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路易体痴呆中阿尔茨海默病共病的自然语言标志物。

Natural speech markers of Alzheimer's disease co-pathology in Lewy body dementias.

机构信息

Penn Frontotemporal Degeneration Center and Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.

Linguistic Data Consortium, University of Pennsylvania, Philadelphia, PA, USA.

出版信息

Parkinsonism Relat Disord. 2022 Sep;102:94-100. doi: 10.1016/j.parkreldis.2022.07.023. Epub 2022 Aug 6.

Abstract

INTRODUCTION

An estimated 50% of patients with Lewy body dementias (LBD), including Parkinson's disease dementia (PDD) and Dementia with Lewy bodies (DLB), have co-occurring Alzheimer's disease (AD) that is associated with worse prognosis. This study tests an automated analysis of natural speech as an inexpensive, non-invasive screening tool for AD co-pathology in biologically-confirmed cohorts of LBD patients with AD co-pathology (SYN + AD) and without (SYN-AD).

METHODS

We analyzed lexical-semantic and acoustic features of picture descriptions using automated methods in 22 SYN + AD and 38 SYN-AD patients stratified using AD CSF biomarkers or autopsy diagnosis. Speech markers of AD co-pathology were identified using best subset regression, and their diagnostic discrimination was tested using receiver operating characteristic. ANCOVAs compared measures between groups covarying for demographic differences and cognitive disease severity. We tested relations with CSF tau levels, and compared speech measures between PDD and DLB clinical disorders in the same cohort.

RESULTS

Age of acquisition of nouns (p = 0.034, |d| = 0.77) and lexical density (p = 0.0064, |d| = 0.72) were reduced in SYN + AD, and together showed excellent discrimination for SYN + AD vs. SYN-AD (95% sensitivity, 66% specificity; AUC = 0.82). Lower lexical density was related to higher CSF t-Tau levels (R = -0.41, p = 0.0021). Clinically-diagnosed PDD vs. DLB did not differ on any speech features.

CONCLUSION

AD co-pathology may result in a deviant natural speech profile in LBD characterized by specific lexical-semantic impairments, not detectable by clinical disorder diagnosis. Our study demonstrates the potential of automated digital speech analytics as a screening tool for underlying AD co-pathology in LBD.

摘要

简介

据估计,50%的路易体痴呆症(LBD)患者,包括帕金森病痴呆症(PDD)和路易体痴呆症(DLB),存在同时发生的阿尔茨海默病(AD),这与预后更差相关。本研究测试了一种自动化分析自然语言的方法,作为一种廉价、非侵入性的筛查工具,用于生物证实的 LBD 患者中存在 AD 共病(SYN+AD)和不存在 AD 共病(SYN-AD)的队列。

方法

我们使用自动化方法分析了 22 名 SYN+AD 和 38 名 SYN-AD 患者的图片描述的词汇语义和声学特征,这些患者根据 AD 脑脊液生物标志物或尸检诊断进行分层。使用最佳子集回归识别 AD 共病的言语标志物,并使用接受者操作特征测试其诊断鉴别力。ANCOVAs 比较了组间差异的指标,这些差异包括人口统计学差异和认知疾病严重程度。我们测试了与 CSF tau 水平的关系,并在同一队列中比较了 PDD 和 DLB 临床障碍的言语测量。

结果

名词的习得年龄(p=0.034,|d|=0.77)和词汇密度(p=0.0064,|d|=0.72)在 SYN+AD 中降低,两者结合起来对 SYN+AD 与 SYN-AD 的区分具有出色的效果(95%的敏感性,66%的特异性;AUC=0.82)。较低的词汇密度与较高的 CSF t-Tau 水平相关(R=-0.41,p=0.0021)。临床上诊断的 PDD 与 DLB 在任何言语特征上均无差异。

结论

AD 共病可能导致 LBD 中的自然言语谱异常,其特征是特定的词汇语义障碍,不能通过临床障碍诊断检测到。我们的研究表明,自动数字语音分析具有作为 LBD 中潜在 AD 共病的筛查工具的潜力。

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Natural speech markers of Alzheimer's disease co-pathology in Lewy body dementias.路易体痴呆中阿尔茨海默病共病的自然语言标志物。
Parkinsonism Relat Disord. 2022 Sep;102:94-100. doi: 10.1016/j.parkreldis.2022.07.023. Epub 2022 Aug 6.

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