A machine learning model for mortality prediction in patients with severe fever with thrombocytopenia syndrome: a prospective, multicenter cohort study.

Journal: Emerging microbes & infections
Published Date: Jun 19, 2025

Abstract

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease that imposes a considerable medical burden. In this study, we enrolled 1,606 SFTS patients, developed and validated machine learning models for mortality prediction, and ultimately constructed a model consisting of six variables. The prediction model, UNION-SFTS, constructed using the multilayer perceptron (MLP) algorithm, achieved the best performance with an area under the curve (AUC) of 0.917, an accuracy of 0.905, and a precision of 0.795 on the internal validation set. Additionally, the model achieved an AUC of 0.883 on the prospective validation set and AUCs of 1.000, 0.927 and 0.905 on the three external validation sets, respectively. We developed a user-friendly web-based calculator for clinical use, available at http://175.178.66.58/english/. By utilizing the UNION-SFTS model, clinicians can promptly predict and monitor the disease severity and mortality risk of SFTS patients, enabling early intervention in severe cases and ultimately reduces patient mortality.

Authors

  • Yanan Liu
    College of Environmental Science and Engineering, Donghua University, 2999 North Renmin Road, Shanghai 201620, China.
  • Lei Fan
    Department of Chemistry, National University of Singapore, 3 Science Drive 3, Singapore, 117543, Singapore.
  • Wencai Wang
    School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
  • Hongxuan Song
    Department of Infectious Diseases, The Sixth People's Hospital of Qingdao City, Qingdao, People's Republic of China.
  • Zhenghua Zhang
    Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, Anhui, People's Republic of China.
  • Qian Liu
    State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China.
  • Zhongji Meng
    Department of Infectious Diseases, Hubei Provincial Clinical Research Center for Precise Diagnosis and Treatment of Liver Cancer, Taihe Hospital, Hubei University of Medicine, Hubei, People's Republic of China.
  • Shibo Li
    Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System, Shenzhen 518055, China. Electronic address: sb.li@siat.ac.cn.
  • Hua Wang
    Department of Orthopaedics, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Shijun Zhou
    Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, Anhui, People's Republic of China.
  • Wanjun Liu
    Shanghai Ocean University, Shanghai, 201306, China. 72500L10067@shsmu.edu.cn.
  • Guomei Xia
    Institute of Clinical Virology, Department of Infectious Diseases, The Second Affiliated Hospital of Anhui Medical University, Hefei, China.
  • Jianping Duan
    Department of Infectious Diseases, The Sixth People's Hospital of Qingdao City, Qingdao, People's Republic of China.
  • Chunxia Guo
    Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
  • Lu Wang
    Department of Laboratory, Akesu Center of Disease Control and Prevention, Akesu, China.
  • Ling Xu
    Department of Respiratory Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, No. 600, YiShan Road, Shanghai, 200233, China. quanlingxu@163.com.
  • Tong Wang
    School of Public Health, Shanxi Medical University, Taiyuan 030000, China; Key Laboratory of Coal Environmental Pathogenicity and Prevention (Shanxi Medical University), Ministry of Education, Taiyuan 030000, China.
  • Hanxin Li
    Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
  • Xinyue Zhang
    Department of Radiology, Changhai Hospital.
  • Tiandan Xiang
    Department of Infectious Diseases, The First Affiliated Hospital of Soochow University, Suzhou, People's Republic of China.
  • Di Liu
    Laboratory of Nutrition and Functional Food, College of Food Science and Engineering, Jilin University, Changchun, China.
  • Zujiang Yu
    Gene Hospital of Henan Province, Precision Medicine Center, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
  • Yuliang Liu
    State Key Laboratory Cultivation Base for Nonmetal Composites and Functional Materials, Southwest University of Science and Technology, Mianyang, 621010, People's Republic of China.
  • Junzhong Wang
    Department of Infectious Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
  • Xin Zheng
    Department of Clinical Laboratory, Longhua Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China. Electronic address: dearjanna@126.com.

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