Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery.

Journal: Cardiovascular diabetology
PMID:

Abstract

BACKGROUND: The stress hyperglycemia ratio (SHR) was developed to reduce the effects of long-term chronic glycemic factors on stress hyperglycemia levels, which was associated with adverse clinical outcomes. This study aims to evaluate the relationship between the postoperative SHR index and all-cause mortality in patients undergoing cardiac surgery.

Authors

  • Yingjian Pei
    Department of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, A 167, Beilishi Road, Xicheng District, Beijing, 100037, China.
  • Yajun Ma
    Radiology Department, University of California San Diego, La Jolla 92093, CA, USA. Electronic address: yam013@ucsd.edu.
  • Ying Xiang
    College of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi'an 710021, Shaanxi, China.
  • Guitao Zhang
    Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province and School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen, 518107, China. quxm5@mail.sysu.edu.cn.
  • Yao Feng
    Traditional Chinese Medicine Department, the First Affiliated Hospital of Jiamusi University, Jiamusi 154000, Heilongjiang, China.
  • Wenbo Li
    Foshan Xianhu Laboratory of the Advanced Energy Science and Technology Guangdong Laboratory, Xianhu Hydrogen Valley, Foshan 528200, China.
  • Yinghua Zhou
    Department of Neurology, National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, A 167, Beilishi Road, Xicheng District, Beijing, 100037, China. yhzhou2008@sina.com.
  • Shujuan Li