Tracking Cognitive Trajectories in Mild Cognitive Impairment Using a Machine Learning Technique of Subtype and Stage Inference.

Dementia and neurocognitive disorders Pub Date : 2025-01-01 Epub Date: 2025-01-07 DOI:10.12779/dnd.2025.24.1.44
Hui Jin Ryu, Kyoung Ja Kwon, Yeonsil Moon
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Abstract

Background and purpose: Recognizing cognitive decline patterns in mild cognitive impairment (MCI) is crucial for early screening and preventive interventions. However, studies on the trajectory of individual cognitive functions in MCI are limited. Thus, the purpose of this study was to identify subtypes and stages of cognitive decline in MCI using a machine learning method.

Methods: A total of 944 subjects consisting of those who were cognitively normal and those with MCI were enrolled. Fifteen neuropsychological tasks were used in the analysis. The optimal number of subtypes was determined based on the cross-validation information criterion. Fifteen stages of cognitive trajectory were estimated for each subtype.

Results: The following three subtypes were identified: amnestic-verbal subtype, dysexecutive subtype, and amnestic-visual subtype. Of 723 (76.6%) subjects who had reached stage 1 at least, amnestic-verbal subtype accounted for the most (n=340, 47.0%), followed by dysexecutive subtype (n=253, 35.0%) and amnestic-visual subtype (n=130, 18%). The amnestic-verbal subtype had significantly more males (amnestic-verbal: 41.8%, dysexecutive: 31.2%, and amnestic-visual: 28.5%), younger subjects (amnestic-verbal: 72.01 years, dysexecutive: 74.43 years, and amnestic-visual: 75.06 years), higher educational years (amnestic-verbal: 11.06 years, dysexecutive: 9.53 years, and amnestic-visual: 9.79 years), lower Clinical Dementia Rating sum of boxes (amnestic-verbal: 1.40, dysexecutive: 1.61, and amnestic-visual: 1.71), and lower Korean-Instrumental Activities of Daily Living score (amnestic-verbal: 0.20, dysexecutive: 0.27, and amnestic-visual: 0.26).

Conclusions: Three types of MCIs were extracted using SuStaIn. Pathways of MCI deterioration could be different. The amnestic type could be bisected based on whether episodic verbal or visual memory is degraded first.

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基于亚型和阶段推理的机器学习技术追踪轻度认知障碍患者的认知轨迹。
背景与目的:认识轻度认知障碍(MCI)的认知衰退模式对早期筛查和预防干预至关重要。然而,对轻度认知损伤个体认知功能发展轨迹的研究还很有限。因此,本研究的目的是使用机器学习方法确定MCI认知衰退的亚型和阶段。方法:共944名受试者,包括认知正常和轻度认知障碍患者。分析中使用了15个神经心理学任务。根据交叉验证信息准则确定最佳亚型数。每个亚型的认知轨迹估计有15个阶段。结果:识别出三种亚型:语言遗忘亚型、执行障碍亚型和视觉遗忘亚型。在至少达到第一阶段的723例(76.6%)受试者中,言语遗忘型占最多(340例,47.0%),其次是执行障碍型(253例,35.0%)和视觉遗忘型(130例,18%)。失忆-言语亚型的男性显著多于男性(失忆-言语:41.8%,执行障碍:31.2%,失忆-视觉:28.5%),年轻(失忆-言语:72.01岁,执行障碍:74.43岁,失忆-视觉:75.06岁),高学历(失忆-言语:11.06岁,执行障碍:9.53岁,失忆-视觉:9.79岁),较低的临床痴呆评分(失忆-言语:1.40,执行障碍:1.61,失忆-视觉)。1.71),日常生活韩语工具活动得分较低(失忆-语言:0.20,执行障碍:0.27,失忆-视觉:0.26)。结论:采用SuStaIn提取了3种类型的MCIs。MCI恶化的途径可能不同。遗忘型可以根据情景性言语记忆或视觉记忆是否先退化来划分。
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