A - 53 A Digital Health Solution for Early Detection of Cognitive Impairment in Primary Care

OBJECTIVE

To determine which task or combination of tasks provided the most effective way to differentiate cognitively impaired (CI) from cognitively normal (CN) participants in under 5 minutes and to ensure that classification accuracy was equal to or better than a traditional brief cognitive screening task, the Quick Mild Cognitive Impairment (Qmci) screen.

METHOD

CN (n = 53) and CI (n = 51) participants completed a risk assessment task, a symbol matching (SM) task, and four speech-language tasks, followed by a second administration of SM to examine utility of practice effects administered on an iPad. Participants also completed the Qmci. Eleven models were tested using Bayesian adaptive regression trees.

RESULTS

The top three models all included the two SM variables: the one with SM by itself (estimated c = 0.91), one with SM and features from a personal narrative task (c = 0.94), and one with SM and a counting backwards task (c = 0.90). Models with picture description and procedural discourse tasks performed the worst. For comparison, the QMCI-only model yielded c = 0.91.

CONCLUSIONS

A combination of working memory/processing speed and acoustic and linguistic variables from recalling a personal story achieved a high level of classification accuracy, slightly exceeding that of a traditional cognitive screening task. The inclusion of both verbal and nonverbal tasks may be an important feature, allowing for cognitive screening of individuals who are not able to do one type of task or the other. Future work is planned to examine this shortened tool in a pragmatic clinical trial in two primary care clinics.

A-111 Validation of a Rapid Screening Measure for The Early Detection of Mild Cognitive Impairment in Older Adults

Objective: Examine the psychometric properties and classification accuracy of a digit symbol substitution task (DSST) to screen for mild cognitive impairment (MCI) in older adults.

Methods: Twenty-seven older adults with MCI and 50 demographically-matched healthy controls (HC) over age 60 completed the MMSE, Quick MCI (Qmci), and DSST, the latter of which was administered twice to examine the added utility of practice effects.

Results: Patients with MCI performed significantly worse than their HC counterparts on the MMSE (η2 = 0.191), Qmci (η2 = 0.153), and the first (η2 = 0.337) and second (η2 = 0.393) administration of the DSST. HC participants also demonstrated significantly greater practice effects than those with MCI who did not appear to benefit from task repetition (mean score increases of 7.4 and 0.5, respectively). The DSST exhibited excellent within-session test–retest reliability (R2 = 0.774) and was more strongly correlated with Qmci (R2 = 0.311) than MMSE (R2 = 0.112) scores. ROC analyses indicated that a cutoff score of 23.5 for the first administration (AUC = 0.860) and 27.5 for the second administration (AUC = 0.900) of the DSST were associated with superior classification accuracy to that of the MMSE (AUC = 0.759) and Qmci (AUC = 0.777). DSST difference scores (AUC = 0.764) reflecting within-session practice effects were slightly superior to the MMSE but not the Qmci. In logistic regression analyses, scores from the first administration of the DSST significantly predicted group membership and the addition of practice effects significantly improved model fit (p < 0.001) resulting in an overall classification accuracy of 85.1%.

Conclusions: Findings suggest that the DSST is a valid and reliable rapid screening measure which may prove useful for clinicians and researchers alike.

Examining Relationships between Multiple Self-Reported Sleep Measures and Gait Domains in Cognitively Healthy Older Adults

BACKGROUND

Gait-related changes in older adulthood may be related to changes in cognition (e.g., executive functioning), and recent work suggests that different self-reported measures of sleep may be tied to contrasting aspects of executive functioning. However, the relationship between these self-reported sleep measures and gait domains has not been explored. Such an investigation would be useful in helping to determine which older adults might exhibit changes in gait as well as experience other gait-associated changes (e.g., increased fall risk).

OBJECTIVE

To examine associations between different aspects of self-reported sleep and gait domains in a sample of cognitively healthy older adults.

METHOD

A total of 423 older adults (mean age 69.9 years, range 50-92) completed self-report measures of sleep quality, daytime sleepiness, and sleep-related distress. The participants also completed an objective, electronic measure of both single-task and dual-task gait (i.e., GAITRite). Principal component analyses were used to elucidate the solution for each gait condition, and multiple linear regression was used to examine the contributions of sleep measures to variability in gait performance.

RESULTS

A 5-component solution of the single-task condition and a 4-component solution of the dual-task condition were identified. Multiple linear regressions revealed that a poorer sleep quality was associated with greater single-task and dual-task asymmetry. Greater daytime sleepiness was associated with increased dual-task gait variability and postural control. After controlling for the effects of other facets of sleep, sleep-related distress was not associated with any gait domain.

CONCLUSIONS

Among cognitively healthy older adults,sleep quality and daytime sleepiness, but not sleep-related distress, are associated with aspects of gait. Patients who report these symptoms should be assessed and monitored for possible changes in gait.

Reliability and Validity of a Novel Internet-Based Battery to Assess Mood and Cognitive Function in the Elderly

Dementia is a chronic condition in the elderly and depression is often a concurrent symptom. As populations continue to age, accessible and useful tools to screen for cognitive function and its associated symptoms in elderly populations are needed. The aim of this study was to test the reliability and validity of a new internet-based assessment battery for screening mood and cognitive function in an elderly population. Specifically, the Helping Hand Technology (HHT) assessments for depression (HHT-D) and global cognitive function (HHT-G) were evaluated in a sample of 57 elderly participants (22 male, 35 female) aged 59-85 years. The study sample was categorized into three groups: 1) dementia (n = 8; Mini-Mental State Exam (MMSE) score 10-24), 2) mild cognitive impairment (n = 24; MMSE score 25-28), and 3) control (n = 25; MMSE score 29-30). Test-retest reliability (Pearson correlation coefficient, r) and internal consistency reliability (Cronbach's alpha, α) of the HHT-D and HHT-G were assessed. Validity of the HHT-D and HHT-G was tested via comparison (Pearson r) to commonly used pencil-and-paper based assessments: HHT-D versus the Geriatric Depression Scale (GDS) and HHT-G versus the MMSE. Good test-retest (r = 0.80; p < 0.0001) and acceptable internal consistency reliability (α= 0.73) of the HHT-D were established. Moderate support for the validity of the HHT-D was obtained (r = 0.60 between the HHT-D and GDS; p < 0.0001). Results indicated good test-retest (r = 0.87; p < 0.0001) and acceptable internal consistency reliability (α= 0.70) of the HHT-G. Validity of the HHT-G was supported (r = 0.71 between the HHT-G and MMSE; p < 0.0001). In summary, the HHT-D and HHT-G were found to be reliable and valid computerized assessments to screen for depression and cognitive status, respectively, in an elderly sample.

Apolipoprotein E Genotype Linked to Spatial Gait Characteristics: Predictors of Cognitive Dual Task Gait Change

Background

Developing measures to detect preclinical Alzheimer’s Disease is vital, as prodromal stage interventions may prove more efficacious in altering the disease’s trajectory. Gait changes may serve as a useful clinical heuristic that precedes cognitive decline. This study provides the first systematic investigation of gait characteristics relationship with relevant demographic, physical, genetic (Apolipoprotein E genotype), and health risk factors in non-demented older adults during a cognitive-load dual task walking condition.

Methods

The GAITRite system provided objective measurement of gait characteristics in APOE-e4 “carriers” (n = 75) and “non-carriers” (n = 224). Analyses examined stride length and step time gait characteristics during simple and dual-task (spelling five-letter words backwards) conditions in relation to demographic, physical, genetic, and health risk factors.

Results

Slower step time and shorter stride length associated with older age, greater health risk, and worse physical performance (ps < .05). Men and women differed in height, gait characteristics, health risk factors and global cognition (ps < .05). APOE-e4 associated with a higher likelihood of hypercholesterolemia and overall illness index scores (ps < .05). No genotype-sex interactions on gait were found. APOE-e4 was linked to shorter stride length and greater dual-task related disturbances in stride length.

Conclusions

Stride length has been linked to heightened fall risk, attention decrements and structural brain changes in older adults. Our results indicate that stride length is a useful behavioral marker of cognitive change that is associated with genetic risk for AD. Sex disparities in motor decline may be a function of health risk factors.