AUTHOR=Pan Xiongfeng , Chen Yuyao , Kaminga Atipatsa C. , Wen Shi Wu , Liu Hongying , Jia Peng , Liu Aizhong 

TITLE=Auxiliary screening COVID-19 by computed tomography

JOURNAL=Frontiers in Public Health

VOLUME=11

YEAR=2023

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2023.974542

DOI=10.3389/fpubh.2023.974542

ISSN=2296-2565

ABSTRACT=<sec><title>Background</title><p>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 the control and prevention of this pandemic. This meta-analysis aims to systematically summarize the current characteristics of the computed tomography (CT) auxiliary screening methods for COVID-19 infection in the real world.</p></sec><sec><title>Methods</title><p>Web of Science, Cochrane Library, Embase, PubMed, CNKI, and Wanfang databases were searched for relevant articles published prior to 1 September 2022. Data on specificity, sensitivity, positive/negative likelihood ratio, area under curve (AUC), and diagnostic odds ratio (dOR) were calculated purposefully.</p></sec><sec><title>Results</title><p>One hundred and fifteen studies were included with 51,500 participants in the meta-analysis. Among these studies, the pooled estimates for AUC of CT in confirmed cases, and CT in suspected cases to predict COVID-19 diagnosis were 0.76 and 0.85, respectively. The CT in confirmed cases dOR was 5.51 (95% CI: 3.78–8.02). The CT in suspected cases dOR was 13.12 (95% CI: 11.07–15.55).</p></sec><sec><title>Conclusion</title><p>Our findings support that CT detection may be the main auxiliary screening method for COVID-19 infection in the real world.</p></sec>