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Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience
BACKGROUND: The current outbreak of coronavirus disease 2019 (COVID-19), epi-centered in Wuhan, Hubei Province of the China, has become a global health emergency. Several studies from China have recently provided the evidence of epidemiological, clinical, laboratory, and outcomes of COVID-19 patient...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327362/ https://www.ncbi.nlm.nih.gov/pubmed/32617299 http://dx.doi.org/10.21037/atm-20-2119a |
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author | Zhou, Hua Xu, Kaijin Shen, Yihong Fang, Qiang Chen, Feng Sheng, Jifang Zhao, Feng Lou, Haiyan |
author_facet | Zhou, Hua Xu, Kaijin Shen, Yihong Fang, Qiang Chen, Feng Sheng, Jifang Zhao, Feng Lou, Haiyan |
author_sort | Zhou, Hua |
collection | PubMed |
description | BACKGROUND: The current outbreak of coronavirus disease 2019 (COVID-19), epi-centered in Wuhan, Hubei Province of the China, has become a global health emergency. Several studies from China have recently provided the evidence of epidemiological, clinical, laboratory, and outcomes of COVID-19 patients. Investigation on the role of chest CT in patient screening and management course in a large cohort remains paucity. METHODS: This was a retrospective observational study based on the data collected between January 19 and 2020 to February 15, 2020. A clinic workflow using chest CT and RT-PCR assay to screen suspected patient was reviewed. Clinical data were evaluated and patients were classified to mild, common, severe and critical group. Chest CT characteristics of each patient were evaluated and a CT scoring system was applied to grade the lung involvement. RESULTS: Of 98 enrolled patients, 1, 29, 51 and 17 were clinically classified into mild, common, severe and critical group, respectively. Eighty-three patients (84.7%) demonstrated ground-glass opacity (GGO), 76 patients (77.5%) demonstrated consolidation and 18 patients (18.4%) demonstrated crazy-paving pattern on chest CT. Based on the CT scoring, 2, 35, 55 and 6 patients were categorized to grade 0, grade 1, grade 2 and grade 3, respectively, which significantly consistent with clinical classification (kappa =0.638, P﹤0.05). Twenty-nine patients admitted from fever clinic, with an average interval of 1.2 days (range, 0–4 days) between CT examination and onset of symptom. Three of these patients had negative initial RT-PCR result while abnormalities displayed on the initial chest CT. CONCLUSIONS: Peripheral lung distributed GGO and consolidation, without subpleural sparing, are the most common manifestations on chest CT of COVID-19. Abnormalities on chest CT can occur in an early stage of COVID-19, even when RT-PCR assay negative, which may help to early recognition and rapid diagnosis of this disease. |
format | Online Article Text |
id | pubmed-7327362 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-73273622020-07-01 Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience Zhou, Hua Xu, Kaijin Shen, Yihong Fang, Qiang Chen, Feng Sheng, Jifang Zhao, Feng Lou, Haiyan Ann Transl Med Original Article BACKGROUND: The current outbreak of coronavirus disease 2019 (COVID-19), epi-centered in Wuhan, Hubei Province of the China, has become a global health emergency. Several studies from China have recently provided the evidence of epidemiological, clinical, laboratory, and outcomes of COVID-19 patients. Investigation on the role of chest CT in patient screening and management course in a large cohort remains paucity. METHODS: This was a retrospective observational study based on the data collected between January 19 and 2020 to February 15, 2020. A clinic workflow using chest CT and RT-PCR assay to screen suspected patient was reviewed. Clinical data were evaluated and patients were classified to mild, common, severe and critical group. Chest CT characteristics of each patient were evaluated and a CT scoring system was applied to grade the lung involvement. RESULTS: Of 98 enrolled patients, 1, 29, 51 and 17 were clinically classified into mild, common, severe and critical group, respectively. Eighty-three patients (84.7%) demonstrated ground-glass opacity (GGO), 76 patients (77.5%) demonstrated consolidation and 18 patients (18.4%) demonstrated crazy-paving pattern on chest CT. Based on the CT scoring, 2, 35, 55 and 6 patients were categorized to grade 0, grade 1, grade 2 and grade 3, respectively, which significantly consistent with clinical classification (kappa =0.638, P﹤0.05). Twenty-nine patients admitted from fever clinic, with an average interval of 1.2 days (range, 0–4 days) between CT examination and onset of symptom. Three of these patients had negative initial RT-PCR result while abnormalities displayed on the initial chest CT. CONCLUSIONS: Peripheral lung distributed GGO and consolidation, without subpleural sparing, are the most common manifestations on chest CT of COVID-19. Abnormalities on chest CT can occur in an early stage of COVID-19, even when RT-PCR assay negative, which may help to early recognition and rapid diagnosis of this disease. AME Publishing Company 2020-06 /pmc/articles/PMC7327362/ /pubmed/32617299 http://dx.doi.org/10.21037/atm-20-2119a Text en 2020 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Zhou, Hua Xu, Kaijin Shen, Yihong Fang, Qiang Chen, Feng Sheng, Jifang Zhao, Feng Lou, Haiyan Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience |
title | Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience |
title_full | Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience |
title_fullStr | Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience |
title_full_unstemmed | Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience |
title_short | Coronavirus disease 2019 (COVID-19): chest CT characteristics benefit to early disease recognition and patient classification—a single center experience |
title_sort | coronavirus disease 2019 (covid-19): chest ct characteristics benefit to early disease recognition and patient classification—a single center experience |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327362/ https://www.ncbi.nlm.nih.gov/pubmed/32617299 http://dx.doi.org/10.21037/atm-20-2119a |
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