Tags

Type your tag names separated by a space and hit enter

CT imaging features of 4121 patients with COVID-19: A meta-analysis.
J Med Virol. 2020 07; 92(7):891-902.JM

Abstract

OBJECTIVE

We systematically reviewed the computed tomography (CT) imaging features of coronavirus disease 2019 (COVID-19) 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 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

A total of 34 retrospective studies involving a total of 4121 patients with COVID-19 were included. The results of the meta-analysis showed that most patients presented bilateral lung involvement (73.8%, 95% confidence interval [CI]: 65.9%-81.1%) or multilobar involvement (67.3%, 95% CI: 54.8%-78.7%) and just little patients showed normal CT findings (8.4%). We found that the most common changes in lesion density were 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 patients with COVID-19. 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.

Authors+Show Affiliations

Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.Department of Emergency, The Second Affiliated Hospital of Guangxi Medical University, Nanning, China.

Pub Type(s)

Journal Article
Meta-Analysis
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

32314805

Citation

Zhu, Jieyun, et al. "CT Imaging Features of 4121 Patients With COVID-19: a Meta-analysis." Journal of Medical Virology, vol. 92, no. 7, 2020, pp. 891-902.
Zhu J, Zhong Z, Li H, et al. CT imaging features of 4121 patients with COVID-19: A meta-analysis. J Med Virol. 2020;92(7):891-902.
Zhu, J., Zhong, Z., Li, H., Ji, P., Pang, J., Li, B., & Zhang, J. (2020). CT imaging features of 4121 patients with COVID-19: A meta-analysis. Journal of Medical Virology, 92(7), 891-902. https://doi.org/10.1002/jmv.25910
Zhu J, et al. CT Imaging Features of 4121 Patients With COVID-19: a Meta-analysis. J Med Virol. 2020;92(7):891-902. PubMed PMID: 32314805.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - CT imaging features of 4121 patients with COVID-19: A meta-analysis. AU - Zhu,Jieyun, AU - Zhong,Zhimei, AU - Li,Hongyuan, AU - Ji,Pan, AU - Pang,Jielong, AU - Li,Bocheng, AU - Zhang,Jianfeng, Y1 - 2020/04/29/ PY - 2020/03/23/received PY - 2020/04/18/accepted PY - 2020/4/22/pubmed PY - 2020/6/25/medline PY - 2020/4/22/entrez KW - computed tomography KW - coronavirus disease 2019 KW - imaging features KW - meta-analysis KW - pneumonia KW - systematical review SP - 891 EP - 902 JF - Journal of medical virology JO - J Med Virol VL - 92 IS - 7 N2 - OBJECTIVE: We systematically reviewed the computed tomography (CT) imaging features of coronavirus disease 2019 (COVID-19) 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 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: A total of 34 retrospective studies involving a total of 4121 patients with COVID-19 were included. The results of the meta-analysis showed that most patients presented bilateral lung involvement (73.8%, 95% confidence interval [CI]: 65.9%-81.1%) or multilobar involvement (67.3%, 95% CI: 54.8%-78.7%) and just little patients showed normal CT findings (8.4%). We found that the most common changes in lesion density were 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 patients with COVID-19. 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. SN - 1096-9071 UR - https://www.unboundmedicine.com/medline/citation/32314805/CT_imaging_features_of_4121_patients_with_COVID_19:_A_meta_analysis_ L2 - https://doi.org/10.1002/jmv.25910 DB - PRIME DP - Unbound Medicine ER -