Chest CT abnormalities in COVID-19: a systematic review

Ghayda, Ramy A. and Lee, Keum Hwa and Kim, Jae Seok and Lee, Seul and Hong, Sung Hwi and Kim, Kyeong Seok and Kim, Kyeong Eon and Seok, Jinhyn and Kim, Hajeong and Seo, Jangsuk and Lee, Seungmin and Koyanagi, Ai and Jacob, Louis and Smith, Lee and Li, Han and Kronbichler, Andreas and Shin, Jae Il (2021) Chest CT abnormalities in COVID-19: a systematic review. International Journal of Medical Sciences, 18 (15). pp. 3395-3402. ISSN 1449-1907

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Official URL: https://dx.doi.org/10.7150/ijms.50568

Abstract

Computed tomography (CT) of the chest is one of the main diagnositic tools for coronavirus disease 2019 (COVID-19) infection. To document the chest CT findings in patients with confirmed COVID-19 and their association with the clinical severity, we searched related literatures through PubMed, MEDLINE, Embase, Web of Science (inception to May 4, 2020) and reviewed reference lists of previous systematic reviews. A total of 31 case reports (3768 patients) on CT findings of COVID-19 were included. The most common comorbid conditions were hypertension (18.4%) and diabetes mellitus (8.3%). The most common symptom was fever (78.7%), followed by cough (60.2%). It took an average of 5.6 days from symptom onset to admission. The most common chest CT finding was vascular enlargement (84.8%), followed by ground-glass opacity (GGO) (60.1%), air-bronchogram (47.8%), and consolidation (41.4%). Most lung lesions were located in the lung periphery (72.2%) and involved bilateral lung (76%). Most patients showed normal range of laboratory findings such as white blood cell count (96.4%) and lymphocyte (87.2%). Compared to previous published meta-analyses, our study is the first to summarize the different radiologic characteristics of chest CT in a total of 3768 COVID-19 patients by compiling case series studies. A comprehensive diagnostic approach should be adopted for patients with known COVID-19, suspected cases, and for exposed individuals.

Item Type: Journal Article
Keywords: CT, COVID-19, Systematic Review, Coronavirus disease 2019, Computed tomography
Faculty: COVID-19 Research Collection
Faculty of Science & Engineering
SWORD Depositor: Symplectic User
Depositing User: Symplectic User
Date Deposited: 09 Nov 2020 14:24
Last Modified: 06 Jan 2022 16:12
URI: https://arro.anglia.ac.uk/id/eprint/706034

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