期刊
JOURNAL OF ALZHEIMERS DISEASE
卷 66, 期 1, 页码 347-357出版社
IOS PRESS
DOI: 10.3233/JAD-180604
关键词
All-cause dementia; Alzheimer's disease; cognitive aging; cognitive subtypes; heterogeneity; individual differences; neuropsychology
资金
- National Institute On Aging of the National Institutes of Health [K01AG054700]
- Einstein Aging Study from National Institutes on Aging program [PO1 AG03949]
- National Institutes of Health CTSA from the National Center for Advancing Translational Sciences (NCATS) [1UL1TR001073]
- Sylvia and Leonard Marx Foundation
- Czap Foundation
- National Institute on Aging [R01AG17917]
Identifying preclinical Alzheimer's disease (AD) is an important step toward developing approaches to early treatment and dementia prevention. We applied latent class analysis (LCA) to 10 baseline neuropsychological assessments for 1,345 participants from Einstein Aging Study. Time-to-event models for all-cause dementia and AD were run examining events in 4-year intervals. Five classes were identified: Mixed-Domain Impairment (n = 107), Memory-Specific Impairment (n = 457), Average (n = 539), Frontal Impairment (n = 118), and Superior Cognition (n = 124). Compared to the Average class, the Mixed-Domain Impairment and Memory-Specific Impairment classes were at higher risk of incident all-cause dementia and AD in the first 4 years from baseline, while the Frontal Impairment class was associated with higher risk between 4 and 8 years of follow-up. LCA identified classes which differ in cross-sectional cognitive patterns and in risk of dementia over specific follow-up intervals.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据