您的账号已在其他设备登录,您当前账号已强迫下线,
如非您本人操作,建议您在会员中心进行密码修改

确定
收藏 | 浏览73

Several cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. However, predictors might be more or less powerful depending on the characteristics of the MCI sample.To investigate which cognitive markers and biomarkers predict conversion to AD dementia and course of cognitive functioning in a MCI sample with a high proportion of early-stage MCI patients.Variables known to predict progression in MCI patients and hypothesized to predict progression in early-stage MCI patients were selected. Cognitive (long-delay free recall, regional primacy score), imaging (hippocampal and entorhinal cortex volumes, fornix fractional anisotropy), and CSF (Aβ1-42/t-tau, Aβ1-42) variables from 36 MCI patients were analyzed with Cox regression and mixed-effect models to determine their individual and combined abilities to predict time to conversion to AD dementia and course of global cognitive functioning, respectively.Those variables hypothesized to predict the course of early-stage MCI patients were most predictive for MCI progression. Specifically, regional primacy score (a measure of word-list position learning) most consistently predicted conversion to AD dementia and course of cognitive functioning. Both the prediction of conversion and course of cognitive functioning were maximized by including CSF Aβ1-42 and fornix integrity biomarkers, respectively, indicating the complementary information carried by cognitive variables and biomarkers.Predictors of MCI progression need to be interpreted in light of the characteristics of the respective MCI sample. Future studies should aim to compare predictive strengths of markers between early-stage and late-stage MCI patients.

作者:Simone C, Egli;Daniela I, Hirni;Kirsten I, Taylor;Manfred, Berres;Axel, Regeniter;Achim, Gass;Andreas U, Monsch;Marc, Sollberger

来源:Journal of Alzheimer's disease : JAD 2015 年 44卷 2期

知识库介绍

临床诊疗知识库该平台旨在解决临床医护人员在学习、工作中对医学信息的需求,方便快速、便捷的获取实用的医学信息,辅助临床决策参考。该库包含疾病、药品、检查、指南规范、病例文献及循证文献等多种丰富权威的临床资源。

详细介绍
热门关注
免责声明:本知识库提供的有关内容等信息仅供学习参考,不代替医生的诊断和医嘱。

收藏
| 浏览:73
作者:
Simone C, Egli;Daniela I, Hirni;Kirsten I, Taylor;Manfred, Berres;Axel, Regeniter;Achim, Gass;Andreas U, Monsch;Marc, Sollberger
来源:
Journal of Alzheimer's disease : JAD 2015 年 44卷 2期
标签:
Alzheimer's disease amyloid cerebrospinal fluid dementia diffusion tensor imaging fornix (brain) magnetic resonance imaging memory mild cognitive impairment
Several cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers predict conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia. However, predictors might be more or less powerful depending on the characteristics of the MCI sample.To investigate which cognitive markers and biomarkers predict conversion to AD dementia and course of cognitive functioning in a MCI sample with a high proportion of early-stage MCI patients.Variables known to predict progression in MCI patients and hypothesized to predict progression in early-stage MCI patients were selected. Cognitive (long-delay free recall, regional primacy score), imaging (hippocampal and entorhinal cortex volumes, fornix fractional anisotropy), and CSF (Aβ1-42/t-tau, Aβ1-42) variables from 36 MCI patients were analyzed with Cox regression and mixed-effect models to determine their individual and combined abilities to predict time to conversion to AD dementia and course of global cognitive functioning, respectively.Those variables hypothesized to predict the course of early-stage MCI patients were most predictive for MCI progression. Specifically, regional primacy score (a measure of word-list position learning) most consistently predicted conversion to AD dementia and course of cognitive functioning. Both the prediction of conversion and course of cognitive functioning were maximized by including CSF Aβ1-42 and fornix integrity biomarkers, respectively, indicating the complementary information carried by cognitive variables and biomarkers.Predictors of MCI progression need to be interpreted in light of the characteristics of the respective MCI sample. Future studies should aim to compare predictive strengths of markers between early-stage and late-stage MCI patients.