Risk of alcohol withdrawal syndrome in hospitalized trauma patients: A national data analysis

Background: Alcohol withdrawal syndrome (AWS) is an uncommon occurrence in trauma victims. However, the syndrome can cause a prolonged hospital stay. Therefore, the purpose of this study is to develop and validate the risk factors of AWS so that interventions can be applied to high-risk patients. Methods: All adult trauma patients with an injury severity score of ≥1 and greater than one hospital day were included in the study. The Trauma Quality Improvement Program (TQIP) database from 2013-2016 was accessed for the study. Patient demography, injury and comorbidities were compared between the patients who developed AWS and who did not develop AWS. The data were split into 2 datasets: training and testing. Eighty percent (80%) of the data was randomly selected for the training dataset to develop the risk factors. The remaining 20% of the data were used for validation of the risk factors using multivariable analysis. The receiving operating characteristics (ROC) curve and area under the curve (AUC) were generated for model fitness. All P values <0.01 were considered statistically significant. Results: A total of 497,819 patients qualified for the study. Only 6,894 (1.38%) patients developed AWS during their hospitalization. The median age of the patients, who developed AWS, was 54 years. The patients were predominantly male (84% vs. 63.1%) and Caucasian (80.3% vs. 76.1%). The multivariable analysis showed an age range of 45 years to 74 years old, male gender, Caucasian race, a history of chronic alcoholic abuse, hypertension and cirrhosis increased the risk of AWS. The AUC of the model of 0.910, 95% CI; [0.901, 0.918] showed an excellent model for predicting the risk of the development of AWS. Conclusion: Approximately 1.4% of the trauma victims developed AWS. Certain patient demographic and comorbidity characteristics, and head injury have a higher risk of developing of AWS.