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Updated: Nov 2, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
Published on: January 11, 2020
Subtle cognitive impairment as a marker of Alzheimer's pathologies and clinical progression in cognitively normal
Xue-Ning Shen1, Kevin Kuo1, Yu-Xiang Yang1
1Department of Neurology and Institute of Neurology Huashan Hospital, Shanghai Medical College Fudan University Shanghai China.
Introduction:
Subtle cognitive impairment (SCI) may appear before pathological changes surpass thresholds for abnormality. We aimed to investigate whether SCI could predict Alzheimer's pathologies and advancement.
Methods:
A total of 816 cognitively normal individuals were enrolled to assess the longitudinal neuropathological and clinical correlates of baseline SCI, via linear mixed-effects and Cox proportional-hazard models. Cross-lagged panel models were used in specific time waves.
Results:
SCI individuals had a faster increase in brain amyloid burden and a higher risk of conversion. They also showed greater rates of cerebrospinal fluid (CSF) phosphorylated tau (p-tau)181 increase and glucose metabolism decrease. In addition, baseline SCI predicted worse clinical progression, whereas multi-domain SCI advanced faster compared to the single domain group.
Discussion:
Baseline SCI could be an imperative prediction indicator of clinical and pathological progression. It enables cognitive measures to be informative at a very early stage and provided objective criteria for high-risk population screening.
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