Early prediction of disease progression in COVID- 19 pneumonia patients with chest CT and clinical characteristics
Data
2020Autor
Feng, Zhichao
Yu, Qizhi
Yao, Shanhu
Luo, Lei
Zhou, Wenming
Mao, Xiaowen
Li, Jennifer
Duan, Junhong
Yan, Zhimin
Yang, Min
Tan, Hongpei
Ma, Mengtian
Li, Ting
Yi, Dali
Mi, Ze
Zhao, Huafei
Jiang, Yi
He, Zhenhu
Li, Huiling
Nie, Wei
Liu, Yin
Zhao, Jing
Luo, Muqing
Liu, Xuanhui
Rong, Pengfei
Wang, Wei
Metadata
Mostrar registro completoResumo
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.
Palabras clave
Early prediction; Disease progression; COVID-19; Pneumonia patientsLink para o recurso
https://doi.org/10.1038/s41467-020-18786-xCollections
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