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Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans
Presently, coronavirus disease-19 (COVID-19) is spreading worldwide without an effective treatment method. For COVID-19, which is often asymptomatic, it is essential to adopt a method that does not cause aggravation, as well as a method to prevent infection. Whether aggravation can be predicted by a...
Autores principales: | , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632883/ https://www.ncbi.nlm.nih.gov/pubmed/36327268 http://dx.doi.org/10.1371/journal.pone.0276738 |
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author | Yamasaki, Yukitaka Ooka, Seido Matsuoka, Shin Tomita, Hayato Hirose, Masanori Takano, Tomonori Suzuki, Shotaro Imamura, Mitsuru Handa, Hiroshi Nishine, Hiroki Takita, Mumon Minoura, Ayu Morisawa, Kenichiro Inoue, Takeo Mineshita, Masamichi Kawahata, Kimito Takemura, Hiromu Fujitani, Shigeki Kunishima, Hiroyuki |
author_facet | Yamasaki, Yukitaka Ooka, Seido Matsuoka, Shin Tomita, Hayato Hirose, Masanori Takano, Tomonori Suzuki, Shotaro Imamura, Mitsuru Handa, Hiroshi Nishine, Hiroki Takita, Mumon Minoura, Ayu Morisawa, Kenichiro Inoue, Takeo Mineshita, Masamichi Kawahata, Kimito Takemura, Hiromu Fujitani, Shigeki Kunishima, Hiroyuki |
author_sort | Yamasaki, Yukitaka |
collection | PubMed |
description | Presently, coronavirus disease-19 (COVID-19) is spreading worldwide without an effective treatment method. For COVID-19, which is often asymptomatic, it is essential to adopt a method that does not cause aggravation, as well as a method to prevent infection. Whether aggravation can be predicted by analyzing the extent of lung damage on chest computed tomography (CT) scans was examined. The extent of lung damage on pre-intubation chest CT scans of 277 patients with COVID-19 was assessed. It was observed that aggravation occurred when the CT scan showed extensive damage associated with ground-glass opacification and/or consolidation (p < 0.0001). The extent of lung damage was similar across the upper, middle, and lower fields. Furthermore, upon comparing the extent of lung damage based on the number of days after onset, a significant difference was found between the severe pneumonia group (SPG) with intubation or those who died and non-severe pneumonia group (NSPG) ≥3 days after onset, with aggravation observed when ≥14.5% of the lungs exhibited damage at 3–5 days (sensitivity: 88.2%, specificity: 72.4%) and when ≥20.1% of the lungs exhibited damage at 6–8 days (sensitivity: 88.2%, specificity: 69.4%). Patients with aggravation suddenly developed hypoxemia after 7 days from the onset; however, chest CT scans obtained in the paucisymptomatic phase without hypoxemia indicated that subsequent aggravation could be predicted based on the degree of lung damage. Furthermore, in subjects aged ≥65 years, a significant difference between the SPG and NSPG was observed in the extent of lung damage early beginning from 3 days after onset, and it was found that the degree of lung damage could serve as a predictor of aggravation. Therefore, to predict and improve prognosis through rapid and appropriate management, evaluating patients with factors indicating poor prognosis using chest CT is essential. |
format | Online Article Text |
id | pubmed-9632883 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-96328832022-11-04 Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans Yamasaki, Yukitaka Ooka, Seido Matsuoka, Shin Tomita, Hayato Hirose, Masanori Takano, Tomonori Suzuki, Shotaro Imamura, Mitsuru Handa, Hiroshi Nishine, Hiroki Takita, Mumon Minoura, Ayu Morisawa, Kenichiro Inoue, Takeo Mineshita, Masamichi Kawahata, Kimito Takemura, Hiromu Fujitani, Shigeki Kunishima, Hiroyuki PLoS One Research Article Presently, coronavirus disease-19 (COVID-19) is spreading worldwide without an effective treatment method. For COVID-19, which is often asymptomatic, it is essential to adopt a method that does not cause aggravation, as well as a method to prevent infection. Whether aggravation can be predicted by analyzing the extent of lung damage on chest computed tomography (CT) scans was examined. The extent of lung damage on pre-intubation chest CT scans of 277 patients with COVID-19 was assessed. It was observed that aggravation occurred when the CT scan showed extensive damage associated with ground-glass opacification and/or consolidation (p < 0.0001). The extent of lung damage was similar across the upper, middle, and lower fields. Furthermore, upon comparing the extent of lung damage based on the number of days after onset, a significant difference was found between the severe pneumonia group (SPG) with intubation or those who died and non-severe pneumonia group (NSPG) ≥3 days after onset, with aggravation observed when ≥14.5% of the lungs exhibited damage at 3–5 days (sensitivity: 88.2%, specificity: 72.4%) and when ≥20.1% of the lungs exhibited damage at 6–8 days (sensitivity: 88.2%, specificity: 69.4%). Patients with aggravation suddenly developed hypoxemia after 7 days from the onset; however, chest CT scans obtained in the paucisymptomatic phase without hypoxemia indicated that subsequent aggravation could be predicted based on the degree of lung damage. Furthermore, in subjects aged ≥65 years, a significant difference between the SPG and NSPG was observed in the extent of lung damage early beginning from 3 days after onset, and it was found that the degree of lung damage could serve as a predictor of aggravation. Therefore, to predict and improve prognosis through rapid and appropriate management, evaluating patients with factors indicating poor prognosis using chest CT is essential. Public Library of Science 2022-11-03 /pmc/articles/PMC9632883/ /pubmed/36327268 http://dx.doi.org/10.1371/journal.pone.0276738 Text en © 2022 Yamasaki et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Yamasaki, Yukitaka Ooka, Seido Matsuoka, Shin Tomita, Hayato Hirose, Masanori Takano, Tomonori Suzuki, Shotaro Imamura, Mitsuru Handa, Hiroshi Nishine, Hiroki Takita, Mumon Minoura, Ayu Morisawa, Kenichiro Inoue, Takeo Mineshita, Masamichi Kawahata, Kimito Takemura, Hiromu Fujitani, Shigeki Kunishima, Hiroyuki Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans |
title | Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans |
title_full | Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans |
title_fullStr | Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans |
title_full_unstemmed | Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans |
title_short | Predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans |
title_sort | predicting the aggravation of coronavirus disease-19 pneumonia using chest computed tomography scans |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632883/ https://www.ncbi.nlm.nih.gov/pubmed/36327268 http://dx.doi.org/10.1371/journal.pone.0276738 |
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