摘要
背景:发现阿尔茨海默氏病(AD)和轻度认知功能障碍(MCI) 在出现症状前的早期迹象变得日益重要,使临床试验物有所值并从现有的治疗策略中获得最大受益。然而,区分MCI的早期迹象与正常认知老化是很困难的。生物学标记物广泛应用于AD病理过程的早期检测指标,但是评估这些生物标学志物是昂贵的,并且要广泛应用于症状出现前的社区居住老年人是富有挑战的。在此,我们提出评估社会学标志,它可能为识别引起AD和MCI的症状前期提供一种替代性或补充性以及从生态学观点来看的有效战略。方法:数据来自一个规模较大的随机对照临床试验(RCT),我们调查了使用远程视频通信软件进行日常对话互动是否能改善老年参与者的认知功能。我们评估参与者的话语在参与者和员工面谈者总话语中所占比例,并在干预试验中记录会话作为两人(参与者和面谈者) 在一对一谈话中相互交流的指标。我们检测认知功能正常者与MCI者之间话语比例是否不同。首先,运用广义估计方程分析话语比例结果,接着,运用逻辑回归模型分析认知状态结果,以此估计ROC曲线下面积(ROC-AUC)。结果:相对于那些认知功能正常者,MCI参与者在定时对话会话中的话语占总话语比例更高(p = 0.01)。控制了参与者的年龄、性别、面谈者和评估后这种差异仍然存在(p = 0.03)。当受试者所说的平均话语计数比例作为单变量计入模型时,逻辑回归模型分析显示识别MCI(较正常者)的ROC曲线下面积为0.71(95%置信区间:0.54 - 0.89)。结论:一个从生态学观点来看,如在自然对话中产生的口头语言的比例等有效社会学标志可能对从认知功能正常到MCI的转变敏感。
关键词: 生物学标志
Current Alzheimer Research
Title:Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech
Volume: 12 Issue: 6
Author(s): Hiroko H. Dodge, Nora Mattek, Mattie Gregor, Molly Bowman, Adriana Seelye, Oscar Ybarra, Meysam Asgari and Jeffrey A. Kaye
Affiliation:
关键词: 生物学标志
摘要: Background: Detecting early signs of Alzheimer’s disease (AD) and mild cognitive impairment (MCI) during the pre-symptomatic phase is becoming increasingly important for costeffective clinical trials and also for deriving maximum benefit from currently available treatment strategies. However, distinguishing early signs of MCI from normal cognitive aging is difficult. Biomarkers have been extensively examined as early indicators of the pathological process for AD, but assessing these biomarkers is expensive and challenging to apply widely among pre-symptomatic community dwelling older adults. Here we propose assessment of social markers, which could provide an alternative or complementary and ecologically valid strategy for identifying the pre-symptomatic phase leading to MCI and AD. Methods: The data came from a larger randomized controlled clinical trial (RCT), where we examined whether daily conversational interactions using remote video telecommunications software could improve cognitive functions of older adult participants. We assessed the proportion of words generated by participants out of total words produced by both participants and staff interviewers using transcribed conversations during the intervention trial as an indicator of how two people (participants and interviewers) interact with each other in one-on-one conversations. We examined whether the proportion differed between those with intact cognition and MCI, using first, generalized estimating equations with the proportion as outcome, and second, logistic regression models with cognitive status as outcome in order to estimate the area under ROC curve (ROC AUC). Results: Compared to those with normal cognitive function, MCI participants generated a greater proportion of words out of the total number of words during the timed conversation sessions (p=0.01). This difference remained after controlling for participant age, gender, interviewer and time of assessment (p=0.03). The logistic regression models showed the ROC AUC of identifying MCI (vs. normals) was 0.71 (95% Confidence Interval: 0.54 – 0.89) when average proportion of word counts spoken by subjects was included univariately into the model. Conclusion: An ecologically valid social marker such as the proportion of spoken words produced during spontaneous conversations may be sensitive to transitions from normal cognition to MCI.
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Hiroko H. Dodge, Nora Mattek, Mattie Gregor, Molly Bowman, Adriana Seelye, Oscar Ybarra, Meysam Asgari and Jeffrey A. Kaye , Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech, Current Alzheimer Research 2015; 12 (6) . https://dx.doi.org/10.2174/1567205012666150530201917
DOI https://dx.doi.org/10.2174/1567205012666150530201917 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
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