LAUSR

BackgroundAccidental 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.MethodsData 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.ResultsAmong the 572 patients in the J-point registry, 532 were ultimately included and divided into the development cohort (N = 288, six hospitals, in-hospital mortality 22.0%) and the validation cohort (N = 244, six hospitals, in-hospital mortality 27.0%). The 5 “A” scoring system based on age, activities-of-daily-living status, near arrest, acidemia, and serum albumin level was developed based on the variables’ coefficients in the development cohort. In the validation cohort, the prediction performance was validated.ConclusionOur “5A” severity scoring system could accurately predict the risk of in-hospital mortality among patients with accidental hypothermia.