Nathan Hantke

Objectives: The Word List subtest of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuropsychological battery has been widely used in clinical research to identify and track cognitive disorders. However, normative data and change scores are lacking. The current study aimed to create normative data for the Word List subtest. Methods: CERAD Word List data from 1,530 older adults diagnosed as cognitively intact, Mild Cognitive Impairment (MCI), or dementia were seen for two annual visits in a longitudinal observational study from the Uniform Data Set of the National Alzheimer’s Coordinating Center. Multiple linear regression predicted Time 2 scores from Time 1 scores, demographic variables (age, education, sex, and race), and retest interval. Validation included comparing predicted scores to observed scores in the original sample, and additional validation across five comparison groups (cognitively intact, MCI, dementia, worsening cognition, or improving cognition) and one-sample chi-square test of probabilities to compare group classification to predicted categorization based on chance alone. Results: The four demographic variables significantly predicted test scores for the six primary scores from the Word List subtest. For change data, when predicted Time 2 scores were compared to observed Time 2 scores, there were significant differences for 4 of the 6 scores, but the effect sizes were small. Significant differences were found across the five comparison groups for Total Recall and Delayed Recall (p-values < .001). Conclusions: The current study provides normative data and regression-based change scores for the CERAD Word List subtest for older adults.

Background: Essential Tremor (ET) is increasingly recognized as phenotypically heterogeneous disorder, which may encompass alterations in gait, balance and cognitive dysfunction. Disruption in cerebellar-thalamic-cortical circuits results in varying patterns of executive and memory dysfunction and balance disorders. The current study proposed two aims: 1) identify cognitive subtypes within individuals with essential tremor, and 2) examine for a correlation between these subtypes and gait and balance dysfunction. We hypothesize that gait and balance dysfunction are more common in individuals with ET who demonstrate greater cognitive difficulties. Methods: Seventy-one individuals underwent neuropsychological and physical therapy examinations as part of presurgical deep brain stimulation (DBS) evaluations that included measures of gait and balance (Mini-BESTest; Timed Up and Go, SARA). People with ET were categorized into Cognitively Normal (N = 29), Low Executive Function/Processing Speed (N = 17), and Low Memory Multi-domain groups (N = 25). Results: Regression analyses show that scores on the Mini-Balance Evaluation Systems Test and Scale for the Assessment and Rating of Ataxia were worse in the Low Memory and Low Executive Function groups compared to the cognitively normal group; age was also a significant predictor. Scores on the Timed Up and Go were worse for the Low Executive Function compared to the cognitive normal group; age and education were also significant predictors. Medication use was not associated with any of the clinical gait and balance tests. However, medication use and age were significant predictors of reported falls in daily life. Conclusions: A subset of individuals with ET experience cognitive dysfunction that coalesce into processing speed deficits or immediate memory deficits. These cognitive subtypes were associated with greater difficulty in balance and gait as compared to cognitively normal ET patient and this difference could not be accounted for by medications.

Background: List learning and memory tests are frequently used to evaluate older adults for Mild Cognitive Impairment and Alzheimer’s disease. One such test, the Word List subtest of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), has been widely‐used in clinical trials track such disorders. However, data is lacking on the amount of change that is needed to accurately identify decline.Method: Participants included 897 older adults (age in years: M = 81.1, SD = 8.1, range 55‐100; 67% women; education in years: M = 14.8, SD = 2.8, range = 7‐24) who were cognitively intact at two annual visits in a longitudinal observational study from the Uniform Data Set of the National Alzheimer’s Coordinating Center. Each participant completed the Word List subtest at two visits, which were approximately 1 year apart (interval in years: M = 1.3, SD = 1.0). Multiple linear regression predicted Time 2 scores from Time 1 scores and simple demographic variables (age, sex, education). The predicted Time 2 scores were compared to observed Time 2 scores to preliminarily validate this change data.Result: For three primary scores from the Word List subtest (Acquisition Total Correct, Delay Recall Total Correct, Recognition Total Correct), the Time 2 scores were significantly predicted from the other variables, with R²s ranging from 0.16 – 0.41 (p‐values<0.001). When these predicted Time 2 scores were compared to observed Time 2 scores, there were no significant differences (p‐values≧0.19), indicating preliminary support for these prediction scores.Conclusion: The current prediction equations appear to allow clinicians and researchers to accurately track change on the Word List subtest of the CERAD by comparing their patients/participants to the current sample of robustly intact older adults. Consistent with past work in this area, Time 1 cognitive scores were the best predictors of Time 2 cognitive scores, although demographic variables added to that prediction. Future work should consider if additional variables can improve the prediction equations. Future work should also validate these equations in independent samples to examine their clinical utility.

Background: List learning and memory tests are frequently used to evaluate older adults for late life cognitive disorders, such as Alzheimer’s disease. The Word List subtest of the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuropsychological battery has been widely‐used in clinical research, including clinical trials, to identify and track such disorders. It is also freely‐available, as it is in the public domain. However, normative data, especially in robustly intact older adults, is lacking.Method: CERAD Word List data from 897 older adults (age in years: M = 81.1, SD = 8.1, range 55‐100; 67% women; education in years: M = 14.8, SD = 2.8, range = 7‐24) deemed to be cognitively intact at two annual visits in a longitudinal observational study from the Uniform Data Set of the National Alzheimer’s Coordinating Center were used to generate predicted Word List scores based on age, sex, and education. Predicted scores were compared to observed scores to preliminarily validate these normative values.Result: For six primary scores from the Word List subtest (Trial 1, Trial 2, Trial 3, Total Acquisition, Delay Recall, Recognition Total Correct), the three demographic variables significantly predicted test scores, with R²s ranging from 0.03 – 0.18 (p‐values0.40), indicating preliminary support for these prediction scores.Conclusion: Although further validation is needed in independent intact and impaired samples, the current demographically‐based prediction scores provide normative data for the CERAD Word List subtest for older adults being evaluated for cognitive complaints. The inclusion of additional variables needs to be examined to improve the accuracy of these prediction scores. Nonetheless, normative data allows providers and researchers to be confident in using this learning and memory test in clinics and clinical trials.

Background: Outcome measures available for use in Alzheimer’s disease (AD) clinical trials are limited in ability to detect gradual changes. Measures of everyday function and cognition assessed unobtrusively at home using embedded sensing and computing generated “digital biomarkers” (DBs) have been shown to be ecologically valid and to improve efficiency of clinical trials. However, DBs have not been assessed for their relationship to AD neuropathology. Objectives: The goal of the current study is to perform an exploratory examination of possible associations between DBs and AD neuropathology in an initially cognitively intact community-based cohort. Methods: Participants included in this study were ≥65 years of age, living independently, of average health for age, and followed until death. Algorithms, run on the continuously-collected passive sensor data, generated daily metrics for each DB: cognitive function, mobility, socialization, and sleep. Fixed postmortem brains were evaluated for neurofibrillary tangles (NFTs) and neuritic plaque (NP) pathology and staged by Braak and CERAD systems in the context of the “ABC” assessment of AD-associated changes. Results: The analysis included a total of 41 participants (M±SD age at death = 92.2±5.1 years). The four DBs showed consistent patterns relative to both Braak stage and NP score severity. Greater NP severity was correlated with the DB composite and reduced walking speed. Braak stage was associated with reduced computer use time and increased total time in bed. Discussion: This study provides the first data showing correlations between DBs and neuropathological markers in an aging cohort. The findings suggest continuous, home-based DBs may hold potential to serve as behavioral proxies that index neurodegenerative processes.

We aimed to examine the impact of COVID-19 pandemic-related stay-at-home orders on weekly reports of mood and activity before and during COVID-19 in a sample of older Veterans and their cohabitants...

Objective The COVID-19 pandemic has severely disrupted all aspects of academic medicine, including post-doctoral research fellowship training. The current survey examined ways in which research fellows across 28 U.S. nationally diverse sites have been impacted. Methods Survey participants included 62 M.D. and Ph.D. post-doctoral fellows and 27 local fellowship center directors within the Veterans Affairs (VA) Advanced Fellowship in Mental Illness Research and Treatment (MIRT), a national fellowship program tasked to develop academic clinician researchers within the field of mental health. Survey questions focused on productivity and challenges experienced by fellows during the pandemic. Results Half of fellows reported working entirely off-site during the COVID-19 pandemic. All fellows reported some level of disruption in productivity during the pandemic; 73% reported a disruption in data collection, 69% reported decreased scholarly output, 41% reported disruption in grant writing, and 73% reported disruption in ability to provide clinical care. Yet, the majority of fellows (66%) reported not having to change their research goals, pivoting to telehealth-based data collection, and employing extant data for research projects and peer-reviewed publications. Conclusions The results of the fellow and director surveys highlight the associated disruption of the COVID-19 pandemic on fellowship-related activities and parallel ingenuity of programs to continue conducting research and clinical services in a modified fashion. While many research goals continued unabated, the findings suggest alterations in data collection methodology and a focus on using extant data, which may have a residual influence on future early career research grant applications.