title: Estimating Geriatric Mortality after Injury Using Age, Injury Severity, and Performance of a Transfusion: The Geriatric Trauma Outcome Score.
abstract: BACKGROUND
  A tool to determine the probability of mortality for severely injured geriatric patients is needed.
  
  
  OBJECTIVE
  We sought to create an easily calculated geriatric trauma prognostic score based on parameters available at the bedside to aid in mortality probability determination.
  
  
  METHODS
  All patients ≥ 65 years of age were identified from our Level I trauma center's registry between January 1, 2000 and December 31, 2013. Measurements included age, Injury Severity score (ISS), units of packed red blood cells (PRBCs) transfused in the first 24 hours, and patients' mortality status at the end of their index hospitalization. As a first step, a logistic regression model with maximum likelihood estimation and robust standard errors was used to estimate the odds of mortality from age, ISS, and PRBCs after dichotomizing PRBCs as yes/no. We then constructed a Geriatric Trauma Outcome (GTO) score that became the sole predictor in the re-specified logistic regression model.
  
  
  RESULTS
  The sample (n = 3841) mean age was 76.5 ± 8.1 years and the mean ISS was 12.4 ± 9.8. In-hospital mortality was 10.8%, and 11.9% received a transfusion by 24 hours. Based on the logistic regression model, the equation with the highest discriminatory ability to estimate probability of mortality was GTO Score = age + (2.5 × ISS) + 22 (if given PRBCs). The area under the receiver operating characteristic curve (AUC) for this model was 0.82. Selected GTO scores and their related probability of dying were: 205 = 75%, 233 = 90%, 252 = 95%, 310 = 99%. The range of GTO scores was 67.5 (survivor) to 275.1 (died).
  
  
  CONCLUSIONS
  The GTO model accurately estimates the probability of dying, and can be calculated at bedside by those possessing a working knowledge of ISS calculation.
authors.affiliation: 1 Department of General Surgery, UT Southwestern Medical Center, Parkland Memorial Hospital , Dallas, Texas.
authors.forename: Frank Z
authors.initials: FZ
authors.lastname: Zhao
authors.affiliation: 2 Division of Burns/Trauma/Critical Care, Department of Surgery, UT Southwestern Medical Center, Parkland Memorial Hospital , Dallas, Texas.
authors.forename: Steven E
authors.initials: SE
authors.lastname: Wolf
authors.affiliation: 3 Division of Biostatistics, Department of Clinical Sciences, UT Southwestern Medical Center , Dallas, Texas.
authors.forename: Paul A
authors.initials: PA
authors.lastname: Nakonezny
authors.affiliation: 3 Division of Biostatistics, Department of Clinical Sciences, UT Southwestern Medical Center , Dallas, Texas.
authors.forename: Abu
authors.initials: A
authors.lastname: Minhajuddin
authors.affiliation: 4 Division of Geriatrics and Palliative Care, Department of Internal Medicine, UT Southwestern Medical Center, Parkland Memorial Hospital , Dallas, Texas.
authors.forename: Ramona L
authors.initials: RL
authors.lastname: Rhodes
authors.affiliation: 5 Division of Palliative Care, Department of Internal Medicine, UT Southwestern Medical Center, Parkland Memorial Hospital , Dallas, Texas.
authors.forename: M Elizabeth
authors.initials: ME
authors.lastname: Paulk
authors.affiliation: 2 Division of Burns/Trauma/Critical Care, Department of Surgery, UT Southwestern Medical Center, Parkland Memorial Hospital , Dallas, Texas.
authors.forename: Herb A
authors.initials: HA
authors.lastname: Phelan
mesh_terms: D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D017707:Erythrocyte Transfusion / Q000706:statistics & numerical data*; D005260:Female; D015577:Geriatric Assessment; D017052:Hospital Mortality; D006801:Humans; D015601:Injury Severity Score; D008297:Male; D017063:Outcome Assessment, Health Care; D011336:Probability; D011379:Prognosis; D012042:Registries; D014947:Wounds and Injuries / Q000401:mortality* / Q000628:therapy