One-year and three-year mortality prediction in adult major blunt trauma survivors: A National Retrospective Cohort Analysis

Abstract

Background: Survivors of trauma are at increased risk of dying after discharge. Studies have found that age, head injury, injury severity, falls and co-morbidities predict long-term mortality. The objective of our study was to build a nomogram predictor of 1-year and 3-year mortality for major blunt trauma adult survivors of the index hospitalization. Methods: Using data from the Singapore National Trauma Registry, 2011-2013, we analyzed adults aged 18 and over, admitted after blunt injury, with an injury severity score (ISS) of 12 or more, who survived the index hospitalization, linked to death registry data. The study population was randomly divided 60/40 into separate construction and validation datasets, with the model built in the construction dataset, then tested in the validation dataset. Multivariable logistic regression was used to analyze 1-year and 3-year mortality. Results: Of the 3414 blunt trauma survivors, 247 (7.2%) died within 1 year, and 551 (16.1%) died within 3 years of injury. Age (OR 1.06, 95% CI 1.05-1.07, p < 0.001), male gender (OR 1.53, 95% CI 1.12-2.10, p < 0.01), low fall from 0.5 m or less (OR 3.48, 95% CI 2.06-5.87, p < 0.001), Charlson comorbidity index of 2 or more (OR 2.26, 95% CI 1.38-3.70, p < 0.01), diabetes (OR 1.31, 95% CI 1.68-2.52, p = 0.04), cancer (OR 1.76, 95% CI 0.94-3.32, p = 0.08), head and neck AIS 3 or more (OR 1.79, 95% CI 1.13-2.84, p = 0.01), length of hospitalization of 30 days or more (OR 1.99, 95% CI 1.02-3.86, p = 0.04) were predictors of 1-year mortality. This model had a c-statistic of 0.85. Similar factors were found significant for the model predictor of 3-year mortality, which had a c-statistic of 0.83. Both models were validated on the second dataset, with an overall accuracy of 0.94 and 0.84 for 1-year and 3-year mortality respectively. Conclusions: Adult survivors of major blunt trauma can be risk-stratified at discharge for long-term support. © 2018 The Author(s).