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验证埃尔朗根评分算法在尸检证实的痴呆症患者中的鉴别诊断价值。

Validation of the Erlangen Score Algorithm for Differential Dementia Diagnosis in Autopsy-Confirmed Subjects.

机构信息

Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium.

Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany.

出版信息

J Alzheimers Dis. 2019;68(3):1151-1159. doi: 10.3233/JAD-180563.

Abstract

BACKGROUND

Despite decades of research on the optimization of the diagnosis of Alzheimer's disease (AD), its biomarker-based diagnosis is being hampered by the lack of comparability of raw biomarker data. In order to overcome this limitation, the Erlangen Score (ES), among other approaches, was set up as a diagnostic-relevant interpretation algorithm.

OBJECTIVE

To validate the ES algorithm in a cohort of neuropathologically confirmed cases with AD (n = 106) and non-AD dementia (n = 57).

METHODS

Cerebrospinal fluid (CSF) biomarker concentrations of Aβ1-42, T-tau, and P-tau181 were measured with commercially available single analyte ELISA kits. Based on these biomarkers, ES was calculated as previously reported.

RESULTS

This algorithm proved to categorize AD in different degrees of likelihood, ranging from neurochemically "normal", "improbably having AD", "possibly having AD", to "probably having AD", with a diagnostic accuracy of 74% using the neuropathology as a reference.

CONCLUSION

The ability of the ES to overcome the high variability of raw CSF biomarker data may provide a useful diagnostic tool for comparing neurochemical diagnoses between different labs or methods used.

摘要

背景

尽管数十年来一直在研究阿尔茨海默病(AD)的诊断优化,但由于原始生物标志物数据缺乏可比性,其基于生物标志物的诊断仍受到阻碍。为了克服这一限制,除其他方法外,还建立了 Erlangen 评分(ES)作为与诊断相关的解释算法。

目的

在一组经神经病理学证实的 AD(n=106)和非 AD 痴呆(n=57)病例中验证 ES 算法。

方法

使用市售的单分析物 ELISA 试剂盒测量脑脊液(CSF)中 Aβ1-42、T-tau 和 P-tau181 的生物标志物浓度。根据这些生物标志物,如先前报道的那样计算 ES。

结果

该算法证明可以对 AD 进行不同程度的分类,从神经化学上的“正常”、“不太可能患有 AD”、“可能患有 AD”到“很可能患有 AD”,使用神经病理学作为参考的诊断准确性为 74%。

结论

ES 克服原始 CSF 生物标志物数据高度变异性的能力,可为比较不同实验室或方法之间的神经化学诊断提供有用的诊断工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e10/6484252/ff0f4fcd8c26/jad-68-jad180563-g001.jpg

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