Internal and External Validation of a Machine Learning Risk Score for Acute Kidney Injury.

Journal: JAMA network open
Published Date: Aug 3, 2020

Abstract

IMPORTANCE: Acute kidney injury (AKI) is associated with increased morbidity and mortality in hospitalized patients. Current methods to identify patients at high risk of AKI are limited, and few prediction models have been externally validated.

Authors

  • Matthew M Churpek
    Department of Medicine, University of Wisconsin-Madison, Madison, WI, United States.
  • Kyle A Carey
    Department of Medicine, University of Chicago, Chicago IL, United States.
  • Dana P Edelson
  • Tripti Singh
    Department of Medicine, University of Wisconsin, Madison.
  • Brad C Astor
    Department of Medicine, University of Wisconsin, Madison.
  • Emily R Gilbert
    Department of Medicine, Loyola University Medical Center, Maywood, Illinois.
  • Christopher Winslow
  • Nirav Shah
  • Majid Afshar
    Loyola University Chicago, Chicago, IL.
  • Jay L Koyner
    Section of Nephrology, Department of Medicine, University of Chicago, Chicago, Illinois.

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