Turner Osler1, Alan Cook2, Laurent G Glance3, Fiona Lecky4, Omar Bouamra5, Mark Garrett6, Jeffery S Buzas7, David W Hosmer8. 1. Department of Surgery, University of Vermont, 789 Orchard Shore Road, Colchester, VT 05446, United States. Electronic address: tosler@uvm.edu. 2. Trauma Research Program, Chandler Regional Medical Center, United States; Department of Surgery University of Arizona College of Medicine, Phoenix, United States. Electronic address: alan.cook@dignityhealth.org. 3. Department of Anesthesiology, University of Rochester, United States. Electronic address: Laurent_glance@umc.rochester.edu. 4. Emergency Medicine, University of Sheffield, United Kingdom; Trauma Audit and Research Network, United Kingdom. Electronic address: fiona.lecky@manchester.ac.uk. 5. Trauma Audit and Research Network, United Kingdom. Electronic address: omar.bouamra@manchester.ac.uk. 6. Chandler Regional Medical Center, United States. Electronic address: mark.garrett@bnaneuro.net. 7. Department of Mathematics and Statistics, University of Vermont, United States. Electronic address: jbuzas@uvm.edu. 8. School of Public Health and Health Sciences, University of Massachusetts, United States. Electronic address: hosmer@schoolph.umass.edu.
Abstract
IMPORTANCE: The GCS was created forty years ago as a measure of impaired consciousness following head injury and thus the association of GCS with mortality in patients with traumatic brain injury (TBI) is expected. The association of GCS with mortality in patients without TBI (non-TBI) has been assumed to be similar. However, if this assumption is incorrect mortality prediction models incorporating GCS as a predictor will need to be revised. OBJECTIVE: To determine if the association of GCS with mortality is influenced by the presence of TBI. DESIGN/SETTING/PARTICIPANTS: Using the National Trauma Data Bank (2012; N=639,549) we categorized patients as isolated TBI (12.8%), isolated non-TBI (33%), both (4.8%), or neither (49.4%) based on the presence of AIS codes of severity 3 or greater. We compared the ability GCS to discriminate survivors from non-survivors in TBI and in non-TBI patients using logistic models. We also estimated the odds ratios of death for TBI and non-TBI patients at each value of GCS using linear combinations of coefficients. MAIN OUTCOME MEASURE: Death during hospital admission. RESULTS: As the sole predictor in a logistic model GCS discriminated survivors from non-survivors at an acceptable level (c-statistic=0.76), but discriminated better in the case of TBI patients (c-statistic=0.81) than non-TBI patients (c-statistic=0.70). In both unadjusted and covariate adjusted models TBI patients were about twice as likely to die as non-TBI patients with the same GCS for GCS values<8; for GCS values>8 TBI and non-TBI patients were at similar risk of dying. CONCLUSIONS: A depressed GCS predicts death better in TBI patients than non-TBI patients, likely because in non-TBI patients a depressed GCS may simply be the result of entirely reversible intoxication by alcohol or drugs; in TBI patients, by contrast, a depressed GCS is more ominous because it is likely due to a head injury with its attendant threat to survival. Accounting for this observation into trauma mortality datasets and models may improve the accuracy of outcome prediction.
IMPORTANCE: The GCS was created forty years ago as a measure of impaired consciousness following head injury and thus the association of GCS with mortality in patients with traumatic brain injury (TBI) is expected. The association of GCS with mortality in patients without TBI (non-TBI) has been assumed to be similar. However, if this assumption is incorrect mortality prediction models incorporating GCS as a predictor will need to be revised. OBJECTIVE: To determine if the association of GCS with mortality is influenced by the presence of TBI. DESIGN/SETTING/PARTICIPANTS: Using the National Trauma Data Bank (2012; N=639,549) we categorized patients as isolated TBI (12.8%), isolated non-TBI (33%), both (4.8%), or neither (49.4%) based on the presence of AIS codes of severity 3 or greater. We compared the ability GCS to discriminate survivors from non-survivors in TBI and in non-TBI patients using logistic models. We also estimated the odds ratios of death for TBI and non-TBI patients at each value of GCS using linear combinations of coefficients. MAIN OUTCOME MEASURE: Death during hospital admission. RESULTS: As the sole predictor in a logistic model GCS discriminated survivors from non-survivors at an acceptable level (c-statistic=0.76), but discriminated better in the case of TBI patients (c-statistic=0.81) than non-TBI patients (c-statistic=0.70). In both unadjusted and covariate adjusted models TBI patients were about twice as likely to die as non-TBI patients with the same GCS for GCS values<8; for GCS values>8 TBI and non-TBI patients were at similar risk of dying. CONCLUSIONS: A depressed GCS predicts death better in TBI patients than non-TBI patients, likely because in non-TBI patients a depressed GCS may simply be the result of entirely reversible intoxication by alcohol or drugs; in TBI patients, by contrast, a depressed GCS is more ominous because it is likely due to a head injury with its attendant threat to survival. Accounting for this observation into trauma mortality datasets and models may improve the accuracy of outcome prediction.