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Journal of Neurotrauma
Clinical Elements that Predict Outcome after Traumatic Brain Injury: A Prospective Multicenter Recursive Partitioning (Decision-Tree) Analysis
To cite this article:
Allen W. Brown, James F. Malec, Robyn L. McClelland, Nancy N. Diehl, Jeffrey Englander, David X. Cifu.
Journal of Neurotrauma.
October 2005,
22(10): 1040-1051.
doi:10.1089/neu.2005.22.1040.
Allen W. Brown, M.D.Department of Physical Medicine and Rehabilitation, Mayo Clinic College of Medicine, Rochester, Minnesota. James F. Malec Department of Psychiatry and Psychology, Mayo Clinic College of Medicine, Rochester, Minnesota. Robyn L. McClelland Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota. Nancy N. Diehl Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota. Jeffrey Englander Department of Physical Medicine and Rehabilitation, Santa Clara Valley Medical Center, and Department of Functional Restoration, Stanford University School of Medicine, San Jose, California. David X. Cifu Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Medical College of Virginia, Richmond, Virginia. Traumatic brain injury (TBI) often presents clinicians with a complex combination of clinical elements that can confound treatment and make outcome prediction challenging. Predictive models have commonly used acute physiological variables and gross clinical measures to predict mortality and basic outcome endpoints. The primary goal of this study was to consider all clinical elements available concerning a survivor of TBI admitted for inpatient rehabilitation, and identify those factors that predict disability, need for supervision, and productive activity one year after injury. The Traumatic Brain Injury Model Systems (TBIMS) database was used for decision tree analysis using recursive partitioning (n = 3463). Outcome measures included the Functional Independence Measure™, the Disability Rating Scale, the Supervision Rating Scale, and a measure of productive activity. Predictor variables included all physical examination elements, measures of injury severity (initial Glasgow Coma Scale score, duration of post-traumatic amnesia [PTA], length of coma, CT scan pathology), gender, age, and years of education. The duration of PTA, age, and most elements of the physical examination were predictive of early disability. The duration of PTA alone was selected to predict late disability and independent living. The duration of PTA, age, sitting balance, and limb strength were selected to predict productive activity at 1 year. The duration of PTA was the best predictor of outcome selected in this model for all endpoints and elements of the physical examination provided additional predictive value. Valid and reliable measures of PTA and physical impairment after TBI are important for accurate outcome prediction.  This paper was cited by:Traumatic Brain Injury Christian M. Niedzwecki, Jennifer H. Marwitz, Jessica M. Ketchum, David X. Cifu, Charles M. Dillard, Eugenio A. Monasterio Journal of Head Trauma Rehabilitation. Aug 2008, Vol. 23, No. 4: 209-219 CrossRef Functional outcome 10 years after traumatic brain injury: Its relationship with demographic, injury severity, and cognitive and emotional status JENNIE PONSFORD, KRISTY DRAPER, MICHAEL SCHÖNBERGER Journal of the International Neuropsychological Society. Apr 2008, Vol. 14, No. 02 CrossRef The Effect of Premorbid Demographic Factors on the Recovery of Neurocognitive Function in Traumatic Brain Injury Patients Ik-Chan Jeon, Oh-Lyong Kim, Min-Su Kim, Seong-Ho Kim, Chul-Hoon Chang, Dai-Seg Bai Journal of Korean Neurosurgical Society. Feb 2008, Vol. 44, No. 5: 295 CrossRef The Effects of Increasing Stimulus Complexity in Event-Related Potentials and Reaction Time Testing: Clinical Applications in Evaluating Patients with Traumatic Brain Injury Henry L. Lew, Darryl Thomander, Max Gray, John H. Poole Journal of Clinical Neurophysiology. Nov 2007, Vol. 24, No. 5: 398-404 CrossRef A Systematic Review of Early Prognostic Factors for Return to Work After Traumatic Brain Injury Elizabeth J Nightingale, Cheryl A Soo, Robyn L Tate Brain Impairment. Oct 2007, Vol. 8, No. 2: 101-142 CrossRef The Mayo Classification System for Traumatic Brain Injury Severity James F. Malec, Allen W. Brown, Cynthia L. Leibson, Julie Testa Flaada, Jayawant N. Mandrekar, Nancy N. Diehl, Patricia K. Perkins Journal of Neurotrauma. Sep 2007, Vol. 24, No. 9: 1417-1424 Abstract | Full Text PDF | Reprints & PermissionsSelf-assessment of Impairment, Impaired Self-awareness, and Depression After Traumatic Brain Injury James F. Malec, Julie A. Testa, Beth K. Rush, Allen W. Brown, Anne M. Moessner Journal of Head Trauma Rehabilitation. Jun 2007, Vol. 22, No. 3: 156-166 CrossRef Day-of-Injury Computerized Tomography, Rehabilitation Status, and Development of Cerebral Atrophy in Persons with Traumatic Brain Injury Erin D. Bigler, David K. Ryser, Partha Gandhi, Jordan Kimball, Elisabeth A. Wilde American Journal of Physical Medicine & Rehabilitation. Nov 2006, Vol. 85, No. 10: 793-806 CrossRef Prognostic Value of Evoked and Event-related Potentials in Moderate to Severe Brain Injury Henry L. Lew, John H. Poole, Annabel Castaneda, Rose Marie Salerno, Max Gray Journal of Head Trauma Rehabilitation. Aug 2006, Vol. 21, No. 4: 350-360 CrossRef The Accuracy of Artificial Neural Networks in Predicting Long-term Outcome After Traumatic Brain Injury Mary E. Segal, Philip H. Goodman, Richard Goldstein, Walter Hauck, John Whyte, John W. Graham, Marcia Polansky, Flora M. Hammond Journal of Head Trauma Rehabilitation. Aug 2006, Vol. 21, No. 4: 298-314 CrossRef The Use of Serum Biomarkers to Predict Outcome After Traumatic Brain Injury in Adults and Children Rachel Pardes Berger Journal of Head Trauma Rehabilitation. Aug 2006, Vol. 21, No. 4: 315-333 CrossRef
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