The potential of depressive symptoms to identify cognitive impairment in ageing.

IF 3.7 2区 社会学 Q1 GERONTOLOGY
Panagiotis Alexopoulos, Christos Bountoulis, Everina Katirtzoglou, Mary H Kosmidis, Kostas Siarkos, Mary Yannakoulia, Efthimios Dardiotis, Maria Skondra, Georgios Hadjigeorgiou, Robert Perneczky, Paraskevi Sakka, Eleni-Zacharoula Georgiou, Μarina Charalampopoulou, Panagiotis Felemegkas, Iracema Leroi, Apostolos Batsidis, Laura Perna, Antonios Politis, Nikolaos Scarmeas, Polychronis Economou
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Abstract

Depressive symptoms are common in mild cognitive impairment (MCI), dementia caused by Alzheimer's disease (AD dementia) and in cognitively unimpaired older adults. However, it is unclear whether they could contribute to the identification of cognitive impairment in ageing. To assess the potential utility of depressive symptoms to distinguish between healthy cognitive ageing and MCI and AD dementia. The diagnostic workup of the cognitive function of 1737 older cognitively unimpaired individuals, 334 people with MCI and 142 individuals with AD dementia relied on a comprehensive neuropsychiatric assessment, including the Mini Mental State Examination (MMSE). Depressive symptoms were tapped with the 15-item Geriatric Depression Scale (GDS). Proportional odds logistic regression (POLR) models and the machine learning technique Adaptive Boosting algorithm (AdaBoost) were employed. Stratified repeated random subsampling (stratified bootstrap resampling) was used to recursive partitioning to training- and validation set (70/30 ratio). The average accuracy of the POLR models for the GDS total score in distinguishing between cognitive impairment and healthy cognitive ageing exceeded 78% and was inferior to that of MMSE. Of note, the sensitivity of GDS total score was very low. By employing the AdaBoost algorithm and considering GDS items separately, the average accuracy was higher than 0.72 and comparable to that of the MMSE, while sensitivity- and specificity values were more balanced. The findings of the study provide initial evidence that depressive symptoms may contribute to distinguishing between cognitive impairment and cognitively healthy ageing.

抑郁症状识别衰老过程中认知障碍的潜力
抑郁症状常见于轻度认知障碍(MCI)、阿尔茨海默病引起的痴呆(AD痴呆)和认知未受损的老年人。然而,目前尚不清楚它们是否有助于识别衰老过程中的认知障碍。评估抑郁症状在区分健康认知老化、MCI和AD痴呆中的潜在效用。1737名认知功能未受损的老年人、334名轻度认知障碍患者和142名AD痴呆患者的认知功能诊断工作依赖于包括迷你精神状态检查(MMSE)在内的综合神经精神病学评估。采用15项老年抑郁量表(GDS)对抑郁症状进行测量。采用比例odds logistic regression (POLR)模型和机器学习技术Adaptive Boosting algorithm (AdaBoost)。采用分层重复随机子抽样(分层自举重抽样)对训练集和验证集进行递归划分(70/30)。POLR模型对GDS总分区分认知障碍和健康认知衰老的平均准确率超过78%,低于MMSE模型。值得注意的是,GDS总分的敏感性很低。采用AdaBoost算法并单独考虑GDS项目,平均准确率高于0.72,与MMSE相当,而敏感性和特异性值更加平衡。该研究的发现提供了初步证据,表明抑郁症状可能有助于区分认知障碍和认知健康老龄化。
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来源期刊
CiteScore
6.50
自引率
7.90%
发文量
72
期刊介绍: The European Journal of Ageing: Social, Behavioural and Health Perspectives is an interdisciplinary journal devoted to the understanding of ageing in European societies and the world over. EJA publishes original articles on the social, behavioral and population health aspects of ageing and encourages an integrated approach between these aspects. Emphasis is put on publishing empirical research (including meta-analyses), but conceptual papers (including narrative reviews) and methodological contributions will also be considered. EJA welcomes expert opinions on critical issues in ageing. By stimulating communication between researchers and those using research findings, it aims to contribute to the formulation of better policies and the development of better practice in serving older adults. To further specify, with the term ''social'' is meant the full scope of social science of ageing related research from the micro to the macro level of analysis. With the term ''behavioural'' the full scope of psychological ageing research including life span approaches based on a range of age groups from young to old is envisaged. The term ''population health-related'' denotes social-epidemiological and public health oriented research including research on functional health in the widest possible sense.
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