Digital Cognitive Biomarker for Mild Cognitive Impairments and Dementia: A Systematic Review

Ding, Zihan; Lee, Tsz-lok; Chan, Agnes S.

doi:10.3390/jcm11144191

Cited by 22 publications

(16 citation statements)

References 110 publications

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“…This might as well be regarded as a strength, as it mirrors the current diagnostic pathway. Nevertheless, recent biomarker-based studies reported similar results when using the PACC composite score [36, 2]. Third, traditional paper-and-pencil tests were not administered in patients with MCI.…”

Section: Discussionmentioning

confidence: 99%

Clinical Validity of IntelliSpace Cognition Digital Assessment Platform in Mild Cognitive Impairment

Huijbers

Elswijk

Spaltman

et al. 2023

Preprint

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We evaluated a digital cognitive assessment platform, Philips IntelliSpace Cognition, in a cross-sectional cohort of patients diagnosed with mild cognitive impairment (MCI). Performance on individual neuropsychological tests, cognitive domain scores, and Alzheimer’s disease (AD) specific composite scores in MCI were compared with a cohort of cognitively normal adults (CN). The cohorts were matched for age, sex, and education. The performance on all but two neuropsychological tests was worse in the MCI group. After ranking the cognitive domains by effect size, we found that the memory domain was most impaired, followed by executive functioning. The Early AD/MCI Alzheimer’s Cognitive Composite (EMACC) and Preclinical Alzheimer’s Cognitive Composite (PACC) scores were constructed from the digital tests on Philips IntelliSpace Cognition. Both AD-specific composite scores showed greater sensitivity and specificity than the Mini-Mental State Examination, as well as individual neuropsychological tests and individual cognitive domain scores. Together, these results demonstrate the diagnostic value of Philips IntelliSpace Cognition in patients with MCI.

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Section: Discussionmentioning

confidence: 99%

Clinical Validity of IntelliSpace Cognition Digital Assessment Platform in Mild Cognitive Impairment

Huijbers

Elswijk

Spaltman

et al. 2023

Preprint

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“…As well as what was noted by Ye et al [ 19 ] that computer-based tests help in the early diagnosis of MCI. As previously mentioned, for a correct detection of MCI it is important to analyze the cognitive areas of memory, executive functions [ 23 , 24 ], calculation and orientation [ 24 ]. That is why the NNCT test performs an analysis of each of these areas.…”

Section: Discussionmentioning

confidence: 99%

“…On the other hand, the DCS tool correctly discriminates patients with dementia but its ability to differentiate those with MCI from cognitively healthy older adults is not as good [ 22 ]. In terms of cognitive areas that are assessed as digital cognitive biomarkers, tests that analyze memory and executive functions are the most sensitive and promising for the detection of MCI and dementia [ 23 ]. However, other studies show that MCI manifests itself primarily in the cognitive areas of memory, executive functions, calculation, and orientation [ 24 ].…”

Section: Introductionmentioning

confidence: 99%

Validation of the Computerized Cognitive Assessment Test: NNCT

Oliva¹,

Losa²

2022

IJERPH

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Population aging brings with it cognitive impairment. One of the challenges of the coming years is the early and accessible detection of cognitive impairment. Therefore, this study aims to validate a neuropsychological screening test, self-administered and in software format, called NAIHA Neuro Cognitive Test (NNCT), designed for elderly people with and without cognitive impairment. This test aims to digitize cognitive assessments to add greater accessibility than classic tests, as well as to present results in real time and reduce costs. To this end, a comparison is made with tests such as MMSE, Clock Drawing Test (CDT) and CAMCOG. For this purpose, the following statistical analyses were performed: correlations, ROC curves, and three ANOVAs. The NNCT test evaluates seven cognitive areas and shows a significant and positive correlation with other tests, at total and subareas levels. Scores are established for the detection of both mild cognitive impairment and dementia, presenting optimal sensitivity and specificity. It is concluded that the NNCT test is a valid method of detection of cognitive impairment.

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“…Recent developments in blood testing for Aβ and pTau levels show promise in overcoming these barriers (Hansson et al, 2023; Barthélemy et al, 2024) enabling them to become useful clinical tools. The early detection of subtle cognitive decline via digital biomarkers is also showing promise (Dagum, 2018; Ding et al, 2022; Macdougall et al, 2024). These non-invasive assessments, which can often be remotely self-administered, could complement blood tests in identifying individuals at future risk of decline, as they may detect different aspects of AD progression.…”

Section: Introductionmentioning

confidence: 99%

Cognitive modeling of the Mnemonic Similarity Task as a digital biomarker for Alzheimer’s Disease

Vanderlip,

Lee,

Stark

2024

Preprint

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AD related pathologies, such as beta-amyloid (Aβ) and phosphorylated tau (pTau), are evident decades before any noticeable decline in memory occurs. Identifying individuals during this asymptomatic phase is crucial for timely intervention. The Mnemonic Similarity Task (MST), a modified recognition memory task, is especially relevant for early AD screening, as it assesses hippocampal integrity, a region affected (both directly and indirectly) early in the progression of the disease. Further, strong inferences on the underlying cognitive mechanisms that support performance on this task can be made using Bayesian cognitive modeling. We assessed whether analyzing MST performance using a cognitive model could detect subtle changes in cognitive function and AD biomarker status prior to overt cognitive decline. We analyzed MST data from >200 individuals (young, cognitively healthy older adults, and individuals with MCI), a subset of which also had existing CSF Aβ and pTau data. Traditional performance scores and cognitive modeling using multinomial processing trees was applied to each participants MST data using Bayesian approach-es. We assessed how well each could predict age group, memory ability, MCI status, Aβ/pTau sta-tus using ROC analyses. Both approaches predicted age group membership equally, but cognitive modeling approaches exceeded traditional metrics in all other comparisons. This work establishes that cognitive modeling of the MST can detect individuals with AD prior to cognitive decline, making it a potentially useful tool for both screening and monitoring older adults during the asymptomatic phase of AD.

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Digital Cognitive Biomarker for Mild Cognitive Impairments and Dementia: A Systematic Review

Cited by 22 publications

References 110 publications

Clinical Validity of IntelliSpace Cognition Digital Assessment Platform in Mild Cognitive Impairment

Clinical Validity of IntelliSpace Cognition Digital Assessment Platform in Mild Cognitive Impairment

Validation of the Computerized Cognitive Assessment Test: NNCT

Cognitive modeling of the Mnemonic Similarity Task as a digital biomarker for Alzheimer’s Disease

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