Latent class analysis for identification of sub-phenotypes predicting prognosis in hospitalized out-of-hospital cardiac arrest
Authors
Yuki Kishihara
Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
Hideto Yasuda
Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
School of Nursing and Midwifery, Alliance for Vascular Access Teaching and Research, Griffith University, Australia
School of Nursing, Midwifery and Social Work, UQ Centre for Clinical Research, The University of Queensland, Australia
Department of Clinical Research Education and Training Unit, Keio University Hospital Clinical and Translational Research Center, Tokyo, Japan
Masahiro Kashiura
Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
Shunsuke Amagasa
Department of Emergency and Transport Medicine, National Center for Child Health and Development, Tokyo, Japan
Hiroyuki Tamura
Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
Yutaro Shinzato
Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
Takashi Moriya
Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
Language: English
Page range: 183 - 191
Submitted on: Oct 23, 2024
Accepted on: Mar 8, 2025
Published on: Apr 30, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
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© 2025 Yuki Kishihara, Hideto Yasuda, Masahiro Kashiura, Shunsuke Amagasa, Hiroyuki Tamura, Yutaro Shinzato, Takashi Moriya, published by University of Medicine, Pharmacy, Science and Technology of Targu Mures
This work is licensed under the Creative Commons Attribution 4.0 License.