Giraldo Diana L, Sijbers Jan, Romero Eduardo
Computer Imaging and Medical Applications Laboratory - CIM@LAB Universidad Nacional de Colombia Bogotá Colombia.
imec-Visionlab Department of Physics at University of Antwerp University of Antwerp Antwerp Belgium.
Alzheimers Dement (Amst). 2021 Sep 14;13(1):e12237. doi: 10.1002/dad2.12237. eCollection 2021.
Neuropsychological test scores are limited and standard outcomes may mask the heterogeneity of cognitive impairment. This article presents the calculation and evaluation of six composite scores that quantify domain-specific impairment.
Parameters for composite scores calculation were learned by performing confirmatory factor analysis in a sample of participants from the Alzheimer's Disease Neuroimaging Initiative database. The obtained scores were evaluated with a separate sample of mild cognitive impairment (MCI) in two automated tasks: unsupervised partition in different subgroups and prediction of progression to dementia for different time windows.
MCI subgroups with distinctive cognitive profiles and risk of progression emerged from cluster analysis. Composite scores outperform standard neuropsychological tests when automatically predicting progression within time windows up to 5 years.
Domain-specific composite scores are useful to delineate profiles of impairment, stratify the MCI risk, and predict progression to dementia.
神经心理测试分数存在局限性,标准结果可能掩盖认知障碍的异质性。本文介绍了六个复合分数的计算和评估,这些分数量化了特定领域的损伤。
通过对来自阿尔茨海默病神经影像倡议数据库的参与者样本进行验证性因素分析,学习复合分数计算的参数。在两个自动化任务中,用一个单独的轻度认知障碍(MCI)样本对获得的分数进行评估:在不同亚组中的无监督划分以及不同时间窗口内进展为痴呆症的预测。
聚类分析产生了具有独特认知特征和进展风险的MCI亚组。在自动预测长达5年的时间窗口内的进展时,复合分数优于标准神经心理测试。
特定领域的复合分数有助于描绘损伤概况、分层MCI风险以及预测进展为痴呆症。