Prediction of Sepsis in COVID-19 Using Laboratory Indicators.

Journal: Frontiers in cellular and infection microbiology
Published Date: Mar 2, 2021

Abstract

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a global public health concern. Many inpatients with COVID-19 have shown clinical symptoms related to sepsis, which will aggravate the deterioration of patients' condition. We aim to diagnose Viral Sepsis Caused by SARS-CoV-2 by analyzing laboratory test data of patients with COVID-19 and establish an early predictive model for sepsis risk among patients with COVID-19.

Authors

  • Guoxing Tang
    Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Ying Luo
    School of Statistics, Beijing Normal University, Beijing, China.
  • Feng Lu
    National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
  • Wei Li
    Department of Nephrology, The Second Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.
  • Xiongcheng Liu
    National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
  • Yucen Nan
    The Australia-China Joint Research Centre for Energy Informatics and Demand Response Technologies, Centre for Distributed and High Performance Computing, School of Computer Science, The University of Sydney, Sydney, NSW, Australia.
  • Yufei Ren
    Department of Computer Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
  • Xiaofei Liao
    National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
  • Song Wu
    National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
  • Hai Jin
    National Engineering Research Center for Big Data Technology and System, Services Computing Technology and System Lab, Cluster and Grid Computing Lab, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
  • Albert Y Zomaya
    The Australia-China Joint Research Centre for Energy Informatics and Demand Response Technologies, Centre for Distributed and High Performance Computing, School of Computer Science, The University of Sydney, Sydney, NSW, Australia.
  • Ziyong Sun
    Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.

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