Characterising risk of in-hospital mortality following cardiac arrest using machine learning: A retrospective international registry study.

Journal: PLoS medicine
PMID: 30500816

Abstract

BACKGROUND: Resuscitated cardiac arrest is associated with high mortality; however, the ability to estimate risk of adverse outcomes using existing illness severity scores is limited. Using in-hospital data available within the first 24 hours of admission, we aimed to develop more accurate models of risk prediction using both logistic regression (LR) and machine learning (ML) techniques, with a combination of demographic, physiologic, and biochemical information.

Authors

  • Shane Nanayakkara
    Department of Cardiology, Alfred Hospital, Melbourne, Victoria, Australia.
  • Sam Fogarty
    Institute for Integrated and Intelligent Systems, Griffith University, Gold Coast, Queensland, Australia.
  • Michael Tremeer
    IntelliHQ, Gold Coast, Queensland, Australia.
  • Kelvin Ross
    Institute for Integrated and Intelligent Systems, Griffith University, Gold Coast, Queensland, Australia.
  • Brent Richards
    Department of Intensive Care, Gold Coast University Hospital, Gold Coast, Queensland, Australia.
  • Christoph Bergmeir
    Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia.
  • Sheng Xu
    School of Physics and Information Engineering, Jiangsu Second Normal University, Nanjing, 211200, China.
  • Dion Stub
    Department of Cardiology, Alfred Hospital, Melbourne, Victoria, Australia.
  • Karen Smith
    Centre for Research and Evaluation, Ambulance Victoria, Melbourne, Victoria, Australia.
  • Mark Tacey
    School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • Danny Liew
    School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • David Pilcher
    School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
  • David M Kaye
    Department of Cardiology, Alfred Hospital, Melbourne, Victoria, Australia.

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