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Predictors of functional recovery and description of outcomes after pediatric brain injury
Brain dysfunction in children can result from multiple causes, including trauma, hypoxia, diseases of the central nervous system, metabolic disorders, tumors, vascular abnormalities, and congenital neurological disorders. Goals of rehabilitation research in children with brain dysfunction include identification of factors that impact functional recovery as well as description of functional outcomes. Prediction and description of outcomes is important for targeting and evaluating rehabilitation interventions, providing education to families and caregivers, and helping prepare for the individual’s future. In addition, this information is important for the design of future prospective studies.
Several factors have been found to be predictors of outcome in children with brain dysfunction, including etiology, severity of the injury, and level of consciousness immediately following injury. However, as outcomes are often described globally and little distinction made between the types of injury, it is difficult to apply this information to individual patients. This project proposes to further evaluate predictors of recovery and functional outcomes in children with brain dysfunction. Potential predictors of outcome to be examined include child and injury factors such as etiology of injury, severity of injury, neuropsychological state immediately following injury, pre-injury function, demographic factors, and magnetic resonance imaging findings. Outcome variables will include measures of cognitive and motor function during inpatient rehabilitation and at subsequent follow-up.
This study will be a retrospective record review of children and young adults who were admitted to the Kennedy Krieger Institute’s Brain Injury Rehabilitation program between January 1, 1998 and November 20, 2009. Existing medical data collected as part of routine clinical care during inpatient stays and follow-up visits at Johns Hopkins Hospital and Kennedy Krieger Institute will be extracted. Once this data is collected, we will create a database that is de-identified of all protected health information.
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