4.6 Article

Cognitive and behavioral abnormalities in individuals with Alzheimer's disease, mild cognitive impairment, and subjective memory complaints

Journal

CURRENT PSYCHOLOGY
Volume -, Issue -, Pages -

Publisher

SPRINGER
DOI: 10.1007/s12144-023-04281-1

Keywords

Alzheimer's disease (AD); Mild cognitive impairment (MCI); Subjective memory complaints (SMC); Episodic memory

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This study investigated the ability of commonly used neuropsychological tests to detect cognitive and functional decline in Alzheimer's disease (AD). The results showed that ADAS-13, RAVLT (learning), FAQ, ECog, and MoCA were predictive of the AD progression continuum, while TMT-B and RAVLT (immediate and forgetting) were not significant predictors. The study suggests using ECog (both versions), RAVLT (learning), ADAS-13, and MoCA to screen all stages of the AD continuum.
In this study, we investigated the ability of commonly used neuropsychological tests to detect cognitive and functional decline across the Alzheimer's disease (AD) continuum. Moreover, as preclinical AD is a key area of investigation, we focused on the ability of neuropsychological tests to distinguish the early stages of the disease, such as individuals with Subjective Memory Complaints (SMC). This study included 595 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset who were cognitively normal (CN), SMC, mild cognitive impairment (MCI; early or late stage), or AD. Our cognitive measures included the Rey Auditory Verbal Learning Test (RAVLT), the Everyday Cognition Questionnaire (ECog), the Functional Abilities Questionnaire (FAQ), the Alzheimer's Disease Assessment Scale-Cognitive Subscale (ADAS-Cog), the Montreal Cognitive Assessment scale (MoCA), and the Trail Making test (TMT-B). Overall, our results indicated that the ADAS-13, RAVLT (learning), FAQ, ECog, and MoCA were all predictive of the AD progression continuum. However, TMT-B and the RAVLT (immediate and forgetting) were not significant predictors of the AD continuum. Indeed, contrary to our expectations ECog self-report (partner and patient) were the two strongest predictors in the model to detect the progression from CN to AD. Accordingly, we suggest using the ECog (both versions), RAVLT (learning), ADAS-13, and the MoCA to screen all stages of the AD continuum. In conclusion, we infer that these tests could help clinicians effectively detect the early stages of the disease (e.g., SMC) and distinguish the different stages of AD.

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