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Predictors of Extended Rehabilitation Length of Stay After Traumatic Brain Injury |
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| Authors: | Juan Carlos Arango-Lasprilla Jessica M Ketchum David Cifu Flora Hammond Camilo Castillo Elizabeth Nicholls Thomas Watanabe Anthony Lequerica Xiaoyan Deng |
| Institution: | a Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA b Department of Biostatistics, Virginia Commonwealth University, Richmond, VA c Center for Rehabilitation Sciences and Engineering, Virginia Commonwealth University, Richmond, VA d Indiana University School of Medicine, Indianapolis, IN e Carolinas Rehabilitation, Charlotte, NC f Moss Rehab/Albert Einstein Medical Center, Philadelphia, PA g Department of Physical Medicine and Rehabilitation, University of Medicine and Dentistry of New Jersey, Newark h Kessler Foundation, West Orange, NJ i Physical Medicine and Rehabilitation Service, Richmond Veterans Administration Medical Center, Richmond, VA |
| Abstract: | Arango-Lasprilla JC, Ketchum JM, Cifu D, Hammond F, Castillo C, Nicholls E, Watanabe T, Lequerica A, Deng X. Predictors of extended rehabilitation length of stay after traumatic brain injury.ObjectiveTo develop a prediction rule for acutely identifying patients at risk for extended rehabilitation length of stay (LOS) after traumatic brain injury (TBI) by using demographic and injury characteristics.DesignRetrospective cohort study.SettingTraumatic Brain Injury Model Systems.ParticipantsSample of TBI survivors (N=7284) with injuries occurring between 1999 and 2009.InterventionsNot applicable.Main Outcome MeasuresExtended rehabilitation LOS defined as 67 days or longer.ResultsA multivariable model was built containing FIM motor and cognitive scores at admission, preinjury level of education, cause of injury, punctate/petechial hemorrhage, acute-care LOS, and primary payor source. The model had good calibration, excellent discrimination (area under the receiver operating characteristic curve = .875), and validated well. Based on this model, a formula for determining the probability of extended rehabilitation LOS and a prediction rule that classifies patients with predicted probabilities greater than 4.9% as at risk for extended rehabilitation LOS were developed.ConclusionsThe current predictor model for TBI survivors who require extended inpatient rehabilitation may allow for enhanced rehabilitation team planning, improved patient and family education, and better use of health care resources. Cross-validation of this model with other TBI populations is recommended. |
| Keywords: | Brain injuries Length of stay Prognosis Rehabilitation |
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