Development and validation of inpatient mortality prediction models for patients with hyperglycemic crisis using machine learning approaches.

Journal: BMC endocrine disorders
PMID:

Abstract

BACKGROUND: Hyperglycemic crisis is one of the most common and severe complications of diabetes mellitus, associated with a high motarlity rate. Emergency admissions due to hyperglycemic crisis remain prevalent and challenging. This study aimed to develop and validate predictive models for in-hospital mortality risk among patients with hyperglycemic crisis admitted to the emergency department using various machine learning (ML) methods.

Authors

  • Rui He
    Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China. herui@emails.bjut.edu.cn.
  • Kebiao Zhang
    Department of Emergency, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, Chongqing, 400016, China. zhangkebiao0537@163.com.
  • Hong Li
    Department of Public Health Sciences, Medical College of South Carolina, Charleston, SC.
  • Manping Gu
    Department of Nursing, The First Affiliated Hospital of Chongqing Medical University, Yuzhong District, Chongqing, 400016, China. gumanping@163.com.