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使用轻度认知障碍和阿尔茨海默病患者群组的潜在曲线模型进行的纵向研究。

A longitudinal study using latent curve models of groups with mild cognitive impairment and Alzheimer's disease.

机构信息

MARCS Institute for Brain and Behaviour & School of Psychology, Western Sydney University, Sydney, New South Wales, Australia; Department of Human Anatomy and Physiology, the Faculty of Health Sciences, University of Johannesburg, South Africa.

School of Psychology, Charles Stuart University, Port Macquarie, NSW, Australia.

出版信息

J Neurosci Methods. 2021 Feb 15;350:109040. doi: 10.1016/j.jneumeth.2020.109040. Epub 2020 Dec 17.

Abstract

BACKGROUND

This study explores how mild cognitive impairment (MCI) and Alzheimer's disease (AD) develop over time. NEW METHOD: this study involves a new application of latent curve models (LCM) to examine the development trajectory of a healthy, MCI, and AD groups on a series of clinical and neural measures. Multiple-group latent curve models were used to compare the parameters of the trajectories across groups.

RESULTS

LCM results showed that a linear functional form of growth was adequate for all the clinical and neural measures. Positive and significant differences in initial levels were seen across groups on all of the clinical and neural measures. In all groups, the following measures increased slightly, or considerably, over time: Clinical Dementia Rating, Alzheimer's disease Cognitive Assessment, and Montreal Assessment Test for Dementia. In contrast, a slight or a greatly decreasing trajectory was observed on the following measures: Fluorodeoxyglucose, Mini-Mental State Exam, Rey Auditory Verbal Learning Test as well as Hippocampus, Fusiform and Entorhinal Cortex volume measures. However, a constant mean trajectory was seen on Cognition Self Report Memory and languages scores. COMPARISION WITH EXISTING METHODS: there are no prior studies that applied LCM on large AD datasets.

CONCLUSIONS

cognitive decline occurs in the cognitively normal (CN), MCI, and AD groups but at different rates. Further, some important cognitive, neural, and clinical variables that (a) best differentiate between CN, MCI, and AD as well as (b) differentially change over time in MCI and AD, which may explain disease progression.

摘要

背景

本研究探讨了轻度认知障碍(MCI)和阿尔茨海默病(AD)随时间的发展过程。

新方法

本研究应用潜在曲线模型(LCM)来检查一系列临床和神经测量指标下健康、MCI 和 AD 组的发展轨迹,这是一种新的应用。使用多组潜在曲线模型来比较各组轨迹的参数。

结果

LCM 结果表明,所有临床和神经测量指标的增长均采用线性函数形式。所有临床和神经测量指标上,各组的初始水平均呈现出积极且显著的差异。在所有组中,以下指标随时间略有增加或显著增加:临床痴呆评定量表、阿尔茨海默病认知评估量表和蒙特利尔认知评估量表。相比之下,以下指标的轨迹呈轻微或大幅下降趋势:氟脱氧葡萄糖、简易精神状态检查、瑞文听觉言语学习测试以及海马体、梭状回和内嗅皮质体积测量。然而,认知自我报告记忆和语言评分呈恒定均值轨迹。

与现有方法的比较

没有先前研究应用 LCM 对大型 AD 数据集进行分析。

结论

认知正常(CN)、MCI 和 AD 组均存在认知衰退,但衰退速度不同。此外,一些重要的认知、神经和临床变量,(a)能最好地区分 CN、MCI 和 AD,以及(b)在 MCI 和 AD 中随时间发生差异变化,这可能解释了疾病的进展。

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