Prediction of neurologic outcome after out-of-hospital cardiac arrest: An interpretable approach with machine learning.

Journal: Resuscitation
PMID: 39142467

Abstract

UNLABELLED: Out-of-hospital cardiac arrest (OHCA) is a critical condition with low survival rates. In patients with a return of spontaneous circulation, brain injury is a leading cause of death. In this study, we propose an interpretable machine learning approach for predicting neurologic outcome after OHCA, using information available at the time of hospital admission.

Authors

  • Araz Rawshani
    University of Gothenburg, Institute of Medicine, Sahlgrenska Academy, Gröna Stråket 4, 43146, Gothenburg, Sweden.
  • Fredrik Hessulf
    Department of Anesthesiology and Intensive Care Medicine, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • John Deminger
    Department of Medicine and Emergency Care, Sahlgrenska University Hospital, Göteborgsvägen 33, 431 30 Mölndal, Sweden.
  • Pedram Sultanian
    Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
  • Vibha Gupta
    Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden.
  • Peter Lundgren
    Department of Molecular and Clinical Medicine, Institute of Medicine, University of Gothenburg, Wallenberg Laboratory, Blå stråket 5, Sahlgrenska University Hospital, 413 45 Gothenburg, Sweden; Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden.
  • Mohammed Mohammed
    Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden.
  • Monér Abu Alchay
    Department of Cardiology, Sahlgrenska University Hospital, Blå stråket 5, 413 45 Gothenburg, Sweden.
  • Tobias Siöland
    Department of Anesthesiology and Intensive Care Medicine, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
  • Emilia Gryska
    MedTech West at Sahlgrenska University Hospital, University of Gothenburg, Gothenburg, Sweden emilia.gryska@gu.se.
  • Adam Piasecki
    Department of Anesthesiology and Intensive Care, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Blå stråket 5, 413 45 Gothenburg, Sweden; Department of Anesthesiology and Intensive Care, Sahlgrenska University Hospital, Göteborgsvägen 31, 431 30 Mölndal, Sweden. Electronic address: adam.piasecki@gu.se.

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