SLEEP AND EEG DISCRIMINATION OF DEMENTIA FROM DEPRESSION

痴呆症和抑郁症是老年患者的常见问题， 每年都有很多养老院的入院者。精神功能丧失 在阿尔茨海默病的早期阶段，痴呆症通常会因 抑郁症，造成了一个诊断困境，阻碍了治疗和 有效的应对策略。睡眠和某些脑电测量在 阿尔茨海默氏症，可能是由于胆碱能脑的退化 小路。我们对非抑郁症老年人的初步研究显示， 睡眠和脑电变量是早期阿尔茨海默氏症的良好标志 痴呆症。该项目旨在确认和扩展这些研究， 检查这些和其他潜在的医学健康诊断标记物 社区老年人，有或没有可诊断的轻度阿尔茨海默氏症。 将评估睡眠和脑电(频率、功率和连贯性)测量 有两个可取的品质：(1)辨别轻度痴呆的能力 非痴呆症和(2)区分轻度痴呆和重度痴呆的能力 抑郁症。将研究一个主要的抑郁症受试者群体，以便 确定并消除以相同方式受到以下影响的所有措施 抑郁症和痴呆症都有。区分轻度痴呆症和 非痴呆症(或严重抑郁症)将使用一系列 判别分析(DA)。这些DA中出现的预测变量将 使用以前的受试组进行重新检查，以便复制结果 只要有可能。最佳预测值的灵敏度和特异度 将计算变量。有可能做出有用的诊断 阿尔茨海默氏症早期阶段的标志物可能会出现。一个 第二个目标是进一步评估这些预测变量 应用多元回归分析认知损失的相关因素。一系列 认知测试，涵盖痴呆症和非痴呆症范围 我们将考察他们的认知能力。我们假设初级神经元 变性可能导致认知丧失，也可能导致睡眠和脑电 变化；这一假说将预测睡眠和脑电标志对轻度 痴呆症的诊断也将与因以下原因造成的认知损失高度相关 潜在的有机变化。

Dementia and depression are common problems in geriatric patients and account for many nursing home admissions each year. Mental function loss in the earliest stages of Alzheimer's dementia is often complicated by depression, creating a diagnostic dilemma that hampers treatment and effective coping strategies. Sleep and certain EEG measures are altered in Alzheimer's dementia, perhaps due to degeneration in cholinergic brain pathways. Our initial studies among non-depressed elderly revealed that sleep and EEG variables serve well as markers for early Alzheimer's dementia. This project seeks to confirm and expand these studies, examining these and other potential diagnostic markers in medically healthy communtiy elderly, with and without diagnosable mild Alzheimer's dementia. Sleep and EEG (frequency, power and coherence) measures will be evaluated for two desirable qualities: (1) ability to discriminate mild dementia from non-dementia and (2) ability to discriminate mild dementia from major depression. A major depression subject group will be studied in order to identify and eliminate all measures that are affected in the same way by both depression and dementia. Ability to discriminate mild dementia from non-dementia (or from major depression) will be evaluated using a series of discriminant analyses (DA). Predictor variables emerging in these DAs will be reexamined using previous subject groups in order to replicate results wherever possible. Sensitivity and specificity of the best predictor variables will be calculated. It is possible that useful diagnostic markers for the earliest stages of Alzheimer's dementia may result. A second objective is to further evaluate these predicator variables as correlates of cognitive loss using multiple regression analyses. A series of cognitive tests, covering both dementia and nondementia ranges of cognition will be examined. We hypothesize that primary neuronal degeneration may underlie both cognitive loss and also sleep and EEG changes; this hypothesis would predict that sleep and EEG markers for mild dementia diagnosis will also correlate highly with cognitive loss due to underlying organic changes.