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老年言语变化:基于言语的健康衰老与阿尔茨海默病鉴别方法学的考虑。

Speech changes in old age: Methodological considerations for speech-based discrimination of healthy ageing and Alzheimer's disease.

机构信息

Spanish Language Department, Faculty of Philology, University of Salamanca, Salamanca, Spain.

Institute of Neuroscience of Castilla y León, Salamanca, Spain.

出版信息

Int J Lang Commun Disord. 2024 Jan-Feb;59(1):13-37. doi: 10.1111/1460-6984.12888. Epub 2023 May 4.

Abstract

BACKGROUND

Recent evidence suggests that speech substantially changes in ageing. As a complex neurophysiological process, it can accurately reflect changes in the motor and cognitive systems underpinning human speech. Since healthy ageing is not always easily discriminable from early stages of dementia based on cognitive and behavioural hallmarks, speech is explored as a preclinical biomarker of pathological itineraries in old age. A greater and more specific impairment of neuromuscular activation, as well as  a specific cognitive and linguistic impairment in dementia, unchain discriminating changes in speech. Yet, there is no consensus on such discriminatory speech parameters, neither on how they should be elicited and assessed.

AIMS

To provide a state-of-the-art on speech parameters that allow for early discrimination between healthy and pathological ageing; the aetiology of these parameters; the effect of the type of experimental stimuli on speech elicitation and the predictive power of different speech parameters; and the most promising methods for speech analysis and their clinical implications.

METHODS & PROCEDURES: A scoping review methodology is used in accordance with the PRISMA model. Following a systematic search of PubMed, PsycINFO and CINAHL, 24 studies are included and analysed in the review.

MAIN CONTRIBUTION

The results of this review yield three key questions for the clinical assessment of speech in ageing. First, acoustic and temporal parameters are more sensitive to changes in pathological ageing and, of these two, temporal variables are more affected by cognitive impairment. Second, different types of stimuli can trigger speech parameters with different degree of accuracy for the discrimination of clinical groups. Tasks with higher cognitive load are more precise in eliciting higher levels of accuracy. Finally, automatic speech analysis for the discrimination of healthy and pathological ageing should be improved for both research and clinical practice.

CONCLUSIONS & IMPLICATIONS: Speech analysis is a promising non-invasive tool for the preclinical screening of healthy and pathological ageing. The main current challenges of speech analysis in ageing are the automatization of its clinical assessment and the consideration of the speaker's cognitive background during evaluation.

WHAT THIS PAPER ADDS

What is already known on the subject Societal aging  goes hand in hand with the rising incidence of ageing-related neurodegenerations, mainly Alzheimer's disease (AD). This is particularly noteworthy in countries with longer life expectancies. Healthy ageing and early stages of AD share a set of cognitive and behavioural characteristics. Since there is no cure for dementias, developing methods for accurate discrimination of healthy ageing and early AD is currently a priority. Speech has been described as one of the most significantly impaired features in AD. Neuropathological alterations in motor and cognitive systems would underlie specific speech impairment in dementia. Since speech can be evaluated quickly, non-invasively and inexpensively, its value for the clinical assessment of ageing itineraries may be particularly high. What this paper adds to existing knowledge Theoretical and experimental advances in the assessment of speech as a marker of AD have developed rapidly over the last decade. Yet, they are not always known to clinicians. Furthermore, there is a need to provide an updated state-of-the-art on which speech features are discriminatory to AD, how they can be assessed, what kind of results they can yield, and how such results should be interpreted. This article provides an updated overview of speech profiling, methods of speech measurement and analysis, and the clinical power of speech assessment for early discrimination of AD as the most common cause of dementia. What are the potential or actual clinical implications of this work? This article provides an overview of the predictive potential of different speech parameters in relation to AD cognitive impairment. In addition, it discusses the effect that the cognitive state, the type of elicitation task and the type of assessment method may have on the results of the speech-based analysis in ageing.

摘要

背景

最近的证据表明,言语在衰老过程中会发生实质性的变化。作为一个复杂的神经生理过程,它可以准确地反映人类言语所依赖的运动和认知系统的变化。由于基于认知和行为特征的健康衰老并不总是容易与痴呆的早期阶段区分开来,因此探索言语作为老年期病理性轨迹的临床前生物标志物。由于在痴呆症中,神经肌肉激活的更大和更特定的损伤以及特定的认知和语言损伤,因此可以区分言语的变化。然而,对于这些具有区分性的言语参数,无论是如何引出和评估的,目前还没有达成共识。

目的

提供有关允许在健康和病理性衰老之间进行早期区分的言语参数的最新信息;这些参数的病因;不同实验刺激类型对言语引出的影响以及不同言语参数的预测能力;以及最有前途的言语分析方法及其临床意义。

方法与程序

根据 PRISMA 模型采用范围综述方法。在对 PubMed、PsycINFO 和 CINAHL 进行系统搜索后,纳入了 24 项研究并进行了综述分析。

主要贡献

该综述的结果为衰老过程中言语临床评估提出了三个关键问题。首先,声学和时间参数对病理性衰老的变化更为敏感,而在这两个参数中,时间变量受认知障碍的影响更大。其次,不同类型的刺激可以触发具有不同准确性的言语参数,以区分临床群体。认知负荷较高的任务更能准确地引出更高水平的准确性。最后,为了研究和临床实践,应该改进用于健康和病理性衰老区分的自动言语分析。

结论和意义

言语分析是一种有前途的非侵入性工具,可用于健康和病理性衰老的临床前筛查。目前,言语分析在衰老中的主要挑战是其临床评估的自动化以及在评估过程中考虑说话者的认知背景。

本文的新增内容

  • 主题已知内容:随着与衰老相关的神经退行性疾病(主要是阿尔茨海默病)发病率的上升,社会老龄化也随之而来。在预期寿命较长的国家,这一点尤其值得关注。健康衰老和 AD 的早期阶段有一系列认知和行为特征。由于目前尚无针对痴呆症的治愈方法,因此目前的重点是开发准确区分健康衰老和早期 AD 的方法。言语已被描述为 AD 中受损最严重的特征之一。运动和认知系统的神经病理学改变将是痴呆症中特定言语障碍的基础。由于言语可以快速、非侵入性和廉价地评估,因此其在评估衰老轨迹方面的临床价值可能特别高。

  • 本文新增知识:AD 作为 AD 标志物的评估的理论和实验进展在过去十年中迅速发展。然而,临床医生并不总是了解这些进展。此外,需要提供有关 AD 中哪些言语特征具有区分性、如何评估它们、它们可以产生什么样的结果以及如何解释这些结果的最新概述。本文提供了 AD 中言语分析、方法的最新概述,以及言语评估在 AD 早期识别中的临床潜力。

可能或实际的临床意义是什么?本文提供了不同言语参数与 AD 认知障碍的预测潜力的概述。此外,它还讨论了认知状态、引出任务的类型和评估方法的类型可能对基于言语的衰老分析结果产生的影响。

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