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 () and Wei Wang ()
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Zhichao Feng: Central South University
Qizhi Yu: First Hospital of Changsha
Shanhu Yao: Central South University
Lei Luo: Central South University
Wenming Zhou: First Hospital of Yueyang
Xiaowen Mao: Central Hospital of Shaoyang
Jennifer Li: University of Sydney
Junhong Duan: Central South University
Zhimin Yan: Central South University
Min Yang: Central South University
Hongpei Tan: Central South University
Mengtian Ma: Central South University
Ting Li: Central South University
Dali Yi: Central South University
Ze Mi: Central South University
Huafei Zhao: Central South University
Yi Jiang: Central South University
Zhenhu He: Central South University
Huiling Li: Central South University
Wei Nie: Central South University
Yin Liu: Central South University
Jing Zhao: Central South University
Muqing Luo: Central South University
Xuanhui Liu: Second People’s Hospital of Hunan
Pengfei Rong: Central South University
Wei Wang: Central South University

Nature Communications, 2020, vol. 11, issue 1, 1-9

Abstract: Abstract The outbreak of coronavirus disease 2019 (COVID-19) has rapidly spread to become a worldwide emergency. Early identification of patients at risk of progression may facilitate more individually aligned treatment plans and optimized utilization of medical resource. Here we conducted a multicenter retrospective study involving patients with moderate COVID-19 pneumonia to investigate the utility of chest computed tomography (CT) and clinical characteristics to risk-stratify the patients. Our results show that CT severity score is associated with inflammatory levels and that older age, higher neutrophil-to-lymphocyte ratio (NLR), and CT severity score on admission are independent risk factors for short-term progression. The nomogram based on these risk factors shows good calibration and discrimination in the derivation and validation cohorts. These findings have implications for predicting the progression risk of COVID-19 pneumonia patients at the time of admission. CT examination may help risk-stratification and guide the timing of admission.

Date: 2020
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DOI: 10.1038/s41467-020-18786-x

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