A nomogramic model based on clinical and laboratory parameters at admission for predicting the survival of COVID-19 pati
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RESEARCH ARTICLE
Open Access
A nomogramic model based on clinical and laboratory parameters at admission for predicting the survival of COVID-19 patients Xiaojun Ma1†, Huifang Wang2†, Junwei Huang3†, Yan Geng4†, Shuqi Jiang5, Qiuping Zhou5, Xuan Chen6, Hongping Hu7, Weifeng Li8, Chengbin Zhou9, Xinglin Gao3, Na Peng10,11* and Yiyu Deng2*
Abstract Background: COVID-19 has become a major global threat. The present study aimed to develop a nomogram model to predict the survival of COVID-19 patients based on their clinical and laboratory data at admission. Methods: COVID-19 patients who were admitted at Hankou Hospital and Huoshenshan Hospital in Wuhan, China from January 12, 2020 to March 20, 2020, whose outcome during the hospitalization was known, were retrospectively reviewed. The categorical variables were compared using Pearson’s χ2-test or Fisher’s exact test, and continuous variables were analyzed using Student’s t-test or Mann Whitney U-test, as appropriate. Then, variables with a P-value of ≤0.1 were included in the log-binomial model, and merely these independent risk factors were used to establish the nomogram model. The discrimination of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC), and internally verified using the Bootstrap method. Results: A total of 262 patients (134 surviving and 128 non-surviving patients) were included in the analysis. Seven variables, which included age (relative risk [RR]: 0.905, 95% confidence interval [CI]: 0.868–0.944; P < 0.001), chronic heart disease (CHD, RR: 0.045, 95% CI: 0.0097–0.205; P < 0.001, the percentage of lymphocytes (Lym%, RR: 1.125, 95% CI: 1.041–1.216; P = 0.0029), platelets (RR: 1.008, 95% CI: 1.003–1.012; P = 0.001), C-reaction protein (RR: 0.982, 95% CI: 0.973–0.991; P < 0.001), lactate dehydrogenase (LDH, RR: 0.993, 95% CI: 0.990–0.997; P < 0.001) and D-dimer (RR: 0.734, 95% CI: 0.617–0.879; P < 0.001), were identified as the independent risk factors. The nomogram model based on these factors exhibited a good discrimination, with an AUC of 0.948 (95% CI: 0.923–0.973). (Continued on next page)
* Correspondence: [email protected]; [email protected] † Xiaojun Ma, Huifang Wang, Junwei Huang and Yan Geng contributed equally to this work. 10 Department of Critical Care Medicine, General Hospital of Southern Theater Command of PLA, Guangzhou 510010, Guangdong, China 2 Department of Critical Care Medicine, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou 510080, Guangdong, China Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third
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