DNS Cohort Study Aimed at Understanding the Pathophysiology of AD and AD Related Disorders (ADRD)
试验速览
- 阶段
- 不适用
- 状态
- 进行中（未招募）
- 发起方
- Altoida
- 入组人数
- 3,500
- 试验地点
- 1
- 主要终点
- Demographics, medical history, physical status, life-habits, and medication from the analysis of neuropsychological assessments.
研究概览
简要总结
Alzheimer's disease (AD) clinically characterized by the cognitive impairment and lowering of various functional abilities lead to staggering costs and suffering, which are particularly related to the social impacts of caring for increasingly disabled individuals. Some of these changes can be almost undetectable in the early stages of the disease, worsening over time often and at a varying rate of progression in different people. The traditional clinical scales or questionnaires such as ADCS (Alzheimer's Disease Cooperative Study) - ADL (Activities of Daily Living) for detecting such functional disabilities are typically blunt and rely on direct observation or caregiver recall. Digital technologies, particularly those based on the use of smart phones, wearable and/or home-based monitoring devices, here defined as 'Remote Measurement Technologies' (RMTs), provide an opportunity to change radically the way in which functional assessment is undertaken in AD, RMTs have potential to obtain better measurements of behavioral and biological parameters associated with individual Activities of Daily Living (ADL) when compared to the current subjective scales or questionnaires. Divergence from normative ADL profiles could objectively indicate the presence of incipient functional impairment at the very early stages of AD. Therefore, the main hypothesis of this study is that RMTs should allow the detection of impairments in functional components of ADLs that occur below the detection threshold of clinical scale or questionnaires.
详细描述
Relevant outcome measurements for the study have been selected through the following longitudinal process:
Identification of functional domains that meet one or more of the following criteria:
Predicts conversion of MCI due to AD to mild AD dementia. Impaired in mild AD dementia. Predicts functional decline in AD dementia. Reported as important by an AD dementia patient advisory board. Identification of candidate RMTs to cover real-life measurement of the functional domains identified in step 1.
Identification of candidate digital biomarkers, which are life-log data such as steps, sleep, heart rate and exercise collected by RMTs, to cover clinical measurement of the functional domains identified in step 1.
Functional domains, RMTs, and clinical assessments that resulted from the selection process above are listed in Table 1, and 2. The selection process described in step 1 resulted in the identification of the following functional domains, sorted by relevance [HR (highly relevant), R (relevant), N (neutral), and LR (least relevant)].
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 50 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 是
入选标准
- 未提供
排除标准
- 未提供
结局指标
主要结局
Demographics, medical history, physical status, life-habits, and medication from the analysis of neuropsychological assessments.
时间窗: 5 years
Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia focusing on their demographics, medical history, physical status, life-habits, and medication from the analysis of neuropsychological assessments.
ADL using selected RMTs
时间窗: 5 years
Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia in outcome measures of ADL using selected RMTs.
Neuropsychological assessment like Altoida, Inc. Neuro Motor Index (NMI) medical device
时间窗: 5 years
Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia using RMTs, neuropsychological assessment like the Altoida, Inc. Neuro Motor Index (NMI) medical device.
Demographics, medical history, physical status, life-habits, and medication from the analysis of RMTs
时间窗: 5 years
Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia focusing on their demographics, medical history, physical status, life-habits, and medication from the analysis of RMTs.
Neuropsychological assessment like the Clinical Dementia Rating (CDR) scale
时间窗: 5 years
Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia using RMTs, neuropsychological assessment like CDR.
Demographics, medical history, physical status, life-habits, and medication from the analysis of biomarker measurements.
时间窗: 5 years
Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia focusing on their demographics, medical history, physical status, life-habits, and medication from the analysis of biomarker measurements.
Demographics, medical history, physical status, life-habits, and medication from the analysis of Altoida NMI medical device.
时间窗: 5 years
Assess statistically significant difference between healthy volunteers, preclinical AD, MCI due to AD, mild, moderate and severe AD dementia focusing on their demographics, medical history, physical status, life-habits, and medication from the analysis of Altoida NMI medical device.
次要结局
未报告次要终点