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The primary aim of this prospective study is to develop and validate a new prognostic model for predicting the risk of mortality in Emergency Department (ED) patients. The study involved 1765 patients in the development cohort and 1728 in the validation cohort. The main outcome was mortality up to 30 days after admission. Potential risk factors included clinical characteristics, vital signs, and routine haematological and biochemistry tests. The Bayesian Model Averaging method within the Cox’s regression model was used to identify independent risk factors for mortality. In the development cohort, the incidence of 30-day mortality was 9.8%, and the following factors were associated with a greater risk of mortality: male gender, increased respiratory rate and serum urea, decreased peripheral oxygen saturation and serum albumin, lower Glasgow Coma Score, and admission to intensive care unit. The area under the receiver operating characteristic curve for the model with the listed factors was 0.871 (95% CI, 0.844–0.898) in the development cohort and 0.783 (95% CI, 0.743–0.823) in the validation cohort. Calibration analysis found a close agreement between predicted and observed mortality risk. We conclude that the risk of mortality among ED patients could be accurately predicted by using common clinical signs and biochemical tests.

Development and validation of a prognostic model for predicting 30-day mortality risk in medical patients in emergency department (ED)