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A systematic review and meta-analysis of children with coronavirus disease 2019 (COVID-19).

Xiaojian CuiZhihu ZhaoTongqiang ZhangWei GuoWenwei GuoJiafeng ZhengJiayi ZhangCuicui DongRen NaLisheng ZhengWenliang LiZihui LiuJia MaJinhu WangSijia HeYongsheng XuPing SiYongming ShenChunquan Cai
Published in: Journal of medical virology (2020)
To provide a comprehensive and systematic analysis of demographic characteristics, clinical symptoms, laboratory findings, and imaging features of coronavirus disease 2019 (COVID-19) in pediatric patients. A meta-analysis was carried out to identify studies on COVID-19 from 25 December 2019 to 30 April 2020. A total of 48 studies with 5829 pediatric patients were included. Children of all ages were at risk for COVID-19. The main illness classification ranged as: 20% (95% confidence interval [CI]: 14%-26%; I2  = 91.4%) asymptomatic, 33% (95% CI: 23%-43%; I2  = 95.6%) mild and 51% (95% CI: 42%-61%; I2  = 93.4%) moderate. The typical clinical manifestations were fever 51% (95% CI: 45%-57%; I2  = 78.9%) and cough 41% (95% CI: 35%-47%, I2  = 81.0%). The common laboratory findings were normal white blood cell 69% (95% CI: 64%-75%; I2  = 58.5%), lymphopenia 16% (95% CI: 11%-21%; I2  = 76.9%) and elevated creatine-kinase MB 37% (95% CI: 25%-48%; I2  = 59.0%). The frequent imaging features were normal images 41% (95% CI: 30%-52%; I2  = 93.4%) and ground-glass opacity 36% (95% CI: 25%-47%; I2  = 92.9%). Among children under 1 year old, critical cases account for 14% (95% CI: 13%-34%; I2  = 37.3%) that should be of concern. In addition, vomiting occurred in 33% (95% CI: 18%-67%; I2  = 0.0%) cases that may also need attention. Pediatric patients with COVID-19 may experience milder illness with atypical clinical manifestations and rare lymphopenia. High incidence of critical illness and vomiting symptoms reward attention in children under 1 year old.
Keyphrases
  • coronavirus disease
  • sars cov
  • young adults
  • respiratory syndrome coronavirus
  • high resolution
  • machine learning
  • working memory
  • physical activity
  • single cell
  • cell therapy
  • convolutional neural network