23.04.2020
CT imaging features of 4,121 patients with COVID-19: a meta-analysis
Epidemiology Radiology
Zhu J et al
J Med Virol
Main result
34 retrospective studies with a total of 4,121 COVID-19 patients were included. All studies were conducted in China. All studies were of high quality.
The results of the meta-analysis showed that most patients had bilateral (73.8%, 95% CI: 65.9%-81.1%) or multilobular (67.3%, 95% CI: 54.8%-78.7%) lung involvement and only a few patients had normal CT scan results (8.4%).
The most frequent 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%). The most common forms of lesion in patients treated with COVID-19 were spotted (40.3%), spider web (39.5%), cord (36.8%), and nodular (20.5%). Pleural thickening (27.1%) was observed in some patients. Lymphadenopathy (5.4%) and pleural effusion (5.3%) were rare.
The results of the meta-analysis showed that most patients had bilateral (73.8%, 95% CI: 65.9%-81.1%) or multilobular (67.3%, 95% CI: 54.8%-78.7%) lung involvement and only a few patients had normal CT scan results (8.4%).
The most frequent 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%). The most common forms of lesion in patients treated with COVID-19 were spotted (40.3%), spider web (39.5%), cord (36.8%), and nodular (20.5%). Pleural thickening (27.1%) was observed in some patients. Lymphadenopathy (5.4%) and pleural effusion (5.3%) were rare.
Takeaways
In summary, most patients had bilateral or multilobular lung involvement. The most common changes were ground-glass opacities and airway bronchogram findings. The other most frequent changes were spots, spider web sign, etc. Lymphadenopathy and pleural effusion were rare. However, due to the quality and quantity of the included studies, the above conclusions need to be confirmed by other high quality studies.
Strength of evidence Moderate
- A large sample size and high quality of the included studies.
- Most of the included studies are monocentric; most of the included studies did not specify inclusion or exclusion criteria, disease course and severity were not the same; all included studies are retrospective studies; this meta-analysis revealed significant heterogeneity between studies.
- Subgroup analysis fails to eliminate all sources of heterogeneity, which may affect the accuracy of the meta-analysis results.
Objectives
Summarize the characteristics of COVID-19 CT imaging to provide a reference for future clinical practice.
Method
Searches of PubMed, FMRS, EMbase, CNKI, WanFang and VIP databases to collect literature on the CT imaging characteristics of COVID-19 from January 1, 2020 to March 16, 2020.
The criteria for inclusion were as follows: (1) Cohort studies, case-control studies, and case-series studies; (2) The study population consisted of patients diagnosed with COVID-19; (3) The observational indicators were CT imaging results from chest CT or CTRCT.
The exclusion criteria were as follows: (1) Overlap or duplication of studies; (2) Absence of clinical indicators or necessary data that could not be obtained even by contacting the author; (3) Case reports and studies with a sample size less than 30.
Three reviewers independently reviewed the literature, extracted data, and assessed the potential for bias in the included studies, and this meta-analysis was conducted using Stata12.0 software.
Subgroup analyses were conducted by region and study sample size. Sensitivity analysis was also performed by excluding each study individually.
The criteria for inclusion were as follows: (1) Cohort studies, case-control studies, and case-series studies; (2) The study population consisted of patients diagnosed with COVID-19; (3) The observational indicators were CT imaging results from chest CT or CTRCT.
The exclusion criteria were as follows: (1) Overlap or duplication of studies; (2) Absence of clinical indicators or necessary data that could not be obtained even by contacting the author; (3) Case reports and studies with a sample size less than 30.
Three reviewers independently reviewed the literature, extracted data, and assessed the potential for bias in the included studies, and this meta-analysis was conducted using Stata12.0 software.
Subgroup analyses were conducted by region and study sample size. Sensitivity analysis was also performed by excluding each study individually.
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