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Computed tomography features of COVID-19 in children: A systematic review and meta-analysis
BACKGROUND: There are few reports on the chest computed tomography (CT) imaging features of children with coronavirus disease 2019 (COVID-19), and most reports involve small sample sizes. OBJECTIVES: To systematically analyze the chest CT imaging features of children with COVID-19 and provide refere...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Lippincott Williams & Wilkins
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462638/ https://www.ncbi.nlm.nih.gov/pubmed/34559092 http://dx.doi.org/10.1097/MD.0000000000022571 |
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author | Wang, Ji-gan Mo, Yu-fang Su, Yu-heng Wang, Li-chuan Liu, Guang-bing Li, Meng Qin, Qian-qiu |
author_facet | Wang, Ji-gan Mo, Yu-fang Su, Yu-heng Wang, Li-chuan Liu, Guang-bing Li, Meng Qin, Qian-qiu |
author_sort | Wang, Ji-gan |
collection | PubMed |
description | BACKGROUND: There are few reports on the chest computed tomography (CT) imaging features of children with coronavirus disease 2019 (COVID-19), and most reports involve small sample sizes. OBJECTIVES: To systematically analyze the chest CT imaging features of children with COVID-19 and provide references for clinical practice. DATA SOURCES: We searched PubMed, Web of Science, and Embase; data published by Johns Hopkins University; and Chinese databases CNKI, Wanfang, and Chongqing Weipu. METHODS: Reports on chest CT imaging features of children with COVID-19 from January 1, 2020 to August 10, 2020, were analyzed retrospectively and a meta-analysis carried out using Stata12.0 software. RESULTS: Thirty-seven articles (1747 children) were included in this study. The heterogeneity of meta-analysis results ranged from 0% to 90.5%. The overall rate of abnormal lung CT findings was 63.2% (95% confidence interval [CI]: 55.8%–70.6%), with a rate of 61.0% (95% CI: 50.8%–71.2%) in China and 67.8% (95% CI: 57.1%–78.4%) in the rest of the world in the subgroup analysis. The incidence of ground-glass opacities was 39.5% (95% CI: 30.7%–48.3%), multiple lung lobe lesions was 65.1% (95% CI: 55.1%–67.9%), and bilateral lung lesions was 61.5% (95% CI: 58.8%–72.2%). Other imaging features included nodules (25.7%), patchy shadows (36.8%), halo sign (24.8%), consolidation (24.1%), air bronchogram signs (11.2%), cord-like shadows (9.7%), crazy-paving pattern (6.1%), and pleural effusion (9.1%). Two articles reported 3 cases of white lung, another reported 2 cases of pneumothorax, and another 1 case of bullae. CONCLUSIONS: The lung CT results of children with COVID-19 are usually normal or slightly atypical. The lung lesions of COVID-19 pediatric patients mostly involve both lungs or multiple lobes, and the common manifestations are patchy shadows, ground-glass opacities, consolidation, partial air bronchogram signs, nodules, and halo signs; white lung, pleural effusion, and paving stone signs are rare. Therefore, chest CT has limited value as a screening tool for children with COVID-19 and can only be used as an auxiliary assessment tool. |
format | Online Article Text |
id | pubmed-8462638 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Lippincott Williams & Wilkins |
record_format | MEDLINE/PubMed |
spelling | pubmed-84626382021-09-27 Computed tomography features of COVID-19 in children: A systematic review and meta-analysis Wang, Ji-gan Mo, Yu-fang Su, Yu-heng Wang, Li-chuan Liu, Guang-bing Li, Meng Qin, Qian-qiu Medicine (Baltimore) 6200 BACKGROUND: There are few reports on the chest computed tomography (CT) imaging features of children with coronavirus disease 2019 (COVID-19), and most reports involve small sample sizes. OBJECTIVES: To systematically analyze the chest CT imaging features of children with COVID-19 and provide references for clinical practice. DATA SOURCES: We searched PubMed, Web of Science, and Embase; data published by Johns Hopkins University; and Chinese databases CNKI, Wanfang, and Chongqing Weipu. METHODS: Reports on chest CT imaging features of children with COVID-19 from January 1, 2020 to August 10, 2020, were analyzed retrospectively and a meta-analysis carried out using Stata12.0 software. RESULTS: Thirty-seven articles (1747 children) were included in this study. The heterogeneity of meta-analysis results ranged from 0% to 90.5%. The overall rate of abnormal lung CT findings was 63.2% (95% confidence interval [CI]: 55.8%–70.6%), with a rate of 61.0% (95% CI: 50.8%–71.2%) in China and 67.8% (95% CI: 57.1%–78.4%) in the rest of the world in the subgroup analysis. The incidence of ground-glass opacities was 39.5% (95% CI: 30.7%–48.3%), multiple lung lobe lesions was 65.1% (95% CI: 55.1%–67.9%), and bilateral lung lesions was 61.5% (95% CI: 58.8%–72.2%). Other imaging features included nodules (25.7%), patchy shadows (36.8%), halo sign (24.8%), consolidation (24.1%), air bronchogram signs (11.2%), cord-like shadows (9.7%), crazy-paving pattern (6.1%), and pleural effusion (9.1%). Two articles reported 3 cases of white lung, another reported 2 cases of pneumothorax, and another 1 case of bullae. CONCLUSIONS: The lung CT results of children with COVID-19 are usually normal or slightly atypical. The lung lesions of COVID-19 pediatric patients mostly involve both lungs or multiple lobes, and the common manifestations are patchy shadows, ground-glass opacities, consolidation, partial air bronchogram signs, nodules, and halo signs; white lung, pleural effusion, and paving stone signs are rare. Therefore, chest CT has limited value as a screening tool for children with COVID-19 and can only be used as an auxiliary assessment tool. Lippincott Williams & Wilkins 2021-09-24 /pmc/articles/PMC8462638/ /pubmed/34559092 http://dx.doi.org/10.1097/MD.0000000000022571 Text en Copyright © 2021 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC), where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc/4.0 (https://creativecommons.org/licenses/by-nc/4.0/) |
spellingShingle | 6200 Wang, Ji-gan Mo, Yu-fang Su, Yu-heng Wang, Li-chuan Liu, Guang-bing Li, Meng Qin, Qian-qiu Computed tomography features of COVID-19 in children: A systematic review and meta-analysis |
title | Computed tomography features of COVID-19 in children: A systematic review and meta-analysis |
title_full | Computed tomography features of COVID-19 in children: A systematic review and meta-analysis |
title_fullStr | Computed tomography features of COVID-19 in children: A systematic review and meta-analysis |
title_full_unstemmed | Computed tomography features of COVID-19 in children: A systematic review and meta-analysis |
title_short | Computed tomography features of COVID-19 in children: A systematic review and meta-analysis |
title_sort | computed tomography features of covid-19 in children: a systematic review and meta-analysis |
topic | 6200 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8462638/ https://www.ncbi.nlm.nih.gov/pubmed/34559092 http://dx.doi.org/10.1097/MD.0000000000022571 |
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