Enhanced Mortality Risk Prediction in Critically Ill COVID-19 Patients Using Stress Hyperglycemia Ratio and Machine Learning: A Multicenter Retrospective Analysis - Top-Institutions - MDSpire

Enhanced Mortality Risk Prediction in Critically Ill COVID-19 Patients Using Stress Hyperglycemia Ratio and Machine Learning: A Multicenter Retrospective Analysis

  • By

  • Jiaxing Du

  • Keze Ma

  • Zhiwei Ye

  • Juanli Song

  • Sujun Chen

  • Jie Yu

  • Bing Liu

  • Zixuan Jiang

  • Fen Zhang

  • January 16, 2026

  • 0 min

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Top Institutions in Pulmonary

Brief introduction explaining scope and methodology.

  • #1

    Johns Hopkins University
    Johns Hopkins University

    Baltimore, MD

    Key Differentiators

    • Critical Care Medicine
    • Endocrinology
    • Infectious Diseases
    • Biomedical Informatics

  • #2

    Massachusetts General Hospital / Harvard Medical School
    Massachusetts General Hospital / Harvard Medical School

    Boston, MA

    Key Differentiators

    • Critical Care Medicine
    • Endocrinology
    • Data Science

  • #3

    University of California, San Francisco (UCSF)
    University of California, San Francisco (UCSF)

    San Francisco, CA

    Key Differentiators

    • Critical Care Medicine
    • Endocrinology
    • Biomedical Data Science

  • #4

    Cleveland Clinic
    Cleveland Clinic

    Cleveland, OH

    Key Differentiators

    • Critical Care Medicine
    • Endocrinology
    • Clinical Research

  • #5

    University of Pennsylvania (Perelman School of Medicine)
    University of Pennsylvania (Perelman School of Medicine)

    Philadelphia, PA

    Key Differentiators

    • Critical Care Medicine
    • Endocrinology
    • Biomedical Informatics

Original Source(s)

Enhanced Mortality Risk Prediction in Critically Ill COVID-19 Patients Using Stress Hyperglycemia Ratio and Machine Learning: A Multicenter Retrospective Analysis

  • by Jiaxing Du, Keze Ma, Zhiwei Ye, Juanli Song, Sujun Chen, Jie Yu, Bing Liu, Zixuan Jiang, Fen Zhang

  • January 16, 2026

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