Dataset Information
Auxiliary Screening COVID-19 by Serology.
Ontology highlight
ABSTRACT: 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 1st, 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.
SUBMITTER: Pan X
PROVIDER: S-EPMC9380738 | biostudies-literature | 2022
REPOSITORIES: biostudies-literature
Publications
Auxiliary Screening COVID-19 by Serology.
Frontiers in public health 20220802
<h4>Background</h4>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.<h4>Methods</h4>Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wangfang databases wer ...[more]