Hypothermia in Emergency Care: Longitudinal Demographic Trends and Predictors of Critical Outcomes in Hungary

Background Accidental hypothermia, defined as a core temperature below 35°C, can cause metabolic, respiratory, and circulatory disturbances; fatal arrhythmias; or cardiac arrest. Our objective was to analyze the profile of patients presenting at a Hungarian emergency department and to identify predictors of critical outcomes. Methods We conducted a retrospective cohort analysis from 2020–2024 at the Department of Emergency Medicine, Semmelweis University. Patients whose core temperature was less than 35°C were included, and their demographics and triage categories were documented. Hypothermia severity was assessed via the Swiss staging model and the Wilderness Medical Society classification. The primary outcome was a composite of admissions to the intensive care unit and mortality in the emergency department. We tested the ability of hypothermia-specific scales and triage categories, admission temperature, and their combined models to predict the primary outcome. Predictive accuracy was evaluated via receiver operating characteristic (ROC) analysis. The strength of the correlations was quantified via logistic regression. Results A total of 131 patients met the inclusion criteria. The median age was 67.5 years (IQR: 59.0–75.0). Eighty-eight patients (67.2%) were male. The median admission core temperature was 29.3°C (IQR: 26.1–31.4°C). The median length of stay was 13.7 hours (IQR: 9.5–18.9 hours). Severe hypothermia (< 30°C) was present in 47 patients (34.6%). Intensive care unit admission was required for 16 patients (12.2%), and 28 patients (21.4%) died during emergency care. Ambient temperature seasonally affected the incidence of hypothermia but had no influence on the probability of critical outcomes. The triage category outperformed hypothermia-specific stratification tools and was the strongest single predictor of critical outcomes (AUC = 0.683). The combination of triage category and admission core temperature had the highest predictive accuracy (AUC = 0.740, 95% CI: 0.650–0.831) for the primary outcome. Conclusions Accidental hypothermia is a serious and potentially lethal emergency despite milder winters associated with climate change. The admission core temperature improves the predictive performance of general triage systems for critical outcomes. To identify and manage high-risk hypothermic patients in environments with sudden temperature fluctuations, comprehensive, integrated risk assessment methods are essential.