Nature Communications (Oct 2020)

Early prediction of disease progression in COVID-19 pneumonia patients with chest CT and clinical characteristics

  • Zhichao Feng,
  • Qizhi Yu,
  • Shanhu Yao,
  • Lei Luo,
  • Wenming Zhou,
  • Xiaowen Mao,
  • Jennifer Li,
  • Junhong Duan,
  • Zhimin Yan,
  • Min Yang,
  • Hongpei Tan,
  • Mengtian Ma,
  • Ting Li,
  • Dali Yi,
  • Ze Mi,
  • Huafei Zhao,
  • Yi Jiang,
  • Zhenhu He,
  • Huiling Li,
  • Wei Nie,
  • Yin Liu,
  • Jing Zhao,
  • Muqing Luo,
  • Xuanhui Liu,
  • Pengfei Rong,
  • Wei Wang

DOI
https://doi.org/10.1038/s41467-020-18786-x
Journal volume & issue
Vol. 11, no. 1
pp. 1 – 9

Abstract

Read online

Early identification of COVID-19 patients at risk of progression may facilitate more individually aligned treatment plans. Here the authors develop an online nomogram incorporating CT severity score and clinical characteristics for early predicting the disease progression risk among COVID-19 pneumonia patients.