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Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis
BACKGROUND: The outbreak of the coronavirus disease 2019 (COVID-19) has had a massive impact on the whole world. Computed tomography (CT) has been widely used in the diagnosis of this novel pneumonia. This study aims to understand the role of CT for the diagnosis and the main imaging manifestations...
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/PMC7290647/ https://www.ncbi.nlm.nih.gov/pubmed/32566559 http://dx.doi.org/10.21037/atm-20-3311 |
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author | Lv, Meng Wang, Mengshu Yang, Nan Luo, Xufei Li, Wei Chen, Xin Liu, Yunlan Ren, Mengjuan Zhang, Xianzhuo Wang, Ling Ma, Yanfang Lei, Junqiang Fukuoka, Toshio Ahn, Hyeong Sik Lee, Myeong Soo Luo, Zhengxiu Chen, Yaolong Liu, Enmei Tian, Jinhui Wang, Xiaohui |
author_facet | Lv, Meng Wang, Mengshu Yang, Nan Luo, Xufei Li, Wei Chen, Xin Liu, Yunlan Ren, Mengjuan Zhang, Xianzhuo Wang, Ling Ma, Yanfang Lei, Junqiang Fukuoka, Toshio Ahn, Hyeong Sik Lee, Myeong Soo Luo, Zhengxiu Chen, Yaolong Liu, Enmei Tian, Jinhui Wang, Xiaohui |
author_sort | Lv, Meng |
collection | PubMed |
description | BACKGROUND: The outbreak of the coronavirus disease 2019 (COVID-19) has had a massive impact on the whole world. Computed tomography (CT) has been widely used in the diagnosis of this novel pneumonia. This study aims to understand the role of CT for the diagnosis and the main imaging manifestations of patients with COVID-19. METHODS: We conducted a rapid review and meta-analysis on studies about the use of chest CT for the diagnosis of COVID-19. We comprehensively searched databases and preprint servers on chest CT for patients with COVID-19 between 1 January 2020 and 31 March 2020. The primary outcome was the sensitivity of chest CT imaging. We also conducted subgroup analyses and evaluated the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. RESULTS: A total of 103 studies with 5,673 patients were included. Using reverse transcription polymerase chain reaction (RT-PCR) results as reference, a meta-analysis based on 64 studies estimated the sensitivity of chest CT imaging in COVID-19 was 99% (95% CI, 0.97–1.00). If case reports were excluded, the sensitivity in case series was 96% (95% CI, 0.93–0.99). The sensitivity of CT scan in confirmed patients under 18 years old was only 66% (95% CI, 0.15–1.00). The most common imaging manifestation was ground-glass opacities (GGO) which was found in 75% (95% CI, 0.68–0.82) of the patients. The pooled probability of bilateral involvement was 84% (95% CI, 0.81–0.88). The most commonly involved lobes were the right lower lobe (84%, 95% CI, 0.78–0.90) and left lower lobe (81%, 95% CI, 0.74–0.87). The quality of evidence was low across all outcomes. CONCLUSIONS: In conclusion, this meta-analysis indicated that chest CT scan had a high sensitivity in diagnosis of patients with COVID-19. Therefore, CT can potentially be used to assist in the diagnosis of COVID-19. |
format | Online Article Text |
id | pubmed-7290647 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-72906472020-06-19 Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis Lv, Meng Wang, Mengshu Yang, Nan Luo, Xufei Li, Wei Chen, Xin Liu, Yunlan Ren, Mengjuan Zhang, Xianzhuo Wang, Ling Ma, Yanfang Lei, Junqiang Fukuoka, Toshio Ahn, Hyeong Sik Lee, Myeong Soo Luo, Zhengxiu Chen, Yaolong Liu, Enmei Tian, Jinhui Wang, Xiaohui Ann Transl Med Original Article BACKGROUND: The outbreak of the coronavirus disease 2019 (COVID-19) has had a massive impact on the whole world. Computed tomography (CT) has been widely used in the diagnosis of this novel pneumonia. This study aims to understand the role of CT for the diagnosis and the main imaging manifestations of patients with COVID-19. METHODS: We conducted a rapid review and meta-analysis on studies about the use of chest CT for the diagnosis of COVID-19. We comprehensively searched databases and preprint servers on chest CT for patients with COVID-19 between 1 January 2020 and 31 March 2020. The primary outcome was the sensitivity of chest CT imaging. We also conducted subgroup analyses and evaluated the quality of evidence using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. RESULTS: A total of 103 studies with 5,673 patients were included. Using reverse transcription polymerase chain reaction (RT-PCR) results as reference, a meta-analysis based on 64 studies estimated the sensitivity of chest CT imaging in COVID-19 was 99% (95% CI, 0.97–1.00). If case reports were excluded, the sensitivity in case series was 96% (95% CI, 0.93–0.99). The sensitivity of CT scan in confirmed patients under 18 years old was only 66% (95% CI, 0.15–1.00). The most common imaging manifestation was ground-glass opacities (GGO) which was found in 75% (95% CI, 0.68–0.82) of the patients. The pooled probability of bilateral involvement was 84% (95% CI, 0.81–0.88). The most commonly involved lobes were the right lower lobe (84%, 95% CI, 0.78–0.90) and left lower lobe (81%, 95% CI, 0.74–0.87). The quality of evidence was low across all outcomes. CONCLUSIONS: In conclusion, this meta-analysis indicated that chest CT scan had a high sensitivity in diagnosis of patients with COVID-19. Therefore, CT can potentially be used to assist in the diagnosis of COVID-19. AME Publishing Company 2020-05 /pmc/articles/PMC7290647/ /pubmed/32566559 http://dx.doi.org/10.21037/atm-20-3311 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 Lv, Meng Wang, Mengshu Yang, Nan Luo, Xufei Li, Wei Chen, Xin Liu, Yunlan Ren, Mengjuan Zhang, Xianzhuo Wang, Ling Ma, Yanfang Lei, Junqiang Fukuoka, Toshio Ahn, Hyeong Sik Lee, Myeong Soo Luo, Zhengxiu Chen, Yaolong Liu, Enmei Tian, Jinhui Wang, Xiaohui Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis |
title | Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis |
title_full | Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis |
title_fullStr | Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis |
title_full_unstemmed | Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis |
title_short | Chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (COVID-19): a rapid review and meta-analysis |
title_sort | chest computed tomography for the diagnosis of patients with coronavirus disease 2019 (covid-19): a rapid review and meta-analysis |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7290647/ https://www.ncbi.nlm.nih.gov/pubmed/32566559 http://dx.doi.org/10.21037/atm-20-3311 |
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