Development and Validation of a Machine Learning Model to Predict Near-Term Risk of Iatrogenic Hypoglycemia in Hospitalized Patients.

Journal: JAMA network open
PMID: 33416883

Abstract

IMPORTANCE: Accurate clinical decision support tools are needed to identify patients at risk for iatrogenic hypoglycemia, a potentially serious adverse event, throughout hospitalization.

Authors

  • Nestoras N Mathioudakis
    Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Mohammed S Abusamaan
    Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Ahmed F Shakarchi
    Wilmer Eye Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Sam Sokolinsky
    Department of Quality Improvement and Clinical Analytics, Johns Hopkins Health System, Baltimore, Maryland.
  • Shamil Fayzullin
    Department of Quality Improvement and Clinical Analytics, Johns Hopkins Health System, Baltimore, Maryland.
  • John McGready
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
  • Mihail Zilbermint
    Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
  • Suchi Saria
    Department of Computer Science, Johns Hopkins University, Baltimore, MD.
  • Sherita Hill Golden
    Division of Endocrinology, Diabetes & Metabolism, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.

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