Sleep-EEG Predictors of Functional Outcome after TBI

 描述(由申请人提供)： 创伤性脑损伤是造成退伍军人身体和神经精神残疾的主要原因，尤其是中度到重度的脑损伤，阻碍了社区的重新融入和重新就业。早期预测颅脑损伤的预后是目前所缺乏的迫切需要，也是从现有的VA治疗方案中优化分配稀缺资源以及更好地告知患者及其家人预后所必需的。目前对脑外伤后长期功能结果的预测通常基于人口统计学/社会经济学和临床标记物，仅显示出中等的预测能力；它们还不够精确，不足以指导个体的治疗决定。为了解决脑外伤后对灵敏/特异的功能预后预测指标的迫切需求，我们建议测试基于睡眠脑电(EEG)定量分析的新的脑损伤后功能结果预测指标。分析的结构是基于脑电频段之间的交叉频率耦合(CFC)的测量，反映了产生潜在的脑电节律和振荡模式的神经电路之间的协调。在我们的初步动物研究中，我们已经确定了几个对脑外伤组高度敏感的脑电神经标记物。接下来，我们在接受神经康复治疗的中重度脑损伤退伍军人中(n=7)，研究了这些神经标记物及其与功能结果(功能独立性测量(FIM)和残疾评定量表(DRS))的相关性。我们发现一个特殊的基于睡眠的脑电神经标记物--增量-伽马交叉频率耦合对康复后的功能改善有非常强烈和显著的预测作用(DRS回归模型：R2=0.95F=86，p&lt；0.0002；FIM回归模型：R2=0.91F=50，p&lt；0.001)。重要的是，我们在一年后的跟踪时间点发现了同样强大的预测能力，不仅表明内部 一致性，但也突出了确定有价值的、超长期预测f结果的可能性，(FIM回归模型：R2=0.89，F=40，p&lt；0.002)。本SPIRE项目的主要目的是综合评价基于EEG CFC的神经标记物区分脑外伤和健康对照的能力，并预测中重度脑外伤退伍军人的功能结局。这将通过使用现有的数据库来计算Delta-Gamma神经标记物，该数据库记录了45名健康人和80名患有中重度脑外伤的退伍军人，以及他们在基线、神经康复出院时和出院后一年的功能结果(DRS和FIM)。我们还将探索潜在改进的神经标记物的发展，通过概括我们的分析，包括计算扩展的频段对之间的脑电交叉频率耦合，包括theta，α，Delta和Gamma，以及清醒、非REM和REM睡眠的3种状态。预期结果：本研究将评估可预测中重度脑外伤患者功能恢复和治疗反应的新的客观神经标记物。

 DESCRIPTION (provided by applicant): Traumatic brain injury (TBI), particularly moderate to severe TBI, is a major cause of physical and neuropsychiatric disability in Veterans, preventing community reintegration and return to employment. Early prognostication of outcome from TBI is a critical need which is currently lacking, and is necessary to optimally allocate scarce resources from existing VA treatment programs, and to better inform patients and their families about the prognosis. Current predictors of long-term functional outcome after TBI are generally based on demographic/socioeconomic and clinical markers, and have shown only moderate predictive ability; they have not been sufficiently precise to direct therapy decisions in individuals. To address the critical need for sensitive/specific functional outcome predictors after TBI, we propose to test novel predictors of functional outcome after TBI, which are based on quantitative analysis of electroencephalography (EEG) during sleep. The structure of the analysis is based on measures of cross- frequency couplings (CFC) between EEG frequency bands, reflecting coordination between neural circuits that generate the underlying rhythmic and oscillatory pattern of EEG. In our preliminary animal studies, we have identified several EEG neuromarkers that were highly sensitive to the TBI group. Next, we examined these same neuromarkers and their correlation with functional outcomes (Functional Independence Measure (FIM) and Disability Rating Scale (DRS)) in a small cohort (n=7) of Veterans with moderate-to-severe TBI who received neuro-rehabilitation. We found that one particular sleep-based EEG neuromarker, delta-gamma cross-frequency coupling, very strongly and significantly predicted functional improvement after rehabilitation (DRS regression model: R2=0.95, F=86, p < 0.0002; FIM regression model: R2 =0.91, F= 50, p < 0.001). Importantly, we found the same strong predictive capability at a follow-up time point one-year later, not only indicating robust internal consistency, but also highlighting the potential to identify a valuable, ultra-long term predictor f outcome, (FIM regression model: R2 =0.89, F= 40, p < 0.002) . The main objective of this SPiRE project is to comprehensively evaluate the ability of EEG CFC-based neuromarker to distinguish TBI from healthy control, and to predict Functional Outcomes of Veterans with moderate-severe TBI. This will be accomplished by computing the delta-gamma neuromarkers using an existing database of recorded sleep-EEG studies from 45 healthy individuals, and 80 Veterans with moderate- severe TBI, in conjunction with their measures of functional outcome (DRS and FIM) at baseline, at discharge from neuro-rehabilitation, and at one year post discharge. We will also explore the development of potentially improved neuromarkers by generalizing our analyses to include computation of EEG cross frequency couplings between an expanded pairs of frequency bands including theta, alpha, delta and gamma, and for 3 states of awake, non-REM, and REM sleep. Expected Outcomes: This study will evaluate novel objective neuromarkers that can predict functional recovery and response to treatment in moderate-severe TBI patients.