Separation of cognitive domains to improve prediction of progression from mild cognitive impairment to Alzheimer's disease

被引：4

作者：

Hendrix, Suzanne B. ^{[1
]}

Welsh-Bohmer, Kathleen A. ^{[2
]}

机构：

[1] Pentara Corp, Salt Lake City, UT 84109 USA

[2] Duke Univ, Joseph & Kathleen Bryan Alzheimers Dis Res Ctr Br, Durham, NC 27705 USA

来源：

ALZHEIMERS RESEARCH & THERAPY | 2013年 / 5卷 / 03期

关键词：

Mild Cognitive Impairment; Cognitive Domain; Mild Cognitive Impairment Subject; Early Population; Bayesian Statistical Model;

D O I：

10.1186/alzrt176

中图分类号：

R74 [神经病学与精神病学];

学科分类号：

摘要：

Addressing causes of heterogeneity in cognitive outcomes is becoming more critical as Alzheimer's disease (AD) research focuses on earlier disease. One of the causes of this heterogeneity may be that individuals with deficiencies in different cognitive domains may perform similarly on a neuropsychological (NP) test for very different reasons. Tatsuoka and colleagues have applied a Bayesian model in order to integrate knowledge about cognitive domains relevant to each NP test with the observed outcomes from the Alzheimer's Disease Neuroimaging Initiative (ADNI) mild cognitive impairment data. This approach resulted in better prediction of AD diagnosis than more traditional approaches.

引用

页数：2