Prediction of Fatal Outcomes in Patients With Severe Burns With the Use of Logistic Regression Methods

Abstract

Objectives: Our goal was to create a new model to predict mortality in patients with severe burns using logistic regression. Materials and Methods: We analyzed the scientific literature and conducted a retrospective study of 330 patients over 18 years old with shock-related burn injury who were treated in the Department of Anesthesiology and Resuscitation under the Department of Thermal Injuries of the Saint-Petersburg I. I. Dzhanelidze Research Institute of Emergency Medicine from 2013 to 2019. Results: In the process of studying the burn cases, 69 factors were identified, reflecting the clinical picture of patients with severe burns and accounting for infusion therapy administration. During construction of the logistic regression, 18 indicators were used that had statistically significant differences (P < .05) and in the aggregate made it possible to create a new prediction model. We found the resulting model to be highly efficient, predicting death and recovery with an accuracy of 87% and 93%, respectively.Conclusions: The use of a logistic regression method made it possible to create a new formula for predicting mortality in patients with severe burns, taking into account the main factors in the pathogenesis of severe burn injury upon admission and the effectiveness of infusion therapy in the first 3 days of hospitalization. This technique, based on the analysis of 330 patients with severe burns, showed high accuracy, with the ability to be used in everyday practice.