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Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis
Background: The pooled prevalence of chest computed tomography (CT) abnormalities and other detailed analysis related to patients’ biodata like gender and different age groups have not been previously described for patients with coronavirus disease 2019 (COVID-19), thus necessitating this study. Obj...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759864/ https://www.ncbi.nlm.nih.gov/pubmed/33260639 http://dx.doi.org/10.3390/diagnostics10121023 |
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author | Komolafe, Temitope Emmanuel Agbo, John Olaniyi, Ebenezer Obaloluwa Komolafe, Kayode Yang, Xiaodong |
author_facet | Komolafe, Temitope Emmanuel Agbo, John Olaniyi, Ebenezer Obaloluwa Komolafe, Kayode Yang, Xiaodong |
author_sort | Komolafe, Temitope Emmanuel |
collection | PubMed |
description | Background: The pooled prevalence of chest computed tomography (CT) abnormalities and other detailed analysis related to patients’ biodata like gender and different age groups have not been previously described for patients with coronavirus disease 2019 (COVID-19), thus necessitating this study. Objectives: To perform a meta-analysis to evaluate the diagnostic performance of chest CT, common CT morphological abnormalities, disease prevalence, biodata information, and gender prevalence of patients. Methods: Studies were identified by searching PubMed and Science Direct libraries from 1 January 2020 to 30 April 2020. Pooled CT positive rate of COVID-19 and RT-PCR, CT-imaging features, history of exposure, and biodata information were estimated using the quality effect (QE) model. Results: Out of 36 studies included, the sensitivity was 89% (95% CI: 80–96%) and 98% (95% CI: 90–100%) for chest CT and reverse transcription-polymerase chain reaction (RT-PCR), respectively. The pooled prevalence across lesion distribution were 72% (95% CI: 62–80%), 92% (95% CI: 84–97%) for lung lobe, 88% (95% CI: 81–93%) for patients with history of exposure, and 91% (95% CI: 85–96%) for patients with all categories of symptoms. Seventy-six percent (95% CI: 67–83%) had age distribution across four age groups, while the pooled prevalence was higher in the male with 54% (95% CI: 50–57%) and 46% (95% CI: 43–50%) in the female. Conclusions: The sensitivity of RT-PCR was higher than chest CT, and disease prevalence appears relatively higher in the elderly and males than children and females, respectively. |
format | Online Article Text |
id | pubmed-7759864 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-77598642020-12-26 Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis Komolafe, Temitope Emmanuel Agbo, John Olaniyi, Ebenezer Obaloluwa Komolafe, Kayode Yang, Xiaodong Diagnostics (Basel) Review Background: The pooled prevalence of chest computed tomography (CT) abnormalities and other detailed analysis related to patients’ biodata like gender and different age groups have not been previously described for patients with coronavirus disease 2019 (COVID-19), thus necessitating this study. Objectives: To perform a meta-analysis to evaluate the diagnostic performance of chest CT, common CT morphological abnormalities, disease prevalence, biodata information, and gender prevalence of patients. Methods: Studies were identified by searching PubMed and Science Direct libraries from 1 January 2020 to 30 April 2020. Pooled CT positive rate of COVID-19 and RT-PCR, CT-imaging features, history of exposure, and biodata information were estimated using the quality effect (QE) model. Results: Out of 36 studies included, the sensitivity was 89% (95% CI: 80–96%) and 98% (95% CI: 90–100%) for chest CT and reverse transcription-polymerase chain reaction (RT-PCR), respectively. The pooled prevalence across lesion distribution were 72% (95% CI: 62–80%), 92% (95% CI: 84–97%) for lung lobe, 88% (95% CI: 81–93%) for patients with history of exposure, and 91% (95% CI: 85–96%) for patients with all categories of symptoms. Seventy-six percent (95% CI: 67–83%) had age distribution across four age groups, while the pooled prevalence was higher in the male with 54% (95% CI: 50–57%) and 46% (95% CI: 43–50%) in the female. Conclusions: The sensitivity of RT-PCR was higher than chest CT, and disease prevalence appears relatively higher in the elderly and males than children and females, respectively. MDPI 2020-11-28 /pmc/articles/PMC7759864/ /pubmed/33260639 http://dx.doi.org/10.3390/diagnostics10121023 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Komolafe, Temitope Emmanuel Agbo, John Olaniyi, Ebenezer Obaloluwa Komolafe, Kayode Yang, Xiaodong Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis |
title | Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis |
title_full | Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis |
title_fullStr | Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis |
title_full_unstemmed | Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis |
title_short | Prevalence of COVID-19 Diagnostic Output with Chest Computed Tomography: A Systematic Review and Meta-Analysis |
title_sort | prevalence of covid-19 diagnostic output with chest computed tomography: a systematic review and meta-analysis |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7759864/ https://www.ncbi.nlm.nih.gov/pubmed/33260639 http://dx.doi.org/10.3390/diagnostics10121023 |
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