Allyson C Cook1, Bellal Joseph2, M Jane Mohler3, Kenji Inaba4, Brandon R Bruns5, Paul A Nakonezny6, Jeff D Kerby7, Karen J Brasel8, Steven E Wolf1, Joseph Cuschieri9, M Elizabeth Paulk10, Ramona L Rhodes10, Scott C Brakenridge11, A Peter Ekeh12, Herb A Phelan1. 1. UT Southwestern Department of Surgery, Division of Burns/Trauma/Critical Care, Parkland Memorial Hospital, Dallas, Texas. 2. Critical Care, Burn, and Emergency Surgery, University of Arizona Division of Trauma, Tucson, Arizona. 3. General Medicine, and Palliative Care, University of Arizona Section of Geriatrics, Tucson, Arizona. 4. USC Division of Acute Care Surgery and Surgical Critical Care, Los Angeles, California. 5. R Adams Cowley Shock Trauma Center at the University of Maryland, Baltimore, Maryland. 6. Division of Biostatistics, UT Southwestern Department of Clinical Sciences, Dallas, Texas. 7. Division of Trauma, Burns, and Surgical Critical Care, UAB Medical Center, Birmingham, Alabama. 8. Division of Trauma, Critical Care, and Acute Care Surgery, Oregon Health Sciences University, Portland, Oregon. 9. University of Washington Division of Trauma, Burn, and Critical Care Surgery, Seattle, Washington. 10. Palliative Medicine, UT Southwestern Department of Internal Medicine, Dallas, Texas. 11. University of Florida Division of Acute Care Surgery, Gainesville, Florida. 12. Wright State University Division of Acute Care Surgery, Dayton, Ohio.
Abstract
BACKGROUND/ OBJECTIVES: The P.A.L.Li.A.T.E. (prognostic assessment of life and limitations after trauma in the elderly) consortium has previously created a prognosis calculator for mortality after geriatric injury based on age, injury severity, and transfusion requirement called the geriatric trauma outcome score (GTOS). Here, we sought to create and validate a prognosis calculator called the geriatric trauma outcome score ii (GTOS II) estimating probability of unfavorable discharge. DESIGN: Retrospective cohort. SETTING: Four geographically diverse Level 1 trauma centers. PARTICIPANTS: Trauma admissions aged 65 to 102 years surviving to discharge from 2000 to 2013. INTERVENTION: None. MEASUREMENTS: Age, injury severity score (ISS), transfusion at 24 hours post-admission, discharge dichotomized as favorable (home/rehabilitation) or unfavorable (skilled nursing/long term acute care/hospice). Training and testing samples were created using the holdout method. A multiple logistic mixed model (GTOS II) was created to estimate the odds of unfavorable disposition then re-specified using the GTOS II as the sole predictor in a logistic mixed model using the testing sample. RESULTS: The final dataset was 16,114 subjects (unfavorable discharge status = 15.4%). Training (n = 8,057) and testing (n = 8,057) samples had similar demographics. The formula based on the training sample was (GTOS II = Age + [0.71 × ISS] + 8.79 [if transfused by 24 hours]). Misclassification rate and AUC were 15.63% and 0.67 for the training sample, respectively, and 15.85% and 0.67 for the testing sample. CONCLUSION: GTOS II estimates the probability of unfavorable discharge in injured elders with moderate accuracy. With the GTOS mortality calculator, it can help in goal setting conversations after geriatric injury.
BACKGROUND/ OBJECTIVES: The P.A.L.Li.A.T.E. (prognostic assessment of life and limitations after trauma in the elderly) consortium has previously created a prognosis calculator for mortality after geriatric injury based on age, injury severity, and transfusion requirement called the geriatric trauma outcome score (GTOS). Here, we sought to create and validate a prognosis calculator called the geriatric trauma outcome score ii (GTOS II) estimating probability of unfavorable discharge. DESIGN: Retrospective cohort. SETTING: Four geographically diverse Level 1 trauma centers. PARTICIPANTS: Trauma admissions aged 65 to 102 years surviving to discharge from 2000 to 2013. INTERVENTION: None. MEASUREMENTS: Age, injury severity score (ISS), transfusion at 24 hours post-admission, discharge dichotomized as favorable (home/rehabilitation) or unfavorable (skilled nursing/long term acute care/hospice). Training and testing samples were created using the holdout method. A multiple logistic mixed model (GTOS II) was created to estimate the odds of unfavorable disposition then re-specified using the GTOS II as the sole predictor in a logistic mixed model using the testing sample. RESULTS: The final dataset was 16,114 subjects (unfavorable discharge status = 15.4%). Training (n = 8,057) and testing (n = 8,057) samples had similar demographics. The formula based on the training sample was (GTOS II = Age + [0.71 × ISS] + 8.79 [if transfused by 24 hours]). Misclassification rate and AUC were 15.63% and 0.67 for the training sample, respectively, and 15.85% and 0.67 for the testing sample. CONCLUSION: GTOS II estimates the probability of unfavorable discharge in injured elders with moderate accuracy. With the GTOS mortality calculator, it can help in goal setting conversations after geriatric injury.