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\begin{document}

\title{Establishment of a diagnostic model to distinguish Coronavirus Disease
2019 from influenza A based on laboratory findings}



\author[1]{Dongyang Xing}%
\author[1]{Suyan Tian}%
\author[1]{Yukun Chen}%
\author[2]{Jinmei  Wang}%
\author[3]{Xuejuan  Sun}%
\author[4]{Shanji Li}%
\author[1]{Jiancheng Xu}%
\affil[1]{Jilin University First Hospital}%
\affil[2]{Siping Infectious Disease Hospital}%
\affil[3]{Changchun City Infectious Disease Hospital}%
\affil[4]{Jilin Province Infectious Disease Hospital }%


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  \date{June 07, 2024}


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\begin{abstract}
Background: Coronavirus disease 2019 (COVID-19) and Influenza A are
common disease caused by viral infection. The clinical symptoms and
transmission routes of the two diseases are similar. This study
established a model of laboratory findings to distinguish COVID-19 from
influenza A perfectly. Methods: In this study, 56 COVID-19 patients and
54 influenza A patients were included. Laboratory findings,
epidemiological characteristics and demographic data were obtained from
electronic medical record databases. Elastic network models, followed by
a stepwise logistic regression model were implemented to identify
indicators capable of discriminating COVID-19 and influenza A. Results:
A monogram is diagramed to show the resulting discriminative model. The
majority of hematological and biochemical parameters in COVID-19
patients were significantly different from those in influenza A
patients. In the final model, albumin/globulin, total bilirubin and
erythrocyte specific volume were selected as predictors. This model has
been demonstrated to have a satisfactory predictive performance to
discriminate between COVID-19 and influenza A (AUC=0.844) using an
external validation set. Conclusion: The establishment of a diagnostic
model on laboratory findings is of great significance for the
identification of COVID-19 and influenza A.%
\end{abstract}%



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