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Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis
PURPOSE: A growing number of publications have paid close attention to the chest computed tomography (CT) detection of COVID-19 with inconsistent diagnostic accuracy, the present meta-analysis assessed the available evidence regarding the overall performance of chest CT for COVID-19. METHODS: 2 × 2...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8149579/ https://www.ncbi.nlm.nih.gov/pubmed/34055674 http://dx.doi.org/10.1007/s40336-021-00434-z |
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author | Pang, Caishuang Hou, Qingtao Yang, Zhaowei Ren, Liwei |
author_facet | Pang, Caishuang Hou, Qingtao Yang, Zhaowei Ren, Liwei |
author_sort | Pang, Caishuang |
collection | PubMed |
description | PURPOSE: A growing number of publications have paid close attention to the chest computed tomography (CT) detection of COVID-19 with inconsistent diagnostic accuracy, the present meta-analysis assessed the available evidence regarding the overall performance of chest CT for COVID-19. METHODS: 2 × 2 diagnostic table was extracted from each of the included studies. Data on specificity (SPE), sensitivity (SEN), negative likelihood ratio (LR−), positive likelihood ratio (LR+), and diagnostic odds ratio (DOR) were calculated purposefully. RESULTS: Fifteen COVID-19 related publications met our inclusion criteria and were judged qualified for the meta-analysis. The following were summary estimates for diagnostic parameters of chest CT for COVID-19: SPE, 0.49 (95% CI 46–52%); SEN, 0.94 (95% CI 93–95%); LR−, 0.15 (95% CI 11–20%); LR+, 1.93 (95% CI 145–256%); DOR, 17.14 (95% CI 918–3199%); and the area under the receiver operating characteristic curve (AUC), 0.93. CONCLUSION: Chest CT has high SEN, but the SPE is not ideal. It is highly recommended to use a combination of different diagnostic tools to achieve sufficient SEN and SPE. It should be taken into account as a diagnostic tool for current COVID-19 detection, especially for patients with symptoms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40336-021-00434-z. |
format | Online Article Text |
id | pubmed-8149579 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-81495792021-05-26 Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis Pang, Caishuang Hou, Qingtao Yang, Zhaowei Ren, Liwei Clin Transl Imaging Meta-Analysis PURPOSE: A growing number of publications have paid close attention to the chest computed tomography (CT) detection of COVID-19 with inconsistent diagnostic accuracy, the present meta-analysis assessed the available evidence regarding the overall performance of chest CT for COVID-19. METHODS: 2 × 2 diagnostic table was extracted from each of the included studies. Data on specificity (SPE), sensitivity (SEN), negative likelihood ratio (LR−), positive likelihood ratio (LR+), and diagnostic odds ratio (DOR) were calculated purposefully. RESULTS: Fifteen COVID-19 related publications met our inclusion criteria and were judged qualified for the meta-analysis. The following were summary estimates for diagnostic parameters of chest CT for COVID-19: SPE, 0.49 (95% CI 46–52%); SEN, 0.94 (95% CI 93–95%); LR−, 0.15 (95% CI 11–20%); LR+, 1.93 (95% CI 145–256%); DOR, 17.14 (95% CI 918–3199%); and the area under the receiver operating characteristic curve (AUC), 0.93. CONCLUSION: Chest CT has high SEN, but the SPE is not ideal. It is highly recommended to use a combination of different diagnostic tools to achieve sufficient SEN and SPE. It should be taken into account as a diagnostic tool for current COVID-19 detection, especially for patients with symptoms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s40336-021-00434-z. Springer International Publishing 2021-05-26 2021 /pmc/articles/PMC8149579/ /pubmed/34055674 http://dx.doi.org/10.1007/s40336-021-00434-z Text en © Italian Association of Nuclear Medicine and Molecular Imaging 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Meta-Analysis Pang, Caishuang Hou, Qingtao Yang, Zhaowei Ren, Liwei Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis |
title | Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis |
title_full | Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis |
title_fullStr | Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis |
title_full_unstemmed | Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis |
title_short | Chest computed tomography as a primary tool in COVID-19 detection: an update meta-analysis |
title_sort | chest computed tomography as a primary tool in covid-19 detection: an update meta-analysis |
topic | Meta-Analysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8149579/ https://www.ncbi.nlm.nih.gov/pubmed/34055674 http://dx.doi.org/10.1007/s40336-021-00434-z |
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