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A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Characteristics of Cognitive Deficit in Amnestic Mild Cognitive Impairment With Subthreshold Depression
Zhiyu Sun1,2,3,4, Zhijiang Wang2,3,4,5, Lujie Xu1,2,3,4
11 School of Mental Health, Wenzhou Medical University, Wenzhou, China.
Abstract:
It is widely recognized that depression may precipitate the incidence of dementia in the elderly individuals and individuals with amnestic mild cognitive impairment (aMCI) in particular. However, the association between subthreshold depression (SD) and cognitive deficits in patients with aMCI remains unclear. To address this, we collected demographic information and conducted a battery of neuropsychological cognitive assessments in 33 aMCI participants with SD (aMCI/SD+), 33 nondepressed aMCI participants (aMCI/SD-), and 53 normal controls (NC). Both aMCI groups showed significantly poorer performance in most cognitive domains relative to the NC group (ie, memory, language, processing speed, and executive function). Notably, the aMCI/SD+ group showed significantly poorer attention/working memory compared with the aMCI/SD- group. Multiple linear regression analyses revealed a significant negative association between the severity of depressive symptoms and attention/working memory capacity (β = - .024, P = .024), accounting for 8.28% of the variations in this cognitive domain. All statistical analyses were adjusted by age, sex, and years of education. A logistic regression model had an accuracy of 72.4% in discriminating between the aMCI/SD+ and aMCI/SD- groups based on individual cognitive profiles over 6 domains. Our findings indicate that patients with aMCI with and without SD have distinct patterns of cognitive impairment. This finding may facilitate the diagnosis and treatment of SD in patients with aMCI.
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