Fast Declining Prediction in Alzheimer's Disease from Early Clinical Assessment.

IF 4.8 2区 医学 Q1 NEUROSCIENCES
Lourdes Álvarez-Sánchez, Mar Peretó, Lorena García-Vallés, Ángel Balaguer, Carmen Peña-Bautista, Laura Ferré-González, Miguel Baquero, Consuelo Cháfer Pericás
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引用次数: 0

Abstract

Intoduction: The heterogenicity in Alzheimer's Disease (AD) progression hinders individual prognosis. The present work is an observational 2-year longitudinal study in patients with mild cognitive impairment due to AD (n= 52, with positive CSF biomarkers). The aim of this study is to predict which patients are at risk of fast progression. For this, 3 neuropsychological tests based on different domains (clinical dementia, cognition, delayed memory) and the sum of them were used.

Method: The tests were performed at diagnosis time (T1) and two years after the diagnosis time (T2). Then, the corresponding progression models were developed using each individual test and their sum as a variable response.

Results: As a result, the model based on cognition status to predict fast decline (differences in the Z score (T2-T1) <1.5 were considered fast declining) provided satisfactory performance (AUC 0.74, 83.3% of sensibility and 70.2% of specificity); the models based on clinical dementia and delayed memory to predict fast declining showed low AUC and sensitivity. Nevertheless, the model based on the sum of the 3 tests showed the highest AUC (0.79), low sensitivity (63.6%), and high specificity.

Conclusion: The developed progression models could provide useful information to clinicians and AD patients regarding their fast/normal decline in general or specific domains.

通过早期临床评估快速预测阿尔茨海默病的恶化
引言:阿尔茨海默病(AD)进展的异质性阻碍了个体预后。本研究是一项为期 2 年的纵向观察性研究,研究对象是因阿尔茨海默病(AD)导致轻度认知障碍的患者(52 人,脑脊液生物标志物呈阳性)。这项研究的目的是预测哪些患者有快速进展的风险。为此,采用了基于不同领域(临床痴呆、认知、延迟记忆)的 3 项神经心理测试及其总和:方法:在诊断时(T1)和诊断后两年(T2)进行测试。方法:分别在确诊时(T1)和确诊后两年(T2)进行测试,然后将每项测试及其总和作为变量响应,建立相应的进展模型:结果:基于认知状况的模型可以预测快速衰退(Z 评分(T2-T1)的差异):所建立的进展模型可为临床医生和AD患者提供有用信息,帮助他们了解自己在一般或特定领域的快速/正常衰退情况。
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来源期刊
Current Neuropharmacology
Current Neuropharmacology 医学-神经科学
CiteScore
8.70
自引率
1.90%
发文量
369
审稿时长
>12 weeks
期刊介绍: Current Neuropharmacology aims to provide current, comprehensive/mini reviews and guest edited issues of all areas of neuropharmacology and related matters of neuroscience. The reviews cover the fields of molecular, cellular, and systems/behavioural aspects of neuropharmacology and neuroscience. The journal serves as a comprehensive, multidisciplinary expert forum for neuropharmacologists and neuroscientists.
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