Preclinical Alzheimer Disease and Driving

临床前阿尔茨海默病与驾驶

• 批准号: 10224075
• 负责人: Ganesh M Babulal
• 金额: $ 106.99万
• 依托单位: WASHINGTON UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2024-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10224075
• 关键词: Admission activity; Age; Age-Years; Alzheimer' s Disease; Alzheimer' s disease brain; Alzheimer’s disease biomarker; Amyloid; Amyloid beta-42; Automobile Driving; Behavior; Behavioral; Biological Markers; Biostatistical Methods; Brain Pathology; Cerebrospinal Fluid; Cessation of life; Clinical; Cognitive; Communities; Data; Dementia; Destinations; Deterioration; Diagnosis; Disease; Disease Progression; Elderly; Enrollment; Environment; Evaluation; Event; Goals; Gold; Health; Image; Individual; Infrastructure; Injury; Institutes; Intervention Trial; Knowledge; Link; Long-Term Care; Longitudinal Studies; Measures; Mental Depression; Methodology; Outcome; Outcomes Research; Participant; Performance; Persons; Positioning Attribute; Predictive Value; Proxy; Research; Risk; Safety; Spinal Puncture; Standardization; Surveys; System; Testing; Time; Travel; United States; Vehicle crash; Vision; Visit; Work; aged; aging brain; amyloid imaging; cohort; data acquisition; driving behavior; driving safety; driving skills; imaging biomarker; innovation; interest; member; mild cognitive impairment; mortality; multidisciplinary; neuroimaging marker; novel; older driver; pre-clinical; predictive modeling; repository; research study; secondary analysis; tau Proteins; time use

PROJECT SUMMARY/ABSTRACT The goal of this research is to characterize the long-term impact of Alzheimer disease (AD) brain pathology on driving behavior and driving cessation among persons with and without preclinical AD. Our findings indicate that the long preclinical stage of AD, as reflected in amyloid imaging and cerebrospinal fluid (CSF) biomarkers among cognitively normal persons, is associated with poorer driving performance on a standardized road test. This research is significant because 36 million licensed drivers are aged 65 years or older, and the number of older adults in the United States is expected to double by 2050, when 1 in 4 drivers will be 65 years or older. Motor vehicle crashes are a leading cause of injury and death in older adults. The ability to identify who will be at most risk of driving decline and to predict when decline will occur will inform early driving safety intervention trials for older adults. Preclinical AD is an important stage during which to plan and implement safety measures in anticipation of changes in driving skills with disease progression. Our Specific Aims will determine how levels of both novel and well-established AD biomarkers and other age- and disease-associated factors are related to driving performance across the course of preclinical AD: (1) To maintain and grow our unique cohort of older adult drivers with and without preclinical AD. (2) To test whether preclinical AD predicts cross-sectional differences and longitudinal changes in naturalistic driving. (3) To identify driving, biomarker, clinical, physical, and behavioral predictors of driving cessation, and to develop predictive models using these variables. To test these Specific Aims, we have assembled a multidisciplinary team with expertise in AD, neuroimaging biomarkers, CSF biomarkers, driving generally, naturalistic driving specifically, cognitive and brain aging, and longitudinal biostatistical methods. We will capitalize on existing infrastructure to follow our current cohort of 180 cognitively normal participants with and without preclinical AD, and add additional participants to create a cohort of 300 individuals. This larger cohort will continue to undergo an annual driving test, as well as utilize a naturalistic driving methodology that will capture their driving behaviors on an everyday basis. The long-term impact of AD brain pathology will be defined in several ways to help understand its impact on driving performance, behavior, and cessation. Additionally, we will create predictive models of driving cessation. Once obtained, this knowledge can be used to create stage-appropriate, personalized, driving-related safety strategies that can be implemented upon diagnosis, and adjusted throughout disease progression.

项目概要/摘要 这项研究的目标是描述阿尔茨海默病 (AD) 大脑的长期影响 患有和未患有临床前 AD 的人的驾驶行为和停止驾驶的病理学。我们的 研究结果表明，淀粉样蛋白成像和脑脊液反映了 AD 的长期临床前阶段 （脑脊液）生物标志物在认知正常的人中，与较差的驾驶表现有关 标准化道路测试。 这项研究意义重大，因为 3600 万持有执照的驾驶员年龄在 65 岁或以上，而且 到 2050 年，美国老年人数量预计将增加一倍，届时四分之一的驾驶员将年满 65 岁 或更老。机动车碰撞事故是老年人受伤和死亡的主要原因。识别能力 谁最有可能驾驶能力下降，预测驾驶能力下降何时发生将为早期驾驶安全提供信息 针对老年人的干预试验。临床前AD是规划和实施的重要阶段 预测驾驶技能随疾病进展而变化的安全措施。 我们的具体目标将决定新型和成熟的 AD 生物标志物的水平以及 其他与年龄和疾病相关的因素与整个临床前过程中的驾驶表现有关 AD：(1) 维持和发展我们独特的患有或未患有临床前 AD 的老年驾驶员群体。 (2) 至 测试临床前 AD 是否可以预测自然驾驶中的横截面差异和纵向变化。 (3) 识别驾驶、生物标志物、停止驾驶的临床、身体和行为预测因素，并 使用这些变量开发预测模型。 为了测试这些具体目标，我们组建了一支具有 AD 专业知识的多学科团队， 神经影像生物标志物、脑脊液生物标志物、一般驾驶、具体自然驾驶、认知和 脑老化和纵向生物统计方法。我们将利用现有的基础设施来遵循我们的 当前队列由 180 名患有或不患有临床前 AD 的认知正常参与者组成，并添加额外的 参与者创建一个由 300 人组成的队列。这个更大的群体将继续接受年度驾驶 测试，并利用自然驾驶方法来捕捉他们每天的驾驶行为 基础。 AD 大脑病理学的长期影响将通过多种方式来定义，以帮助理解其影响 关于驾驶表现、行为和停车。此外，我们将创建驾驶预测模型 停止。 一旦获得，这些知识可用于创建适合舞台的、个性化的、与驾驶相关的 可以在诊断后实施并在整个疾病进展过程中进行调整的安全策略。

项目成果

The Role of Eye Tracking Technology in Assessing Older Driver Safety.

眼动追踪技术在评估老年驾驶员安全中的作用。

• 发表时间: 2020-06-07
• 作者: Carr, David B;Grover, Prateek
• 通讯作者: Grover, Prateek