Toward new classification criteria for mild and moderate TBI by a data-inclusive cross-study analysis using FITBIR

项目摘要/摘要 创伤性脑损伤(TBI)是美国主要的死亡和残疾原因之一， 全世界。在美国，每年估计有170万人死于脑损伤，导致5.2万人死亡， 275,000人住院，1,365,000人次到急诊科就诊。这些TBI导致大量 对许多脑外伤患者的负面影响。目前，还没有可以在 急性损伤后时间段，已被证明可以改善患者的预后。有一个 不可否认，有必要对有可能在脑外伤后长期发展的脑损伤患者进行有效的治疗 赤字。TBI领域的一个主要缺点是无法根据以下内容准确地对TBI患者进行分类 患者期待的结果。目前的分类系统使用宽泛的标准将患者归类为“轻度”， “中度”或“重度”创伤性脑损伤类别。然而，这些标准通常允许患者非常不同 他们有非常不同的伤病，他们在受伤后有非常不同的迹象和 症状，归入同一脑损伤组。目前的分类结果是对被分类的患者 与“轻度”脑损伤相同，结果有很大的差异。我们的研究，二次分析 包含在FITBIR中的大数据集，旨在为符合以下条件的患者开发更精确的分类系统 经历了与预期患者结局相关的脑损伤。要制定分类系统 可供临床医生和研究人员使用的数据，这些数据通常在初始患者时可用 将利用评估。可能预测患者结果的因素，因此将被考虑 纳入改进的分类系统与脑外伤后立即出现的神经症状有关，研究结果 在最初的医学评估中，先前脑外伤的存在和特征、内科、神经病学和 精神障碍，脑外伤的机制，以及患者的社会人口学。TBI分类越精确 这项研究将产生的系统将告知临床医生如何积极地开出康复药物 治疗，将允许更准确地预测患者的结果，并将有助于确定纳入 以及未来脑损伤疗法临床试验的排除标准。

Project Summary/Abstract Traumatic brain injury (TBI) is amongst the leading causes of death and disability in the United States and Worldwide. 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 substantial negative impact to many individuals with TBI. Currently, there are not treatments that can be delivered in the acute post-injury time period that have been shown to result in improved patient outcomes. There is an undeniable need for effective treatments for patients with TBI who are likely to develop prolonged post-TBI deficits. A major shortcoming in the TBI field is the inability to accurately classify a patient with TBI according to that 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 different from one another, who have had very different injuries, and who have very different post-injury signs and symptoms, to be classified into the same TBI group. Current classification results in patients who are classified the same, e.g. as “mild” TBI, to have substantially variable outcomes. Our research, a secondary analysis of large datasets contained within FITBIR, aims to develop a more precise classification system for patients who have experienced a TBI that correlates with expected patient outcomes. To make the classification system practical for use by clinicians and researchers, data that are typically available at the time of the initial patient evaluation will be utilized. Factors that might be predictive of patient outcomes and will thus be considered for inclusion in the refined classification system relate to neurologic symptoms immediately following TBI, findings at the initial medical evaluation, presence and characteristics of prior TBIs, history of medical, neurologic, and psychiatric disorders, mechanism of TBI, and patient socio-demographics. The more precise TBI classification system that will result from this research will inform clinicians on how aggressively to prescribe rehabilitative therapies, will allow for more accurate prognostication of patient outcomes, and will help to determine inclusion and exclusion criteria for future clinical trials of TBI therapies.