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

• Published in: Nature communications Vol. 11; no. 1; pp. 4968 - 9
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 02.10.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 692/499; 692/699/255; 692/700/1421; Adult; Betacoronavirus; Chest; China; Clinical Laboratory Techniques; Coinfection; Computed tomography; Coronavirus Infections - diagnosis; Coronavirus Infections - pathology; Coronavirus Infections - physiopathology; Coronaviruses; COVID-19; COVID-19 Testing; Disease Progression; Female; Health services; Hospitalization; Humanities and Social Sciences; Humans; Inflammation; Lung - diagnostic imaging; Lung - pathology; Lymphocytes; Male; Middle Aged; multidisciplinary; Neutrophils; Nomograms; Pandemics; Patients; Pneumonia; Pneumonia, Viral - diagnosis; Pneumonia, Viral - pathology; Pneumonia, Viral - physiopathology; Regression Analysis; Retrospective Studies; Risk analysis; Risk Assessment; Risk Factors; SARS-CoV-2; Science; Science (multidisciplinary); Tomography, X-Ray Computed - methods; Viral diseases; China
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-18786-x

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. 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.