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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
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.
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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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