Performance and validation of a digital memory test across the Alzheimer's disease continuum.

IF 4.5 Q1 CLINICAL NEUROLOGY Brain communications Pub Date : 2025-01-17 eCollection Date: 2025-01-01 DOI:10.1093/braincomms/fcaf024
Sofia Toniolo, Bahaaeddin Attaallah, Maria Raquel Maio, Younes Adam Tabi, Elitsa Slavkova, Verena Svenja Klar, Youssuf Saleh, Mohamad Imran Idris, Vicky Turner, Christoph Preul, Annie Srowig, Christopher Butler, Sian Thompson, Sanjay G Manohar, Kathrin Finke, Masud Husain
{"title":"Performance and validation of a digital memory test across the Alzheimer's disease continuum.","authors":"Sofia Toniolo, Bahaaeddin Attaallah, Maria Raquel Maio, Younes Adam Tabi, Elitsa Slavkova, Verena Svenja Klar, Youssuf Saleh, Mohamad Imran Idris, Vicky Turner, Christoph Preul, Annie Srowig, Christopher Butler, Sian Thompson, Sanjay G Manohar, Kathrin Finke, Masud Husain","doi":"10.1093/braincomms/fcaf024","DOIUrl":null,"url":null,"abstract":"<p><p>Digital cognitive testing using online platforms has emerged as a potentially transformative tool in clinical neuroscience. In theory, it could provide a powerful means of screening for and tracking cognitive performance in people at risk of developing conditions such as Alzheimer's disease. Here we investigate whether digital metrics derived from an in-person administered, tablet-based short-term memory task-the 'What was where?' Oxford Memory Task-were able to clinically stratify patients at different points within the Alzheimer's disease continuum and to track disease progression over time. Performance of these metrics compared to traditional neuropsychological pen-and-paper screening tests of cognition was also analysed. A total of 325 people participated in this study: 49 patients with subjective cognitive decline, 57 with mild cognitive impairment, 63 with Alzheimer's disease dementia and 156 elderly healthy controls. Most digital metrics were able to discriminate between healthy controls and patients with mild cognitive impairment and between mild cognitive impairment and Alzheimer's disease patients. Some, including Absolute Localization Error, also differed significantly between patients with subjective cognitive decline and mild cognitive impairment. Identification accuracy was the best predictor of hippocampal atrophy, performing as well as standard screening neuropsychological tests. A linear support vector model combining digital metrics achieved high accuracy and performed at par with standard testing in discriminating between elderly healthy controls and subjective cognitive decline (area under the curve 0.82) and between subjective cognitive decline and mild cognitive impairment (area under the curve 0.92), while performing worse in classifying between mild cognitive impairment and Alzheimer's disease patients (area under the curve 0.75). Memory imprecision was able to predict cognitive decline on standard cognitive tests over one year. Overall, these findings show how it might be possible to use a digital memory test in clinics and clinical trial contexts to stratify and track performance across the Alzheimer's disease continuum.</p>","PeriodicalId":93915,"journal":{"name":"Brain communications","volume":"7 1","pages":"fcaf024"},"PeriodicalIF":4.5000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11780857/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brain communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1093/braincomms/fcaf024","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}
引用次数: 0

Abstract

Digital cognitive testing using online platforms has emerged as a potentially transformative tool in clinical neuroscience. In theory, it could provide a powerful means of screening for and tracking cognitive performance in people at risk of developing conditions such as Alzheimer's disease. Here we investigate whether digital metrics derived from an in-person administered, tablet-based short-term memory task-the 'What was where?' Oxford Memory Task-were able to clinically stratify patients at different points within the Alzheimer's disease continuum and to track disease progression over time. Performance of these metrics compared to traditional neuropsychological pen-and-paper screening tests of cognition was also analysed. A total of 325 people participated in this study: 49 patients with subjective cognitive decline, 57 with mild cognitive impairment, 63 with Alzheimer's disease dementia and 156 elderly healthy controls. Most digital metrics were able to discriminate between healthy controls and patients with mild cognitive impairment and between mild cognitive impairment and Alzheimer's disease patients. Some, including Absolute Localization Error, also differed significantly between patients with subjective cognitive decline and mild cognitive impairment. Identification accuracy was the best predictor of hippocampal atrophy, performing as well as standard screening neuropsychological tests. A linear support vector model combining digital metrics achieved high accuracy and performed at par with standard testing in discriminating between elderly healthy controls and subjective cognitive decline (area under the curve 0.82) and between subjective cognitive decline and mild cognitive impairment (area under the curve 0.92), while performing worse in classifying between mild cognitive impairment and Alzheimer's disease patients (area under the curve 0.75). Memory imprecision was able to predict cognitive decline on standard cognitive tests over one year. Overall, these findings show how it might be possible to use a digital memory test in clinics and clinical trial contexts to stratify and track performance across the Alzheimer's disease continuum.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
跨阿尔茨海默病连续体的数字记忆测试的性能和验证。
使用在线平台的数字认知测试已经成为临床神经科学的潜在变革工具。从理论上讲,它可以提供一种强有力的手段来筛查和跟踪那些有患阿尔茨海默病等疾病风险的人的认知表现。在这里,我们调查了数字指标是否来自于一个亲自管理的、基于平板电脑的短期记忆任务——“什么在哪里?”牛津记忆任务-能够在阿尔茨海默病连续体的不同阶段对患者进行临床分层,并跟踪疾病随时间的进展。与传统的神经心理学笔和纸的认知筛选测试相比,这些指标的表现也进行了分析。共有325人参与了这项研究:49名主观认知能力下降的患者,57名轻度认知障碍患者,63名阿尔茨海默病痴呆患者和156名老年人健康对照。大多数数字指标能够区分健康对照者和轻度认知障碍患者,以及轻度认知障碍患者和阿尔茨海默病患者。包括绝对定位误差在内的一些指标在主观认知能力下降和轻度认知障碍患者之间也存在显著差异。识别准确性是海马萎缩的最佳预测指标,表现与标准筛选神经心理学测试一样好。结合数字指标的线性支持向量模型在区分老年人健康对照组与主观认知能力下降(曲线下面积0.82)以及主观认知能力下降与轻度认知障碍(曲线下面积0.92)方面取得了较高的准确性,与标准测试相当,而在区分轻度认知障碍与阿尔茨海默病患者(曲线下面积0.75)方面表现较差。在一年多的标准认知测试中,记忆不精确能够预测认知能力的下降。总的来说,这些发现表明,在临床和临床试验背景下,如何使用数字记忆测试来分层和跟踪阿尔茨海默病连续体的表现是可能的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
7.00
自引率
0.00%
发文量
0
审稿时长
6 weeks
期刊最新文献
Replication study: the case of disappearing teaspoons in a Scottish neuroscience department. Cortical gyrification deficits in early-stage Parkinson's disease: the importance of bradykinesia. Increased CSF levels of soluble AXL at diagnosis correlate with poor prognosis in patients affected by amyotrophic lateral sclerosis. Pontine pathology mediates common symptoms of blast-induced chronic mild traumatic brain injury. Juvenile myoclonic epilepsy heterogeneity uncovered: Z-mapped imaging endophenotypes of cortical and subcortical structures and their clinical, cognitive and psychiatric features.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1