Latent class analysis for identification of sub-phenotypes predicting prognosis in hospitalized out-of-hospital cardiac arrest

Yuki Kishihara¹, Hideto Yasuda^1–4, Masahiro Kashiura¹, Shunsuke Amagasa⁵, Hiroyuki Tamura¹, Yutaro Shinzato¹, Takashi Moriya¹

1 Department of Emergency and Critical Care Medicine, Jichi Medical University Saitama Medical Center, Saitama, Japan
2 Department of Clinical Research Education and Training Unit, Keio University Hospital Clinical and Translational Research Center, Tokyo, Japan
3 School of Nursing, Midwifery and Social Work, UQ Centre for Clinical Research, The University of Queensland, Australia
4 School of Nursing and Midwifery; Alliance for Vascular Access Teaching and Research, Griffith University, Australia
5 Department of Emergency and Transport Medicine, National Center for Child Health and Development, Tokyo, Japan

DOI: 10.2478/jccm-2025-0016

Aim of the study: To determine which out-of-hospital cardiac arrest (OHCA) patients should receive advanced treatment is extremely challenging. The objective was to identify sub-phenotypes predicting the prognoses of adult OHCA patients by latent class analysis (LCA) using data up to just after admission.
Material and Methods: We conducted a retrospective observational study using multicentre OHCA registry from 95 Japanese hospitals including adult non-traumatic hospitalized OHCA. The primary outcome was 30-day favourable neurological outcome. Our LCA used clinically relevant variables up to just after admission and the optimal class number was determined from clinical importance and Bayesian information criterion. The associations between sub-phenotypes and outcomes were analysed using univariate logistic regression analysis with odds ratios (ORs) and 95% confidence intervals (CIs).
Results: Our LCA included 2,162 patients and identified four sub-phenotypes. The base excess on hospital arrival had the highest discriminative power. Thirty-day favourable neurological outcomes were observed in 526 patients (24.3%), including 284 (53.8%) in Group 1, 179 (21.2%) in Group 2, 26 (11.4%) in Group 3, and 37 (6.6%) in Group 4. Prehospital return of spontaneous circulation (ROSC) was achieved in 1,009 patients (46.7%), including 379 (81.8%) in Group 1, 340 (40.3%) in Group 2, 115 (50.4%) in Group 3, and 175 (31.1%) in Group 4. Univariate logistic regression analysis for primary outcome using Group 4 as reference revealed ORs (95% CI) of 16.5 (11.4–24.1) in Group 1, 3.83 (2.64–5.56) in Group 2, and 1.83 (1.08–3.10) in Group 3.
Conclusions: Our LCA classified OHCA into four sub-phenotypes showing significant differences for prognosis. In cases who achieved prehospital ROSC, it might be meaningful to continue advanced therapeutic interventions.