Interoperable Models for Identifying Critically Ill Children at Risk of Neurologic Morbidity.

Journal: JAMA network open
PMID: 39903466

Abstract

IMPORTANCE: Decreasing mortality in the field of pediatric critical care medicine has shifted practicing clinicians' attention to preserving patients' neurodevelopmental potential as a main objective. Earlier identification of critically ill children at risk for incurring neurologic morbidity would facilitate heightened surveillance that could lead to timelier clinical detection, earlier interventions, and preserved neurodevelopmental trajectory.

Authors

  • Christopher M Horvat
    Division of Pediatric Critical Care Medicine, Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania.
  • Amie J Barda
    Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, 5607 Baum Boulevard, Pittsburgh, PA, 15206, USA.
  • Eddie Perez Claudio
    Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
  • Alicia K Au
    Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
  • Andrew Bauman
    Seattle Children's Hospital, Seattle, Washington.
  • Qingyang Li
    School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA.
  • Ruoting Li
    Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.
  • Neil Munjal
    Department of Pediatrics, University of Wisconsin, Madison.
  • Mark S Wainwright
    Seattle Children's Hospital, Seattle, Washington.
  • Tanupat Boonchalermvichien
    Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania.
  • Harry Hochheiser
    University of Pittsburgh, Pittsburgh, PA, USA.
  • Robert S B Clark
    Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania.

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