Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech
Social Markers of Mild Cognitive Impairment: Proportion of Word Counts in Free Conversational Speech
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DOI：
10.2174/1567205012666150530201917
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发表时间：
2015-01-01
影响因子：
2.1
通讯作者：
Kaye, Jeffrey A.
中科院分区：
文献类型：
--
作者：
Dodge, Hiroko H.;Mattek, Nora;Kaye, Jeffrey A.
背景：在症状前阶段检测阿尔茨海默病(AD)和轻度认知功能障碍(MCI)的早期迹象对于经济有效的临床试验和从现有治疗策略中获得最大好处变得越来越重要。然而，将MCI的早期迹象与正常的认知老化区分开来是困难的。生物标记物已被广泛研究为AD病理过程的早期指标，但评估这些生物标记物在无症状的社区居住的老年人中广泛应用是昂贵和具有挑战性的。在这里，我们建议评估社会标记物，它可以为识别导致MCI和AD的症状前阶段提供一种替代或补充的生态有效的策略。方法：这些数据来自一项更大的随机对照临床试验(RCT)，在该试验中，我们检查了使用远程视频通信软件进行日常对话互动是否可以改善老年参与者的认知功能。我们使用干预试验期间转录的对话来评估参与者和工作人员面试者产生的总词汇中参与者产生的词汇的比例，以此作为两个人(参与者和面试者)在一对一对话中如何相互作用的指标。我们检验了认知完好者和MCI之间的比例是否不同，第一，以比例为结果的广义估计方程，第二，以认知状态为结果的Logistic回归模型，以估计ROC曲线下面积(ROC AUC)。结果：与认知功能正常的受试者相比，MCI受试者在限时会话中产生的词汇占总词汇的比例更大(p=0.01)。在控制了参与者的年龄、性别、面试者和评估时间后，这种差异仍然存在(p=0.03)。Logistic回归模型显示，将受试者所说词数的平均比例纳入模型中时，识别MCI(与正常人)的ROC AUC为0.71(95%可信区间：0.54-0.89)。结论：一个生态上有效的社会标记物，如自发对话中产生的言语比例，可能对从正常认知到MCI的转变很敏感。
Background: Detecting early signs of Alzheimer's disease (AD) and mild cognitive impairment (MCI) during the pre-symptomatic phase is becoming increasingly important for cost-effective 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.