Abstract

To explore the application value of three emergency and critical illness scoring systems in the prognosis assessment of emergency medical patients is the main objective. The 200 emergency medical cases received in the emergency department of our hospital were selected as the research objects and the 28 d survival of the patients was used as the observation end point. The patients were divided into the survival group 156 cases and the death group 44 cases; statistical analysis of the rapid emergency treatment within 24 h of admission to the two groups; differences in rapid emergency medicine score, modified early warning score, acute physiology and chronic health evaluation II score, statistical analysis of the general physiological indicators and general data of the two groups of patients within 24 h of admission; the work of subjects, receiver operating characteristic curve was used to analyze the differences between the three scoring systems in predicting the prognosis of emergency medical patients and the logistic multivariate regression model was used to analyze the relevant factors affecting the prognosis of patients. The rapid emergency medicine score, modified early warning score and acute physiology and chronic health evaluation II score of the death group were higher than those of the survival group and the difference was statistically significant (p<0.05); the rapid emergency medicine score of the death group predicted the 28 d death of emergency medical patients and the area under the receiver operating characteristic curve was 0.722. The area under the curve value under the receiver operating characteristic curve for modified early warning score predicting 28 d death of emergency medical patients was 0.689 and the area under the curve value under receiver operating characteristic curve for predicting 28 d death of emergency medical patients by acute physiology and chronic health evaluation II score was 0.842; the 28 d prognostic outcome of patients was used as the dependent variable to establish a logistic regression model. Factor analysis showed that the older the patient, circulatory system disease, neurological disease, intensive care unit enrollment, basic disease types >2, decreased saturation of peripheral oxygen and unresponsiveness were independent risk factors for 28 d death in patients admitted to the emergency medical department (p<0.05). For patients admitted to the emergency medical department, rapid emergency medicine score, modified early warning score and acute physiology and chronic health evaluation II score have certain clinical value in predicting the prognosis of patients at 28 d and the value of acute physiology and chronic health evaluation II score is relatively high. There are many factors affecting the prognosis of patients and they affect the adverse effects of patients in emergency medical department and there are many factors for the prognostic outcome.