Project Summary/AbstractTraumatic brain injury (TBI) is amongst the leading causes of death and disability in the United States andWorldwide. Each year in the United States, there are an estimated 1.7 million TBIs, resulting in 52,000 deaths,275,000 hospitalizations, and 1,365,000 Emergency Department visits. These TBIs result in substantialnegative impact to many individuals with TBI. Currently, there are not treatments that can be delivered in theacute post-injury time period that have been shown to result in improved patient outcomes. There is anundeniable need for effective treatments for patients with TBI who are likely to develop prolonged post-TBIdeficits. A major shortcoming in the TBI field is the inability to accurately classify a patient with TBI according tothat patients expected outcomes. Current classification systems use broad criteria to assign patients to ?mild?,?moderate? or ?severe? TBI categories. However, these criteria often allow for patients who are very differentfrom one another, who have had very different injuries, and who have very different post-injury signs andsymptoms, to be classified into the same TBI group. Current classification results in patients who are classifiedthe same, e.g. as ?mild? TBI, to have substantially variable outcomes. Our research, a secondary analysis oflarge datasets contained within FITBIR, aims to develop a more precise classification system for patients whohave experienced a TBI that correlates with expected patient outcomes. To make the classification systempractical for use by clinicians and researchers, data that are typically available at the time of the initial patientevaluation will be utilized. Factors that might be predictive of patient outcomes and will thus be considered forinclusion in the refined classification system relate to neurologic symptoms immediately following TBI, findingsat the initial medical evaluation, presence and characteristics of prior TBIs, history of medical, neurologic, andpsychiatric disorders, mechanism of TBI, and patient socio-demographics. The more precise TBI classificationsystem that will result from this research will inform clinicians on how aggressively to prescribe rehabilitativetherapies, will allow for more accurate prognostication of patient outcomes, and will help to determine inclusionand exclusion criteria for future clinical trials of TBI therapies.
|Effective start/end date||7/22/16 → 6/30/18|
- National Institutes of Health: $247,749.00