Using Variational Autoencoder to Develop and Validate a Compact, Deep Representation of Digital Clock Drawing Test for Classifying Dementia

The Clock Drawing Test (CDT) is an inexpensive tool to screen for dementia. In this study, we examined if a semi-supervised deep learning (DL) system using Variational Autoencoder (VAE) can extract atypical clock features from a large dataset of unannotated CDTs (n=13,580) and use them to classify dementia (n=18) from non-dementia (n=20) peers. The classification model built with VAE latent space features adequately classified dementia from non-dementia (0.78 Area Under Receiver Operating Characteristics (AUROC)). The VAE-identified atypical clock features were then reviewed by domain experts and compared with existing literature on clock drawing errors. This study shows that a semi-supervised deep learning (DL) analysis of the CDT can extract important clock drawing anomalies that are predictive of dementia.

Extended Application of Digital Clock Drawing Test in the Evaluation of Alzheimer’s Disease Based on Artificial intelligence and the Neural Basis

Introduction: This study aimed to build the supervised learning model to predict the state of cognitive impairment, Alzheimer’s Disease (AD) and cognitive domains including memory, language, action, and visuospatial based on Digital Clock Drawing Test (dCDT) precisely. Methods: 207 normal controls, 242 Mild Cognitive Impairment (MCI) patients, 87 dementia patients, including 53 AD patients, were selected from Shanghai Tongji Hospital. The electromagnetic tablets were used to collect the trajectory points of dCDT. By combining dynamic process and static results, different types of features were extracted, and the prediction models were built based on the feature selection approaches and machine learning methods. Results: The optimal AUC of cognitive impairment’s screening, AD’s screening and differentiation are 0.782, 0.919 and 0.818, respectively. In addition, the cognitive state of the domains with the best prediction result based on the features of dCDT is action with the optimal AUC 0.794, while the other three cognitive domains got the prediction results between 0.744-0.755. Discussion: By extracting dCDT features, cognitive impairment and AD patients can be identified early. Through dCDT feature extraction, a prediction model of single cognitive domain damage can be established.

Clock drawing test: comparison between the Pfizer and the Shulman systems

ABSTRACT Cognitive decline can be screened by the clock drawing test (CDT), which has several versions. Objective: This survey aimed to analyze the correlation between two simple methods for scoring the CDT. Methods: This cross-sectional study was nested in the Elo-Creati cohort from Passo Fundo, Brazil and comprised 404 subjects. Two raters underwent previous training and scored the subjects’ CDT according to both the Pfizer and Shulman systems. The inter-observer and intra-observer concordance within each method was analyzed with the Spearman’s rank correlation coefficient, as well as the concordance of the scores between the two methods. Age and scholarity were also correlated with the scores. Results: Most of the participants were women (93.8%) and Caucasian (84.6%), with a mean age of 66.9 (±7.8) years and a scholarity of 10.9 years (±5.6). There was significant inter-observer (Pfizer: r=0.739, p£0.001; Shulman: r=0.727, p£0.001) and intra-observer correlation (Pfizer: rater 1, r=0.628, p≤0.001; rater 2, r=0.821, p≤0.001; Shulman: rater 1, r=0.843, p≤0.001; rater 2: r=0.819; p≤0.001). Intra-observer correlation was also observed comparing Pfizer and Shulman methods (rater 1: r=0.744; p≤0.001; rater 2: r=0.702; p≤0.001). There was weak correlation of the scores with scholarity (Pfizer: r=0.283, p£0.001; Shulman: r=0.244, p£0.001) and age (Pfizer: r=-0.174, p£0.001; Shulman: r=-0.170, p£0.001). More participants were classified with decreased cognition through the Pfizer system (rater 1: 44.3 vs. 26.5%; rater 2: 42.1 vs. 16.3%; p≤0.001). Conclusions: For this population, our results suggest that the Pfizer system of scoring CDT is more suitable for screening cognitive decline.

Caregiver Burden Is Associated With Dementia Patient Cognitive Performance in NHATS

Informal caregivers of dementia patients engage in multicomponent care that is often stressful. In heart failure patients, caregiver burden has been associated with occurrence of cardiovascular events. However, little is known about how caregiver burden affects patient cognition in dementia care dyads. Using data from the National Health and Aging Trends Study and National Study of Caregiving, we examined the association between caregiver burden, assessed on 38 aspects of caring, and patient cognition, assessed with the immediate and delay word recall, Clock Drawing, and self-rated memory. In fully adjusted models at round 7 (2017) higher caregiver burden was cross-sectionally associated with lower immediate (B=-0.02, 95% CI -0.03, -0.01) and delayed (B=-0.03, 95% CI -0.04, -0.02) word recall. Longitudinally, across rounds 7-9 (2017-2019) higher burden was associated with lower patient Clock Draw score (B=-0.01, 95% CI -0.03, -0.001). These findings have implications for economic assistance and interventions in dementia care dyad.

Get Moving! Your Brain Will Thank You

Exercise and cardiovascular fitness are important for physical health and well-being. Recent studies show that exercise is associated with cognitive performance across multiple domains including memory, a common complaint for older adults. Data included a ten-word list of delayed recall, a clock drawing activity, and a three-meter walking course derived from the National Health & Aging Trends Study Database (NHATS Round 9). A total of 4977 participants were included in the analysis which was predominantly white (69.7%), non-Hispanic (94.5%), female (59.2%), and between the ages of 70-84 (62.7%). A hierarchical linear regression revealed that performance on the three-meter walking course positively predicted performance on delayed recall, F(4,3999)=300.257, p<.001, and on the clock drawing activity, which is a common screening task for cognitive decline, F(4,3978)=156.433, p<.001; accounting for 23.1% and 13.6% of the variability, respectively, over and above known demographic variables. Findings suggest that fitness may be one of many factors that is associated with memory and overall cognitive decline. These findings are timely as many individuals slowed down as a result of the COVID-19 pandemic, resulting in decreases in exercise and physical activity. Not being physically active or exercising may be related to poorer physical and cognitive health, with specific concerns regarding memory. Taking into consideration the fear and anxiety associated with declining memory in late life, it is crucial to explore this area further along with other factors that may contribute to the association and develop new ways for older adults to exercise safely during the COVID-19 pandemic.

Get up and go! An Evaluation of Fitness and Memory

As we age, exercise is increasingly important for physical health and well-being. Recent studies have shown that exercise is associated with cognitive performance across multiple domains, specifically memory, a common complaint for older adults. Data included a ten-word list of delayed recall, a clock drawing activity, and a sit-to-stand task (i.e., a low impact sub-maximal test of functional fitness) derived from the National Health & Aging Trends Study Database (NHATS Round 9). A total of 4977 participants were included in the analysis which was predominantly white (69.7%), non-Hispanic (94.5%), female (59.2%), and between the ages of 70-84 (62.7%). A hierarchical linear regression revealed that performance on the sit-to-stand task positively predicted performance on delayed recall, F(4,3914)=245.141, p<.001, and on the clock drawing activity, a common screening task for cognitive decline, F(4,2893)=115.470, p<.001; accounting for 20.1% and 10.6% of the variability, respectively, over and above known demographic variables. These findings indicate that exercise may be one of many factors that is associated with memory and cognitive decline. Given the continuation of quarantine procedures, these findings come at a time of significant clinical relevance. Research shows that many individuals slowed down because of the COVID-19 pandemic, and current findings suggest that not being physically active may be related to poorer physical and cognitive health, with specific concerns surrounding memory. Future research is essential in this area to tease out of other factor that may be contributing to this relationship and to develop new and innovated modalities for older adults to safely exercise.