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Auxiliary Screening COVID-19 by Serology
BACKGROUND: The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current chara...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9380738/ https://www.ncbi.nlm.nih.gov/pubmed/35983367 http://dx.doi.org/10.3389/fpubh.2022.819841 |
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author | Pan, Xiongfeng Kaminga, Atipatsa C. Chen, Yuyao Liu, Hongying Wen, Shi Wu Fang, Yingjing Jia, Peng Liu, Aizhong |
author_facet | Pan, Xiongfeng Kaminga, Atipatsa C. Chen, Yuyao Liu, Hongying Wen, Shi Wu Fang, Yingjing Jia, Peng Liu, Aizhong |
author_sort | Pan, Xiongfeng |
collection | PubMed |
description | BACKGROUND: The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the auxiliary screening methods by serology for COVID-19 infection in real world. METHODS: Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wangfang databases were searched for relevant articles published prior to May 1(st), 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully. RESULTS: Sixty-two studies were included with 35,775 participants in the meta-analysis. Among these studies, the pooled estimates for area under the summary receiver operator characteristic of IgG and IgM to predicting COVID-19 diagnosis were 0.974 and 0.928, respectively. The IgG dOR was 209.78 (95% CI: 106.12 to 414.67). The IgM dOR was 78.17 (95% CI: 36.76 to 166.25). CONCLUSION: Our findings support serum-specific antibody detection may be the main auxiliary screening methods for COVID-19 infection in real world. |
format | Online Article Text |
id | pubmed-9380738 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93807382022-08-17 Auxiliary Screening COVID-19 by Serology Pan, Xiongfeng Kaminga, Atipatsa C. Chen, Yuyao Liu, Hongying Wen, Shi Wu Fang, Yingjing Jia, Peng Liu, Aizhong Front Public Health Public Health BACKGROUND: The 2019 novel coronavirus (COVID-19) pandemic remains rampant in many countries/regions. Improving the positive detection rate of COVID-19 infection is an important measure for control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the auxiliary screening methods by serology for COVID-19 infection in real world. METHODS: Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wangfang databases were searched for relevant articles published prior to May 1(st), 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully. RESULTS: Sixty-two studies were included with 35,775 participants in the meta-analysis. Among these studies, the pooled estimates for area under the summary receiver operator characteristic of IgG and IgM to predicting COVID-19 diagnosis were 0.974 and 0.928, respectively. The IgG dOR was 209.78 (95% CI: 106.12 to 414.67). The IgM dOR was 78.17 (95% CI: 36.76 to 166.25). CONCLUSION: Our findings support serum-specific antibody detection may be the main auxiliary screening methods for COVID-19 infection in real world. Frontiers Media S.A. 2022-08-02 /pmc/articles/PMC9380738/ /pubmed/35983367 http://dx.doi.org/10.3389/fpubh.2022.819841 Text en Copyright © 2022 Pan, Kaminga, Chen, Liu, Wen, Fang, Jia and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Pan, Xiongfeng Kaminga, Atipatsa C. Chen, Yuyao Liu, Hongying Wen, Shi Wu Fang, Yingjing Jia, Peng Liu, Aizhong Auxiliary Screening COVID-19 by Serology |
title | Auxiliary Screening COVID-19 by Serology |
title_full | Auxiliary Screening COVID-19 by Serology |
title_fullStr | Auxiliary Screening COVID-19 by Serology |
title_full_unstemmed | Auxiliary Screening COVID-19 by Serology |
title_short | Auxiliary Screening COVID-19 by Serology |
title_sort | auxiliary screening covid-19 by serology |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9380738/ https://www.ncbi.nlm.nih.gov/pubmed/35983367 http://dx.doi.org/10.3389/fpubh.2022.819841 |
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