The development and validation of a "5A" severity scale for predicting in-hospital mortality after accidental hypothermia from J-point registry data

Abstract

Background: Accidental hypothermia is a serious condition that requires immediate and accurate assessment to determine severity and treatment. Currently, accidental hypothermia is evaluated using the Swiss grading system which uses core body temperature and clinical findings; however, research has shown that core body temperature is not associated with in-hospital mortality in urban settings. Therefore, we developed and validated a severity scale for predicting in-hospital mortality among urban Japanese patients with accidental hypothermia. Methods: Data for this multi-center retrospective cohort study were obtained from the J-point registry. We included patients with accidental hypothermia who were admitted to an emergency department. The total cohort was divided into a development cohort and validation cohort, based on the location of each institution. We developed a logistic regression model for predicting in-hospital mortality using the development cohort and assessed its internal validity using bootstrapping. The model was then subjected to external validation using the validation cohorts. Conclusion: Our “5A” severity scoring system could accurately predict the risk of in-hospital mortality among patients with accidental hypothermia.