Exploring the prognostic impact of triglyceride-glucose index in critically ill patients with first-ever stroke: insights from traditional methods and machine learning-based mortality prediction.

Journal: Cardiovascular diabetology
PMID: 39695656

Abstract

BACKGROUND: The incidence and mortality of first-ever strokes have risen sharply, especially in the intensive care unit (ICU). Emerging surrogate for insulin resistance, triglyceride-glucose index (TyG), has been linked to stroke prognosis. We aims to explore the relationships between TyG with ICU all-cause mortality and other prognosis, and to develop machine learning (ML) models in predicting ICU all-cause mortality in the first-ever strokes.

Authors

  • Yang Chen
    Orthopedics Department of the First Affiliated Hospital of Tsinghua University, Beijing, China.
  • Zhenkun Yang
    School of Electrical and Electronic Engineering, Shanghai Institute of Technology, Shanghai, China.
  • Yang Liu
    Department of Computer Science, Hong Kong Baptist University, Hong Kong, China.
  • Yuanjie Li
    Tianjin Research Institute of Anesthesiology and Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin, China.
  • Ziyi Zhong
    Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK.
  • Garry McDowell
    Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart and Chest Hospital, Liverpool, UK.
  • Coleen Ditchfield
    Department of Medicine for Older People, Whiston Hospital, Mersey and West Lancashire Teaching Hospitals NHS Trust, Prescot, UK.
  • Taipu Guo
    Tianjin Research Institute of Anesthesiology and Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin, China.
  • Mingjuan Yang
    Department of Cardiology, Tianjin Medical University General Hospital, Heping District, Tianjin, People's Republic of China.
  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Bi Huang
    School of Big Data and Intelligent Engineering, Southwest Forestry University, Kunming, China.
  • Ying Gue
    Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, United Kingdom; The Department of Cardiovascular and Metabolic Medicine, University of Liverpool, United Kingdom.
  • Gregory Y H Lip
    Liverpool Centre for Cardiovascular Science, University of Liverpool, Liverpool John Moores University and Liverpool Heart & Chest Hospital, L69 3BX Liverpool, UK.

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