• Allyson C Cook, Bellal Joseph, Kenji Inaba, Paul A Nakonezny, Brandon R Bruns, Jeff D Kerby, Karen J Brasel, Steve E Wolf, Joe Cuschieri, M Elizabeth Paulk, Ramona L Rhodes, Scott C Brakenridge, and Herb A Phelan.
• From the Department of Surgery (A.C.C.), Division of Biostatistics (P.A.N.), Department of Clinical Sciences, Division of Burns/Trauma/Critical Care (S.E.W., H.A.P.), Palliative Medicine (M.E.P.), Department of Internal Medicine, and Palliative Medicine (R.L.R.), Division of Geriatrics, UT Southwestern, Dallas, Texas; Division of Trauma, Critical Care, Burn, and Emergency Surgery (B.J.), University of Arizona, Tucson, Arizona; Division of Acute Care Surgery and Surgical Critical Care (K.I.), USC, Los Angeles, California; R Adams Cowley Shock Trauma Center (B.R.B.), University of Maryland; Baltimore, Maryland; Division of Trauma, Burns, and Surgical Critical Care (J.D.K.), UAB Medical Center, Birmingham, Alabama; Division of Trauma, Critical Care, and Acute Care Surgery (K.J.B.), Oregon Health Sciences University, Portland, Oregon; Division of Trauma, Burn, and Critical Care Surgery (J.C.), University of Washington, Seattle, Washington; and Division of Acute Care Surgery (S.C.B.), University of Florida, Gainesville, Florida.
• J Trauma Acute Care Surg. 2016 Feb 1; 80 (2): 204-9.

BackgroundA prognostic tool for geriatric mortality after injury called the Geriatric Trauma Outcome Score (GTOS), where GTOS = [age] + [ISS × 2.5] + [22 if transfused any PRBCs by 24 hours after admission], was previously developed based on 13 years of data from geriatric trauma patients admitted to Parkland Hospital. We sought to validate this model.MethodsFour Level I centers identified subjects who are 65 years or older for the period of the original study. The GTOS model was first specified using the formula [GTOS = age + (ISS × 2.5) + 22 (if given PRBC by 24 hours)] developed from the Parkland sample and then used as the sole predictor in a logistic mixed model estimating probability of mortality in the validation sample, accounting for site as a random effect. We estimated the misclassification (error) rate, Brier score, Tjur R, and the area under the curve in evaluating the predictive performance of the GTOS model.ResultsThe original Parkland sample (n = 3,841) had a mean (SD) age of 76.6 (8.1) years, mean (SD) ISS of 12.4 (9.9), mortality of 10.8%, and 11.9% receiving PRBCs at 24 hours. The validation sample (n = 18,282) had a mean (SD) age of 77.0 (8.1) years, mean (SD) ISS of 12.3 (10.6), mortality of 11.0%, and 14.1% receiving PRBCs at 24 hours. Fitting the GTOS model to the validation sample revealed that the parameter estimates from the validation sample were similar to those of fitting it to the Parkland sample with highly overlapping 95% confidence limits. The misclassification (error) rate for the GTOS logistic model applied to the validation sample was 9.97%, similar to that of the Parkland sample (9.79%). Brier score, Tjur R, and the area under the curve for the GTOS logistic model when applied to the validation sample were 0.07, 0.25, and 0.86, respectively, compared with 0.08, 0.20, and 0.82, respectively, for the Parkland sample.ConclusionWith the use of the data available at 24 hours after injury, the GTOS accurately predicts in-hospital mortality for the injured elderly.Level Of EvidencePrognostic study, level III.

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