Informant-reported cognitive symptoms that predict amnestic mild cognitive impairment

<p>Abstract</p> <p>Background</p> <p>Differentiating amnestic mild cognitive impairment (aMCI) from normal cognition is difficult in clinical settings. Self-reported and informant-reported memory complaints occur often in both clinical groups, which then necessitates the use of a comprehensive neuropsychological examination to make a differential diagnosis. However, the ability to identify cognitive symptoms that are predictive of aMCI through informant-based information may provide some clinical utility in accurately identifying individuals who are at risk for developing Alzheimer's disease (AD).</p> <p>Methods</p> <p>The current study utilized a case-control design using data from an ongoing validation study of the Alzheimer's Questionnaire (AQ), an informant-based dementia assessment. Data from 51 cognitively normal (CN) individuals participating in a brain donation program and 47 aMCI individuals seen in a neurology practice at the same institute were analyzed to determine which AQ items differentiated aMCI from CN individuals.</p> <p>Results</p> <p>Forward stepwise multiple logistic regression analysis which controlled for age and education showed that 4 AQ items were strong indicators of aMCI which included: repetition of statements and/or questions [OR 13.20 (3.02, 57.66)]; trouble knowing the day, date, month, year, and time [OR 17.97 (2.63, 122.77)]; difficulty managing finances [OR 11.60 (2.10, 63.99)]; and decreased sense of direction [OR 5.84 (1.09, 31.30)].</p> <p>Conclusions</p> <p>Overall, these data indicate that certain informant-reported cognitive symptoms may help clinicians differentiate individuals with aMCI from those with normal cognition. Items pertaining to repetition of statements, orientation, ability to manage finances, and visuospatial disorientation had high discriminatory power.</p

Quality-of-life assessment in dementia: the use of DEMQOL and DEMQOL-Proxy total scores

Purpose There is a need to determine whether health-related quality-of-life (HRQL) assessments in dementia capture what is important, to form a coherent basis for guiding research and clinical and policy decisions. This study investigated structural validity of HRQL assessments made using the DEMQOL system, with particular interest in studying domains that might be central to HRQL, and the external validity of these HRQL measurements. Methods HRQL of people with dementia was evaluated by 868 self-reports (DEMQOL) and 909 proxy reports (DEMQOL-Proxy) at a community memory service. Exploratory and confirmatory factor analyses (EFA and CFA) were conducted using bifactor models to investigate domains that might be central to general HRQL. Reliability of the general and specific factors measured by the bifactor models was examined using omega (?) and omega hierarchical (? h) coefficients. Multiple-indicators multiple-causes models were used to explore the external validity of these HRQL measurements in terms of their associations with other clinical assessments. Results Bifactor models showed adequate goodness of fit, supporting HRQL in dementia as a general construct that underlies a diverse range of health indicators. At the same time, additional factors were necessary to explain residual covariation of items within specific health domains identified from the literature. Based on these models, DEMQOL and DEMQOL-Proxy overall total scores showed excellent reliability (? h > 0.8). After accounting for common variance due to a general factor, subscale scores were less reliable (? h < 0.7) for informing on individual differences in specific HRQL domains. Depression was more strongly associated with general HRQL based on DEMQOL than on DEMQOL-Proxy (?0.55 vs ?0.22). Cognitive impairment had no reliable association with general HRQL based on DEMQOL or DEMQOL-Proxy. Conclusions The tenability of a bifactor model of HRQL in dementia suggests that it is possible to retain theoretical focus on the assessment of a general phenomenon, while exploring variation in specific HRQL domains for insights on what may lie at the ‘heart’ of HRQL for people with dementia. These data suggest that DEMQOL and DEMQOL-Proxy total scores are likely to be accurate measures of individual differences in HRQL, but that subscale scores should not be used. No specific domain was solely responsible for general HRQL at dementia diagnosis. Better HRQL was moderately associated with less depressive symptoms, but this was less apparent based on informant reports. HRQL was not associated with severity of cognitive impairment

Automatic Identification of Behavior Patterns in Mild Cognitive Impairments and Alzheimer's Disease Based on Activities of Daily Living

The growing number of older adults worldwide places high pressure on identifying dementia at its earliest stages so that early management and intervention strategies could be planned. In this study, we proposed a machine learning based method for automatic identification of behavioral patterns of people with mild cognitive impairments and Alzheimer's disease through the analysis of data related to their activities of daily living collected in two smart homes environments. Our method employs first a feature selection technique to extract relevant features for classification and reduce the dimensionality of the data. Then, the output of the feature selection is fed into a random forest classifier for classification. We recruited three groups of participants in our study: healthy older adults, older adults with mild cognitive impairments and older adults with Alzheimer's disease. We conducted extensive experiments to validate our proposed method. We experimentally showed that our method outperforms state-of-the-art machine learning algorithms

Do instrumental activities of daily living predict dementia at 1- and 2-year follow-up? Findings from the Development of Screening guidelines and diagnostic Criteria for Predementia Alzheimer's disease study.

OBJECTIVES: To investigate whether problems in instrumental activities of daily living (IADL) can add to conventionally used clinical measurements in helping to predict a diagnosis of dementia at 1- and 2-year follow-up. DESIGN: Multicenter prospective cohort study. SETTING: Memory clinics in Europe. PARTICIPANTS: Individuals aged 55 and older without dementia. MEASUREMENTS: IADLs were measured using pooled activities from five informant-based questionnaires. Structural equation modeling (SEM) was used to investigate the relation between IADLs and dementia. Age, sex, education, depression, and cognitive measures (Mini-Mental State Examination and verbal memory) were included in the model. RESULTS: Five hundred thirty-one participants had baseline and 1-year follow-up assessments; 69 (13.0%) of these had developed dementia at 1-year follow-up. At 2-year follow-up, 481 participants were seen, of whom 100 (20.8%) had developed dementia. Participants with IADL disabilities at baseline had a higher conversion rate (24.4%) than participants without IADL disabilities (16.7%) (chi-square = 4.28, degrees of freedom = 1, P = .04). SEM showed that IADL disability could help predict dementia in addition to the measured variables at 1-year follow-up (odds ratio (OR) = 2.20, 95% confidence interval (CI) = 1.51-3.13) and 2-year follow-up (OR = 2.11, 95% CI = 1.33-3.33). CONCLUSION: IADL disability is a useful addition to the diagnostic process in a memory clinic setting, indicating who is at higher risk of developing dementia at 1- and 2-year follow-up

Development of a model on factors affecting instrumental activities of daily living in people with mild cognitive impairment - A Delphi study

Introduction: The level of function of instrumental activities of daily living (IADL) is crucial for a person's autonomy. A clear understanding of the nature of IADL and its limitations in people with mild cognitive impairment (MCI) is lacking. Literature suggests numerous possible influencing factors, e.g. cognitive function, but has not considered other domains of human functioning, such as environmental factors. Our aim was to develop a comprehensive model of IADL functioning that depicts the relevant influencing factors. Methods: We conducted a four-round online Delphi study with a sample of international IADL experts (N = 69). In the first round, panelists were asked to mention all possible relevant cognitive and physical function factors, as well as environmental and personal factors, that influence IADL functioning. In the subsequent rounds, panelists rated the relevance of these factors. Consensus was defined as: 1) ≥70% agreement between panelists on a factor, and 2) stability over two successive rounds. Results: Response rates from the four rounds were high (83 to 100%). In the first round, 229 influencing factors were mentioned, whereof 13 factors reached consensus in the subsequent rounds. These consensual factors were used to build a model of IADL functioning. The final model included: five cognitive function factors (i.e. memory, attention, executive function, and two executive function subdomains -problem solving / reasoning and organization / planning); five physical function factors (i.e. seeing functions, hearing functions, balance, gait / mobility functions and functional mobility functions); two environmental factors (i.e. social network / environment and support of social network / environment); and one personal factor (i.e. education). Conclusions: This study proposes a comprehensive model of IADL functioning in people with MCI. The results from this Delphi study suggest that IADL functioning is not merely affected by cognitive function factors, but also by physical function factors, environmental factors and personal factors. The multiplicity of factors mentioned in the first round also underlines the individuality of IADL functioning in people with MCI. This model may serve as a basis for future research in IADL functioning in people with MCI