MULTIVARIATE MODELS FOR PREDICTING SURVIVAL OF PATIENTS WITH TRAUMA FROM LOW FALLS - THE IMPACT OF GENDER AND PREEXISTING CONDITIONS

Objective: To determine if pre-existing conditions significantly impro ve the ability of current (TRISS and ASCOT) methods for predicting sur vival of patients with trauma from low falls. Design: Retrospective an alysis using logistic regression models to identify significant indepe ndent predictors of survival. Setting: Eight hospitals affiliated with New York Medical College. Patients: A total of 1906 patients with tra uma from low falls who were admitted to the eight hospitals between Ju ly 1987 and June 1989. Main Results: Gender and several pre-existing c onditions significantly improved the ability of age and the physiologi c and anatomic variables contained in the TRISS and ASCOT methodologie s to predict survival for trauma patients suffering from low falls, wi th males experiencing a lower probability of survival. Odds of surviva l for patients with these pre-existing conditions ranged from 0.18 to 0.59 times the odds of survival for similar patients without the pre-e xisting conditions when the TRISS variables were used, and from 0.23 t o 0.56 times the odds for similar patients when ASCOT variables were u sed. Furthermore, some substantial differences were found when hospita l performance was assessed with and without the benefit of preexisting conditions. Conclusions: Pre-existing conditions and male gender are significantly related to survival of patients with trauma from low fal ls, and should be included along with age and the various physiologic and anatomic measures currently being used to predict survival for tho se patients.