• Linghang Wang, Yao Liu, Ting Zhang, Yuyong Jiang, Siyuan Yang, Yanli Xu, Rui Song, Meihua Song, Lin Wang, Wei Zhang, Bing Han, Li Yang, Ying Fan, Cheng Cheng, Jingjing Wang, Pan Xiang, Lin Pu, Haofeng Xiong, Chuansheng Li, Ming Zhang, Jianbo Tan, Zhihai Chen, Jingyuan Liu, and Xianbo Wang.
• Emergency Department of Infectious Diseases of Beijing Ditan Hospital, Capital Medical University, Beijing, China.
• Open Forum Infect Dis. 2020 May 1; 7 (5): ofaa169.

BackgroundThere is currently a lack of nonspecific laboratory indicators as a quantitative standard to distinguish between the 2019 coronavirus disease (COVID-19) and an influenza A or B virus infection. Thus, the aim of this study was to establish a nomogram to detect COVID-19.MethodsA nomogram was established using data collected from 457 patients (181 with COVID-19 and 276 with influenza A or B infection) in China. The nomogram used age, lymphocyte percentage, and monocyte count to differentiate COVID-19 from influenza.ResultsOur nomogram predicted probabilities of COVID-19 with an area under the receiver operating characteristic curve of 0.913 (95% confidence interval [CI], 0.883-0.937), greater than that of the lymphocyte:monocyte ratio (0.849; 95% CI, 0.812-0.880; P = .0007), lymphocyte percentage (0.808; 95% CI, 0.768-0.843; P < .0001), monocyte count (0.780; 95% CI, 0.739-0.817; P < .0001), or age (0.656; 95% CI, 0.610-0.699; P < .0001). The predicted probability conformed to the real observation outcomes of COVID-19, according to the calibration curves.ConclusionsWe found that age, lymphocyte percentage, and monocyte count are risk factors for the early-stage prediction of patients infected with the 2019 novel coronavirus. As such, our research provides a useful test for doctors to differentiate COVID-19 from influenza.© The Author(s) 2020. Published by Oxford University Press on behalf of Infectious Diseases Society of America.

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