT assessed for mixed disease (QMD), ground glass opacities (QGGO), consolidation (QCON) and normal lung tissue (QNL). QMD was correlated with respiratory support on admission, tracheostomy decannulation and supplementary oxygen need on discharge. Results Sixteen patients arrived with tracheostomy requiring invasive mechanical ventilation. Four patients arrived on nasal oxygen support. Of the patients included in this study 10 had the tracheostomy cannula removed, four remained on invasive ventilation, and two died. QHR-CT showed 45% QMD, 28.1% QGGO, 3.0% QCON and QNL=23.9%. Patients with mandatory mechanical ventilation had the highest proportion of QMD when compared to no mechanical ventilation. There was no correlation between QMD and tracheostomy decannulation or need for supplementary oxygen at discharge. Conclusions Our data shows severe ongoing lung injury in patients with CARDS, beyond what is usually expected in ARDS. In this severely ill population, the extent of mixed disease correlates with mechanical ventilation, signaling formation of interstitial lung disease. QHR-CT analysis can be useful in the post-acute setting to evaluate for interstitial changes in ARDS. F1000 Research Limited 2023-03-31 /pmc/articles/PMC10182379/ /pubmed/37224317 http://dx.doi.org/10.12688/f1000research.75311.3 Text en Copyright: © 2023 Dolinay T et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Dolinay, Tamas Jun, Dale Maller, Abigail Chung, Augustine Grimes, Brandon Hsu, Lillian Nelson, David Villagas, Bianca Kim, Grace Hyun J Goldin, Jonathan Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study. |
title | Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study. |
title_full | Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study. |
title_fullStr | Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study. |
title_full_unstemmed | Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study. |
title_short | Quantitative image analysis in COVID-19 acute respiratory distress syndrome: a cohort observational study. |
title_sort | quantitative image analysis in covid-19 acute respiratory distress syndrome: a cohort observational study. |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10182379/ https://www.ncbi.nlm.nih.gov/pubmed/37224317 http://dx.doi.org/10.12688/f1000research.75311.3 |
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