Alim-Marvasti Ali, Kuleindiren Narayan, Harvey Kirsten, Ciocca Matteo, Lin Aaron, Selim Hamzah, Mahmud Mohammad
Research Division, Mindset Technologies Ltd., London, United Kingdom.
Queen Square Institute of Neurology, University College London, London, United Kingdom.
Front Digit Health. 2022 Dec 21;4:1029810. doi: 10.3389/fdgth.2022.1029810. eCollection 2022.
The Clinical Dementia Rating (CDR) and Mini-Mental State Examination (MMSE) are useful screening tools for mild cognitive impairment (MCI). However, these tests require qualified in-person supervision and the CDR can take up to 60 min to complete. We developed a digital cognitive screening test (M-CogScore) that can be completed remotely in under 5 min without supervision. We set out to validate M-CogScore in head-to-head comparisons with CDR and MMSE.
To ascertain the validity of the M-CogScore, we enrolled participants as healthy controls or impaired cognition, matched for age, sex, and education. Participants completed the 30-item paper MMSE Second Edition Standard Version (MMSE-2), paper CDR, and smartphone-based M-CogScore. The digital M-CogScore test is based on time-normalised scores from smartphone-adapted Stroop (M-Stroop), digit-symbols (M-Symbols), and delayed recall tests (M-Memory). We used Spearman's correlation coefficient to determine the convergent validity between M-CogScore and the 30-item MMSE-2, and non-parametric tests to determine its discriminative validity with a CDR label of normal (CDR 0) or impaired cognition (CDR 0.5 or 1). M-CogScore was further compared to MMSE-2 using area under the receiver operating characteristic curves (AUC) with corresponding optimal cut-offs.
72 participants completed all three tests. The M-CogScore correlated with both MMSE-2 (rho = 0.54, < 0.0001) and impaired cognition on CDR (Mann Whitney = 187, < 0.001). M-CogScore achieved an AUC of 0.85 (95% bootstrapped CI [0.80, 0.91]), when differentiating between normal and impaired cognition, compared to an AUC of 0.78 [0.72, 0.84] for MMSE-2 (= 0.21).
Digital screening tests such as M-CogScore are desirable to aid in rapid and remote clinical cognitive evaluations. M-CogScore was significantly correlated with established cognitive tests, including CDR and MMSE-2. M-CogScore can be taken remotely without supervision, is automatically scored, has less of a ceiling effect than the MMSE-2, and takes significantly less time to complete.
临床痴呆评定量表（CDR）和简易精神状态检查表（MMSE）是用于轻度认知障碍（MCI）的有用筛查工具。然而，这些测试需要有资质的人员现场监督，并且CDR可能需要长达60分钟才能完成。我们开发了一种数字认知筛查测试（M-CogScore），它可以在无人监督的情况下于5分钟内远程完成。我们着手在与CDR和MMSE的直接比较中验证M-CogScore。
为确定M-CogScore的有效性，我们招募了年龄、性别和教育程度相匹配的健康对照者或认知受损参与者。参与者完成了30项纸质版MMSE第二版标准版（MMSE-2）、纸质版CDR以及基于智能手机的M-CogScore测试。数字M-CogScore测试基于对智能手机适配的斯特鲁普测试（M-斯特鲁普）、数字符号测试（M-符号）和延迟回忆测试（M-记忆）的时间标准化分数。我们使用斯皮尔曼相关系数来确定M-CogScore与30项MMSE-2之间的收敛效度，并使用非参数检验来确定其与CDR标签为正常（CDR 0）或认知受损（CDR 0.5或1）的判别效度。使用受试者工作特征曲线下面积（AUC）及相应的最佳临界值，将M-CogScore与MMSE-2进一步进行比较。
72名参与者完成了所有三项测试。M-CogScore与MMSE-2（rho = 0.54，< 0.0001）以及CDR上的认知受损情况均相关（曼-惠特尼U = 187，< 0.001）。在区分正常和受损认知时，M-CogScore的AUC为0.85（95%自抽样置信区间[0.80, 0.91]），而MMSE-2的AUC为0.78 [0.72, 0.84]（P = 0.21）。
像M-CogScore这样的数字筛查测试有助于快速和远程的临床认知评估。M-CogScore与既定的认知测试（包括CDR和MMSE-2）显著相关。M-CogScore可以在无人监督的情况下远程进行，自动评分，比MMSE-2的天花板效应更小，并且完成时间显著更短。
