Prospective, multicenter validation of the deep learning-based cardiac arrest risk management system for predicting in-hospital cardiac arrest or unplanned intensive care unit transfer in patients admitted to general wards.

Journal: Critical care (London, England)
Published Date: Sep 5, 2023

Abstract

BACKGROUND: Retrospective studies have demonstrated that the deep learning-based cardiac arrest risk management system (DeepCARS™) is superior to the conventional methods in predicting in-hospital cardiac arrest (IHCA). This prospective study aimed to investigate the predictive accuracy of the DeepCARS™ for IHCA or unplanned intensive care unit transfer (UIT) among general ward patients, compared with that of conventional methods in real-world practice.

Authors

  • Kyung-Jae Cho
    VUNO, Seoul, South Korea.
  • Jung Soo Kim
    Division of Critical Care Medicine, Department of Hospital Medicine, Inha College of Medicine, Incheon, Republic of Korea.
  • Dong Hyun Lee
  • Sang-Min Lee
    Department of Orthopedics, Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Korea.
  • Myung Jin Song
    Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Sung Yoon Lim
    Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Young-Jae Cho
    Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea.
  • You Hwan Jo
    Department of Emergency Medicine, Seoul National University Bundang Hospital, Seongnam, Republic of Korea.
  • Yunseob Shin
    VUNO, Seoul, Republic of Korea.
  • Yeon Joo Lee
    From the Department of Radiology, Seoul National University College of Medicine, Seoul National University Hospital, 101 Daehak-ro, Chongno-gu, Seoul 03080, Korea (S.L., J.M.G., S.H.Y.); Division of Pulmonary and Critical Medicine, Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea (J.J.Y., N.K.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea (Y.J.L.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Seoul Metropolitan Government-Seoul National University Boramae Medical Center, Seoul, Korea (J.K.L.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, National Medical Center, Seoul, Korea (J.Y.L.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Incheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Incheon, Korea (J.S.K.); Division of Pulmonary and Critical Care Medicine, Department of Internal Medicine, Severance Hospital, Yonsei University College of Medicine, Seoul, Korea (Y.A.K.); Department of Internal Medicine, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Korea (D.J.); Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Korea (M.J.J.); Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea (J.M.G.); and Department of Radiology, UMass Memorial Medical Center, Worcester, Mass (S.H.Y.).

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