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Using a Digital Neuro Signature to measure longitudinal individual-level change in Alzheimer’s disease: the Altoida large cohort study
npj Digital Medicine ( IF 12.4 ) Pub Date : 2021-06-24 , DOI: 10.1038/s41746-021-00470-z
Irene B Meier 1 , Max Buegler 2 , Robbert Harms 2 , Azizi Seixas 3 , Arzu Çöltekin 4 , Ioannis Tarnanas 2, 5, 6, 7
Affiliation  

Conventional neuropsychological assessments for Alzheimer’s disease are burdensome and inaccurate at detecting mild cognitive impairment and predicting Alzheimer’s disease risk. Altoida’s Digital Neuro Signature (DNS), a longitudinal cognitive test consisting of two active digital biomarker metrics, alleviates these limitations. By comparison to conventional neuropsychological assessments, DNS results in faster evaluations (10 min vs 45–120 min), and generates higher test-retest in intraindividual assessment, as well as higher accuracy at detecting abnormal cognition. This study comparatively evaluates the performance of Altoida’s DNS and conventional neuropsychological assessments in intraindividual assessments of cognition and function by means of two semi-naturalistic observational experiments with 525 participants in laboratory and clinical settings. The results show that DNS is consistently more sensitive than conventional neuropsychological assessments at capturing longitudinal individual-level change, both with respect to intraindividual variability and dispersion (intraindividual variability across multiple tests), across three participant groups: healthy controls, mild cognitive impairment, and Alzheimer’s disease. Dispersion differences between DNS and conventional neuropsychological assessments were more pronounced with more advanced disease stages, and DNS-intraindividual variability was able to predict conversion from mild cognitive impairment to Alzheimer’s disease. These findings are instrumental for patient monitoring and management, remote clinical trial assessment, and timely interventions, and will hopefully contribute to a better understanding of Alzheimer’s disease.



中文翻译:


使用数字神经特征测量阿尔茨海默病的纵向个体水平变化:Altoida 大型队列研究



阿尔茨海默病的传统神经心理学评估在检测轻度认知障碍和预测阿尔茨海默病风险方面是繁琐且不准确的。 Altoida 的数字神经特征 (DNS) 是一种纵向认知测试,由两个主动数字生物标记指标组成,可以缓解这些限制。与传统的神经心理学评估相比,DNS 可以实现更快的评估(10 分钟 vs 45-120 分钟),并在个体评估中产生更高的重测率,以及检测异常认知的准确性更高。本研究通过在实验室和临床环境中对 525 名参与者进行的两项半自然观察实验,比较评估了 Altoida 的 DNS 和传统神经心理学评估在个体认知和功能评估中的表现。结果表明,在捕获纵向个体水平变化方面,DNS 始终比传统的神经心理学评估更敏感,无论是在个体内变异性还是离散性(多个测试中的个体变异性)方面,跨越三个参与者组:健康对照、轻度认知障碍和阿尔茨海默病。 DNS 和传统神经心理学评估之间的分散差异随着疾病阶段的进展而更加明显,并且 DNS 个体内变异性能够预测从轻度认知障碍到阿尔茨海默病的转变。这些发现有助于患者监测和管理、远程临床试验评估和及时干预,并有望有助于更好地了解阿尔茨海默病。

更新日期:2021-06-24
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