PREDICTIVE MODEL TO IDENTIFY TRAUMA PATIENTS WITH BLOOD-ALCOHOL CONCENTRATIONS GREATER-THAN-OR-EQUAL-TO-50 MG DL/

Objective: To develop a simple model for identification of trauma pati ents who are likely to have a blood alcohol concentration greater than or equal to 50 mg/dL (BAC+50). Methods: Demographic, clinical, and BA C data were collected from the clinical trauma registry and toxicology data base at a Level I trauma center, Logistic regression was used to analyze data from 11,206 patients to develop a predictive model, whic h was validated using a subsequent cohort of 3,523 patients. Results: In the model development cohort, alcohol was detected in the blood of 3,180 BAC-tested patients (28.7%), of whom 91.2% had a BAC+50 status. Preliminary analysis revealed associations between a BAC+50 status and sex, age, race, injury type (intentional vs, unintentional), and time of injury (night vs, day and weekend vs, weekday), A predictive model using four attributes (sex and injury type) identified patients at lo w, medium, and high risk for being BAC+50. The model was validated usi ng the second group of patients. Conclusions: Injured patients with a high probability of being alcohol positive can be identified using a s imple scoring system based on readily available demographic and clinic al information.