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计算机辅助预测阿尔茨海默病早期阶段的临床进展。

Computer-assisted prediction of clinical progression in the earliest stages of AD.

作者信息

Rhodius-Meester Hanneke F M, Liedes Hilkka, Koikkalainen Juha, Wolfsgruber Steffen, Coll-Padros Nina, Kornhuber Johannes, Peters Oliver, Jessen Frank, Kleineidam Luca, Molinuevo José Luis, Rami Lorena, Teunissen Charlotte E, Barkhof Frederik, Sikkes Sietske A M, Wesselman Linda M P, Slot Rosalinde E R, Verfaillie Sander C J, Scheltens Philip, Tijms Betty M, Lötjönen Jyrki, van der Flier Wiesje M

机构信息

Alzheimer Center, Department of Neurology, VU University Medical Centre, Amsterdam Neuroscience, Amsterdam, the Netherlands.

VTT Technical Research Centre of Finland Ltd., Tampere, Finland.

出版信息

Alzheimers Dement (Amst). 2018 Oct 8;10:726-736. doi: 10.1016/j.dadm.2018.09.001. eCollection 2018.

Abstract

INTRODUCTION

Individuals with subjective cognitive decline (SCD) are at increased risk for clinical progression. We studied how combining different diagnostic tests can help to identify individuals who are likely to show clinical progression.

METHODS

We included 674 patients with SCD (46% female, 64 ± 9 years, Mini-Mental State Examination 28 ± 2) from three memory clinic cohorts. A multivariate model based on the Disease State Index classifier incorporated the available baseline tests to predict progression to MCI or dementia over time. We developed and internally validated the model in one cohort and externally validated it in the other cohorts.

RESULTS

After 2.9 ± 2.0 years, 151(22%) patients showed clinical progression. Overall performance of the classifier when combining cognitive tests, magnetic resonance imagining, and cerebrospinal fluid showed a balanced accuracy of 74.0 ± 5.5, with high negative predictive value (93.3 ± 2.8).

DISCUSSION

We found that a combination of diagnostic tests helps to identify individuals at risk of progression. The classifier had particularly good accuracy in identifying patients who remained stable.

摘要

引言

主观认知下降(SCD)个体临床进展风险增加。我们研究了联合不同诊断测试如何有助于识别可能出现临床进展的个体。

方法

我们纳入了来自三个记忆门诊队列的674例SCD患者(46%为女性,64±9岁,简易精神状态检查表评分为28±2)。基于疾病状态指数分类器的多变量模型纳入可用的基线测试,以预测随时间发展为轻度认知障碍(MCI)或痴呆的情况。我们在一个队列中开发并内部验证了该模型,并在其他队列中进行了外部验证。

结果

经过2.9±2.0年,151例(22%)患者出现临床进展。联合认知测试、磁共振成像和脑脊液时,分类器的总体表现显示平衡准确率为74.0±5.5,阴性预测值较高(93.3±2.8)。

讨论

我们发现联合诊断测试有助于识别有进展风险的个体。该分类器在识别保持稳定的患者方面具有特别好 的准确性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/36b7/6310913/4647325fa0af/gr1.jpg

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