Clinical Characteristics of Children With COVID-19: A Meta-Analysis
- PMID: 32719759
- PMCID: PMC7350605
- DOI: 10.3389/fped.2020.00431
Clinical Characteristics of Children With COVID-19: A Meta-Analysis
Abstract
Background: With the global spread of novel coronavirus disease 2019 (COVID-19), health care systems are facing formidable challenges. Scientists are conducting studies to explore this new disease, and numerous studies have been shared. However, the number of studies on children with COVID-19 is limited, and no meta-analysis of this group has been performed. Methods: A random-effect meta-analysis was conducted to determine the characteristics of children with COVID-19, including their demographic, epidemiological, clinical, laboratory, imaging features, and outcomes. Four databases and reference lists were screened. Percentages were calculated, and pooled prevalence with 95% confidence intervals (CIs) were reported. Results: Of 195 studies, 33 were selected, and 14 (371 patients) of them were included in the meta-analysis. Then, 19 case reports (25 patients) were summarized separately. Our meta-analysis revealed that 17.4% (95% CI = 9.1-27.3) of children had asymptomatic infection. Fever (51.2%, 95% CI = 40.2-62.2) and cough (37.0%, 95% CI = 25.9-48.8) were the most frequent symptoms. The prevalence of severe or critical illness was almost 0% (95% CI = 0-1.0). The most frequent abnormal laboratory findings, in pediatric patients, were leukopenia/lymphopenia (28.9%, 95% CI = 19.5-39.2) and increased creatine kinase (20.1%, 95% CI = 1.3-49.9). Ground-glass opacity was observed in the CT scan of 53.9% (95% CI = 38.4-68.7) of children diagnosed with pneumonia. Conclusions: Children are at a lower risk of developing COVID-19 and have a milder disease than adults. However, the evidence presented in this study is not satisfactory. Further investigations are urgently needed, and our data will be continuously updated.
Keywords: SARS-CoV-2; children; clinical characteristics; coronavirus disease 2019; epidemic.
Copyright © 2020 Ding, Yan and Guo.
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