Open forum infectious diseases · 2020
Differentiating Between 2019 Novel Coronavirus Pneumonia and Influenza Using a Nonspecific Laboratory Marker-Based Dynamic Nomogram.
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Wang Linghang, Liu Yao, Zhang Ting, Jiang Yuyong, Yang Siyuan, Xu Yanli, Song Rui, Song Meihua, Wang Lin, Zhang Wei, Han Bing, Yang Li, Fan Ying, Cheng Cheng, Wang Jingjing, Xiang Pan, Pu Lin, Xiong Haofeng, Li Chuansheng, Zhang Ming, Tan Jianbo, Chen Zhihai, Liu Jingyuan, Wang Xianbo
Аннотация
BACKGROUND: There 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.
METHODS: A 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.
RESULTS: Our 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.
CONCLUSIONS: We 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.
METHODS: A 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.
RESULTS: Our 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.
CONCLUSIONS: We 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.