A Novel Risk Score to Predict Post-Trauma Mortality in Nonagenarians.

Background: Nonagenarians represent a rapidly growing age group who often have functional limitations and multiple comorbidities, predisposing them to trauma. Aims: The purpose of this study was to identify patient characteristics, hospital complications, and comorbidities that predict in-hospital mortality in the nonagenarian population following trauma. We also sought to create a scoring system using these variables. Settings and Design: This study was a retrospective chart review. Methods: We reviewed the medical records of 548 nonagenarian trauma patients admitted to two Level I trauma centers from 2006 to 2015. Statistical analysis was performed using logistic regression and a machine learning model, which calculated significant variables and computed a scoring system. Results: The in-hospital mortality rate was 7.1% (n = 39). Significant predictors of mortality were cardiac comorbidity, neuro-concussion, New Injury Severity Score (ISS) 16+, striking an object, ISS 25-75, and pulmonary and cardiac complications. Significant variables were assigned a numeric value. A score of 5+ carried a 41.1% mortality risk, 79% sensitivity, and 91% specificity. A score of 10+ had an associated 81.8% mortality risk with 31% specificity and 99% sensitivity. Conclusions: Our findings identified reliable predictors of mortality in nonagenarian population posttrauma. The scoring system performs with good specificity and sensitivity and incrementally correlates with mortality risk.