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阿尔茨海默病还是行为变异额颞叶痴呆?临床和神经心理学诊断准确性相关要点综述。

Alzheimer's Disease or Behavioral Variant Frontotemporal Dementia? Review of Key Points Toward an Accurate Clinical and Neuropsychological Diagnosis.

机构信息

Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Department of Physiopathology, ICBM, Department of Neurosciences, Department of East Neuroscience, Faculty of Medicine, University of Chile, Providencia, Santiago, Chile.

Universidad de los Andes, Santiago, Chile.

出版信息

J Alzheimers Dis. 2020;73(3):833-848. doi: 10.3233/JAD-190924.

DOI:10.3233/JAD-190924
PMID:31884475
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7012749/
Abstract

Alzheimer's disease (AD) and frontotemporal dementia (FTD) are the most common neurodegenerative early-onset dementias. Despite the fact that both conditions have a very distinctive clinical pattern, they present with an overlap in their cognitive and behavioral features that may lead to misdiagnosis or delay in diagnosis. The current review intends to summarize briefly the main differences at the clinical, neuropsychological, and behavioral levels, in an attempt to suggest which aspects would facilitate an adequate diagnosis in a clinical setting, especially in Latin American and low- and middle-income countries, where the resources needed for a differential diagnosis (such as MRI or biomarkers) are not always available. A timely diagnosis of AD and FTD have significant implications for the medical management and quality of life of patients and careers.

摘要

阿尔茨海默病(AD)和额颞叶痴呆(FTD)是最常见的神经退行性早发性痴呆。尽管这两种疾病的临床特征非常明显,但它们在认知和行为特征上存在重叠,可能导致误诊或诊断延迟。目前的综述旨在简要总结临床、神经心理学和行为层面的主要差异,试图提出哪些方面有助于在临床环境中进行充分诊断,特别是在拉丁美洲和低收入及中等收入国家,这些国家并不总是具备进行鉴别诊断所需的资源(如 MRI 或生物标志物)。及时诊断 AD 和 FTD 对患者的医疗管理和生活质量以及职业发展都有重要影响。

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Survival and life-expectancy in a young-onset dementia cohort with six years of follow-up: the NeedYD-study.在一项随访时间长达六年的早发性痴呆队列中,生存和预期寿命:NeedyD 研究。
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Family caregivers experiences of the pre-diagnostic stage in frontotemporal dementia.
海林测试和布里克斯顿测试在中老年成年人中检测痴呆、进行性认知衰退及轻度认知障碍的有效性:一项系统评价与荟萃分析
Neuropsychol Rev. 2025 Apr 17. doi: 10.1007/s11065-025-09658-6.
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Deep learning-based classification of dementia using image representation of subcortical signals.基于深度学习的痴呆症分类:利用皮质下信号的图像表征
BMC Med Inform Decis Mak. 2025 Mar 6;25(1):113. doi: 10.1186/s12911-025-02924-w.
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Boostering diagnosis of frontotemporal lobar degeneration with AI-driven neuroimaging - A systematic review and meta-analysis.人工智能驱动的神经影像学在额颞叶变性诊断中的增强作用——一项系统评价和荟萃分析
Neuroimage Clin. 2025;45:103757. doi: 10.1016/j.nicl.2025.103757. Epub 2025 Feb 17.
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家庭照顾者在额颞叶痴呆前诊断阶段的体验。
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