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J Med Virol. CT imaging features of 4,121 patients with COVI

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  • J Med Virol. CT imaging features of 4,121 patients with COVI


    J Med Virol. 2020 Apr 21. doi: 10.1002/jmv.25910. [Epub ahead of print]
    CT imaging features of 4,121 patients with COVID-19: a meta-analysis.


    Zhu J1, Zhong Z1, Li H1, Ji P1, Pang J1, Li B1, Zhang J1.

    Author information




    Abstract

    OBJECTIVE:

    We systematically reviewed the CT imaging features of COVID-19 in order to provide reference for clinical practice.
    METHODS:

    Our article comprehensively searched PubMed, FMRS, EMbase, CNKI,WanFang databases and VIP databases to collect literatures about the CT imaging features of COVID-19 from 1 January 2020 to 16 March 2020. Three reviewers independently screened literature, extracted data and assessed the risk of bias of included studies, and then, this meta-analysis was performed by using Stata12.0 software.
    RESULTS:

    34 retrospective studies involving a total of 4 121 COVID-19 patients were included. The results of meta-analysis showed that most patients presented bilateral lung involvement (73.8%, 95%CI: 65.9%-81.1%) or multilobar involvement (67.3%,95%CI: 54.8%-78.7 %) and just a little patients showed normal CT findings (8.4%). We found that the most common changes in lesion density was ground-glass opacities (68.1%,95%CI: 56.9%-78.2%). Other changes in density included air bronchogram sign(44.7%), crazy-paving pattern (35.6%) and consolidation (32.0%). Patchy (40.3%), spider web sign (39.5%), cord-like (36.8%) and nodular (20.5%) were common lesion shapes in COVID-19 patients. Pleural thickening (27.1%) was found in some patients. Lymphadenopathy(5.4%) and pleural effusion (5.3%) were rare.
    CONCLUSION:

    The lung lesions of patients with COVID-19 were mostly bilateral lungs or multilobar involved. The most common chest CT findings were patchy and ground-glass opacities. Some patients had air bronchogram, spider web sign and cord-like. Lymphadenopathy and pleural effusion were rare. This article is protected by copyright. All rights reserved.
    This article is protected by copyright. All rights reserved.



    KEYWORDS:

    Computed tomography; Coronavirus disease 2019; Imaging features; Meta-analysis; Pneumonia; Systematical review


    PMID:32314805DOI:10.1002/jmv.25910

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