Computerized Cognitive Testing for Use in Clinical Trials: A Comparison of the NIH Toolbox and Cogstate C3 Batteries

NIH Toolbox Cognition Performance in Older Adults with Normal Cognition, Mild Cognitive Impairment, and Mild Dementia of the Alzheimer's Type: Results from the ARMADA Study

OBJECTIVE

Efficient and early detection of cognitive impairment may be facilitated using the NIH Toolbox (NIHTB), a computerized suite of assessments measuring multiple aspects of neurological functioning.

METHODS

The Advancing Reliable Measurement in Alzheimer's Disease and cognitive Aging study validated the NIHTB across a geographically diverse cognitive aging sample. Participants aged >64 with normal cognition (NC), mild cognitive impairment (MCI), and dementia of the Alzheimer type (DAT) across nine research sites completed the NIHTB. One-way ANOVAs captured differences in performance on the Cognition Battery and effect sizes were calculated.

RESULTS

Groups differed substantially across all cognition measures, with large differences in Total and Fluid Cognition, after demographic adjustment. The largest differentiators were in fluid measures, particularly for working and episodic memory.

CONCLUSIONS

NIHTB-CB differentiates NC, MCI, and DAT groups. Future studies will examine longitudinal differences and performance in enriched samples (African American participants, Spanish NIHTB, 85+ years old).

Accuracy of Reaction Time Measurement on Automated Neuropsychological Assessment Metric UltraMobile

OBJECTIVE

This observational study examined the accuracy of simple reaction time (RT) measurements on various touchscreen tablet devices using the Automated Neuropsychological Assessment Metric (ANAM) UltraMobile test battery. The study investigated the implications of interpreting ANAM UltraMobile with laptop-based normative data by analyzing the magnitude and variability of RT accuracy across devices.

METHOD

RT accuracy on 10 different tablets was assessed using a photodetector and robotic arm to respond to stimuli at predetermined response times. The recorded RT was compared with the true RT obtained from the robotic arm to calculate the RT error.

RESULTS

ANAM UltraMobile recorded slower RTs than the laptop version. Additionally, RT error varied considerably among the 10 tablet models, suggesting psychometrically significant implications that could lead to interpretive errors when using laptop-based normative data.

CONCLUSIONS

Relative to the RT error from the laptop-based version of ANAM, tablet data from ANAM UltraMobile are significantly slower and exhibit large variability between devices. These differences may have clinically significant implications for the comparability of the two versions. The findings suggest that further research with human participants is needed to assess the equivalence of ANAM UltraMobile with its predecessor.

The Digitized Memory Clinic

Several major challenges, including an ageing population and declining workforce and the implementation of recent breakthrough therapies for Alzheimer disease, are prompting a necessary rethink of how people with neurodegenerative dementias are diagnosed and medically managed. Digital health technologies could play a pivotal part in this transformation, with new advances enabling the collection of millions of data points from a single individual. Possible applications include unobtrusive monitoring that aids early detection of disease and artificial intelligence-based health advice. To translate these advances to meaningful benefits for people living with a disease, technologies must be implemented within a system that retains the physician expert as a central figure in decision-making. This Perspective presents a new framework, termed the Digitized Memory Clinic, for the diagnostic pathway of neurodegenerative dementias that incorporates digital health technologies with currently available assessment tools, such as fluid and imaging biomarkers, in an interplay with the physician. The Digitized Memory Clinic will manage people across the entire disease spectrum, from the detection of risk factors for cognitive decline and the earliest symptoms to dementia, and will replace the present paradigm of a pure 'brick-and-mortar' memory clinic. Important ethical, legal and societal barriers associated with the implementation of digital health technologies in memory clinics need to be addressed. The envisioned Digitized Memory Clinic aims to improve diagnostics and enable precise disease-tracking prognostication for individuals with memory disorders and to open new possibilities, such as precision medicine for prevention and treatment.

Artificial intelligence for dementia-Applied models and digital health

INTRODUCTION

The use of applied modeling in dementia risk prediction, diagnosis, and prognostics will have substantial public health benefits, particularly as "deep phenotyping" cohorts with multi-omics health data become available.

METHODS

This narrative review synthesizes understanding of applied models and digital health technologies, in terms of dementia risk prediction, diagnostic discrimination, prognosis, and progression. Machine learning approaches show evidence of improved predictive power compared to standard clinical risk scores in predicting dementia, and the potential to decompose large numbers of variables into relatively few critical predictors.

RESULTS

This review focuses on key areas of emerging promise including: emphasis on easier, more transparent data sharing and cohort access; integration of high-throughput biomarker and electronic health record data into modeling; and progressing beyond the primary prediction of dementia to secondary outcomes, for example, treatment response and physical health.

DISCUSSION

Such approaches will benefit also from improvements in remote data measurement, whether cognitive (e.g., online), or naturalistic (e.g., watch-based accelerometry).

Performing arts as a non-pharmacological intervention for people with dementia and care-partners: a community case study

Participation in psychosocial enrichment activities, such as music and arts programming, have shown potential to delay or reduce functional decline - without adverse effects that can be associated with pharmaceuticals. The performing-arts programming described in this community case study was inspired by a community music program called B-Sharp Music Wellness, located in Phoenix, Arizona, which involved small groups of musicians who provided symphony performances for people with dementia. Our community programming sought to engage people with dementia and their informal care partner (typically a spouse) in existing performing-arts programs in their local community, providing social hours and season tickets for either symphony, dance (ballet), or non-musical theater performances. This case study describes the program history and design, including outcomes and lessons learned from the program evaluation of the last full season (2018-19) and partial season (2019-20), when the program was halted due to the COVID-19 pandemic. Program outcomes suggest strategies for, and benefits of, design for performing-arts programs as psychosocial interventions in other communities.

Computerized cognitive practice effects in relation to amyloid and tau in preclinical Alzheimer's disease: Results from a multi-site cohort

Scalable cognitive paradigms that provide metrics such as the Computerized Cognitive Composite (C3) may be sensitive enough to relate to Alzheimer's disease biomarkers in the preclinical clinically unimpaired (CU) stage. We examined CU older adults (n = 3287) who completed alternate versions of the C3 approximately 51 days apart. A subset of CU with abnormal amyloid also completed tau positron emission tomography (PET) imaging. C3 initial performance and practice effects were examined in relation to amyloid status and continuous regional tau burden. Initial C3 performance was associated with amyloid status across all participants, and with tau burden in the medial temporal lobe and early cortical regions in CU with abnormal amyloid. Short-term practice effects were associated with reduced tau in these regions in CU with abnormal amyloid, but were not associated with amyloid status. Thus, computerized cognitive testing repeated over a short follow-up period provides additional insights into early Alzheimer's disease processes.

Capturing Cognitive Aging in Vivo: Application of a Neuropsychological Framework for Emerging Digital Tools

As the global burden of dementia continues to plague our healthcare systems, efficient, objective, and sensitive tools to detect neurodegenerative disease and capture meaningful changes in everyday cognition are increasingly needed. Emerging digital tools present a promising option to address many drawbacks of current approaches, with contexts of use that include early detection, risk stratification, prognosis, and outcome measurement. However, conceptual models to guide hypotheses and interpretation of results from digital tools are lacking and are needed to sort and organize the large amount of continuous data from a variety of sensors. In this viewpoint, we propose a neuropsychological framework for use alongside a key emerging approach-digital phenotyping. The Variability in Everyday Behavior (VIBE) model is rooted in established trends from the neuropsychology, neurology, rehabilitation psychology, cognitive neuroscience, and computer science literature and links patterns of intraindividual variability, cognitive abilities, and everyday functioning across clinical stages from healthy to dementia. Based on the VIBE model, we present testable hypotheses to guide the design and interpretation of digital phenotyping studies that capture everyday cognition in vivo. We conclude with methodological considerations and future directions regarding the application of the digital phenotyping approach to improve the efficiency, accessibility, accuracy, and ecological validity of cognitive assessment in older adults.

Revisiting the seven pillars of RDoC

BACKGROUND

In 2013, a few years after the launch of the National Institute of Mental Health's Research Domain Criteria (RDoC) initiative, Cuthbert and Insel published a paper titled "Toward the future of psychiatric diagnosis: the seven pillars of RDoC." The RDoC project is a translational research effort to encourage new ways of studying psychopathology through a focus on disruptions in normal functions (such as reward learning or attention) that are defined jointly by observable behavior and neurobiological measures. The paper outlined the principles of the RDoC research framework, including emphases on research that acquires data from multiple measurement classes to foster integrative analyses, adopts dimensional approaches, and employs novel methods for ascertaining participants and identifying valid subgroups.

DISCUSSION

To mark the first decade of the RDoC initiative, we revisit the seven pillars and highlight new research findings and updates to the framework that are related to each. This reappraisal emphasizes the flexible nature of the RDoC framework and its application in diverse areas of research, new findings related to the importance of developmental trajectories within and across neurobehavioral domains, and the value of computational approaches for clarifying complex multivariate relations among behavioral and neurobiological systems.

CONCLUSION

The seven pillars of RDoC have provided a foundation that has helped to guide a surge of new studies that have examined neurobehavioral domains related to mental disorders, in the service of informing future psychiatric nosology. Building on this footing, future areas of emphasis for the RDoC project will include studying central-peripheral interactions, developing novel approaches to phenotyping for genomic studies, and identifying new targets for clinical trial research to facilitate progress in precision psychiatry.

Computerized paired associate learning performance and imaging biomarkers in older adults without dementia

This cross-sectional study examined whether performance on the computerized Paired Associate Learning (PAL) task from the Cambridge Neuropsychological Test Automated Battery is associated with amyloid positivity as measured by Positron Emission Tomography, regional volume composites as measured by Magnetic Resonance Imaging, and cognitive impairment. Participants from the BIOCARD Study (N = 73, including 62 cognitively normal and 11 with mild cognitive impairment; M age = 70 years) completed the PAL task, a comprehensive clinical and neuropsychological assessment, and neuroimaging as part of their annual study visit. In linear regressions covarying age, sex, years of education and diagnosis, higher PAL error scores were associated with amyloid positivity but not with medial temporal or cortical volume composites. By comparison, standard neuropsychological measures of episodic memory and global cognition were unrelated to amyloid positivity, but better performance on the verbal episodic memory measures was associated with larger cortical volume composites. Participants with mild cognitive impairment demonstrated worse cognitive performance on all of the cognitive measures, including the PAL task. These findings suggest that this computerized visual paired associate learning task may be more sensitive to amyloid positivity than standard neuropsychological tests, and may therefore be a promising tool for detecting amyloid positivity in non-demented participants.

Exploratory Research on Key Technology of Human-Computer Interactive 2.5-Minute Fast Digital Early Warning for Mild Cognitive Impairment

Objective. As the preclinical stage of Alzheimer’s disease (AD), Mild Cognitive Impairment (MCI) is characterized by hidden onset, which is difficult to detect early. Traditional neuropsychological scales are main tools used for assessing MCI. However, due to its strong subjectivity and the influence of many factors such as subjects’ educational background, language and hearing ability, and time cost, its accuracy as the standard of early screening is low. Therefore, the purpose of this paper is to propose a new key technology of fast digital early warning for MCI based on eye movement objective data analysis. Methodology. Firstly, four exploratory indexes (test durations, correlation degree, lengths of gaze trajectory, and drift rate) of MCI early warning are determined based on the relevant literature research and semistructured expert interview; secondly, the eye movement state is captured based on the eye tracker to realize the data extraction of four exploratory indexes. On this basis, the human-computer interactive 2.5-minute fast digital early warning paradigm for MCI is designed; thirdly, the rationality of the four early warning indexes proposed in this paper and their early warning effectiveness on MCI are verified. Results. Through the small sample test of human-computer interactive 2.5 fast digital early warning paradigm for MCI conducted by 32 elderly people aged 70–90 in a medical institution in Hangzhou, the two indexes of “correlation degree” and “drift rate” with statistical differences are selected. The experiment results show that AUC of this MCI early warning paradigm is 0.824. Conclusion. The key technology of human-computer interactive 2.5 fast digital early warning for MCI proposed in this paper overcomes the limitations of the existing MCI early warning tools, such as low objectification level, high dependence on professional doctors, long test time, requiring high educational level, and so on. The experiment results show that the early warning technology, as a new generation of objective and effective digital early warning tool, can realize 2.5-minute fast and high-precision preliminary screening and early warning for MCI in the elderly.

Monthly At-Home Computerized Cognitive Testing to Detect Diminished Practice Effects in Preclinical Alzheimer's Disease

Introduction: We investigated whether monthly assessments of a computerized cognitive composite (C3) could aid in the detection of differences in practice effects (PE) in clinically unimpaired (CU) older adults, and whether diminished PE were associated with Alzheimer's disease (AD) biomarkers and annual cognitive decline. Materials and Methods: N = 114 CU participants (age 77.6 ± 5.0, 61% female, MMSE 29 ± 1.2) from the Harvard Aging Brain Study completed the self-administered C3 monthly, at-home, on an iPad for one year. At baseline, participants underwent in-clinic Preclinical Alzheimer's Cognitive Composite-5 (PACC5) testing, and a subsample (n = 72, age = 77.8 ± 4.9, 59% female, MMSE 29 ± 1.3) had 1-year follow-up in-clinic PACC5 testing available. Participants had undergone PIB-PET imaging (0.99 ± 1.6 years before at-home baseline) and Flortaucipir PET imaging (n = 105, 0.62 ± 1.1 years before at-home baseline). Linear mixed models were used to investigate change over months on the C3 adjusting for age, sex, and years of education, and to extract individual covariate-adjusted slopes over the first 3 months. We investigated the association of 3-month C3 slopes with global amyloid burden and tau deposition in eight predefined regions of interest, and conducted Receiver Operating Characteristic analyses to examine how accurately 3-month C3 slopes could identify individuals that showed >0.10 SD annual decline on the PACC-5. Results: Overall, individuals improved on all C3 measures over 12 months (β = 0.23, 95% CI [0.21-0.25], p < 0.001), but improvement over the first 3 months was greatest (β = 0.68, 95% CI [0.59-0.77], p < 0.001), suggesting stronger PE over initial repeated exposures. However, lower PE over 3 months were associated with more global amyloid burden (r = -0.20, 95% CI [-0.38 - -0.01], p = 0.049) and tau deposition in the entorhinal cortex (r = -0.38, 95% CI [-0.54 - -0.19], p < 0.001) and inferior-temporal lobe (r = -0.23, 95% CI [-0.41 - -0.02], p = 0.03). 3-month C3 slopes exhibited good discriminative ability to identify PACC-5 decliners (AUC 0.91, 95% CI [0.84-0.98]), which was better than baseline C3 (p < 0.001) and baseline PACC-5 scores (p = 0.02). Conclusion: While PE are commonly observed among CU adults, diminished PE over monthly cognitive testing are associated with greater AD biomarker burden and cognitive decline. Our findings imply that unsupervised computerized testing using monthly retest paradigms can provide rapid detection of diminished PE indicative of future cognitive decline in preclinical AD.

Unsupervised mobile cognitive testing for use in preclinical Alzheimer's disease

INTRODUCTION

Unsupervised digital cognitive testing is an appealing means to capture subtle cognitive decline in preclinical Alzheimer's disease (AD). Here, we describe development, feasibility, and validity of the Boston Remote Assessment for Neurocognitive Health (BRANCH) against in-person cognitive testing and amyloid/tau burden.

METHODS

BRANCH is web-based, self-guided, and assesses memory processes vulnerable in AD. Clinically normal participants (n = 234; aged 50-89) completed BRANCH; a subset underwent in-person cognitive testing and positron emission tomography imaging. Mean accuracy across BRANCH tests (Categories, Face-Name-Occupation, Groceries, Signs) was calculated.

RESULTS

BRANCH was feasible to complete on participants' own devices (primarily smartphones). Technical difficulties and invalid/unusable data were infrequent. BRANCH psychometric properties were sound, including good retest reliability. BRANCH was correlated with in-person cognitive testing (r = 0.617, P < .001). Lower BRANCH score was associated with greater amyloid (r = -0.205, P = .007) and entorhinal tau (r = -0.178, P = .026).

DISCUSSION

BRANCH reliably captures meaningful cognitive information remotely, suggesting promise as a digital cognitive marker sensitive early in the AD trajectory.

Current advances in digital cognitive assessment for preclinical Alzheimer's disease

There is a pressing need to capture and track subtle cognitive change at the preclinical stage of Alzheimer's disease (AD) rapidly, cost-effectively, and with high sensitivity. Concurrently, the landscape of digital cognitive assessment is rapidly evolving as technology advances, older adult tech-adoption increases, and external events (i.e., COVID-19) necessitate remote digital assessment. Here, we provide a snapshot review of the current state of digital cognitive assessment for preclinical AD including different device platforms/assessment approaches, levels of validation, and implementation challenges. We focus on articles, grants, and recent conference proceedings specifically querying the relationship between digital cognitive assessments and established biomarkers for preclinical AD (e.g., amyloid beta and tau) in clinically normal (CN) individuals. Several digital assessments were identified across platforms (e.g., digital pens, smartphones). Digital assessments varied by intended setting (e.g., remote vs. in-clinic), level of supervision (e.g., self vs. supervised), and device origin (personal vs. study-provided). At least 11 publications characterize digital cognitive assessment against AD biomarkers among CN. First available data demonstrate promising validity of this approach against both conventional assessment methods (moderate to large effect sizes) and relevant biomarkers (predominantly weak to moderate effect sizes). We discuss levels of validation and issues relating to usability, data quality, data protection, and attrition. While still in its infancy, digital cognitive assessment, especially when administered remotely, will undoubtedly play a major future role in screening for and tracking preclinical AD.

Adapting Alzheimer Disease and Related Dementias Clinical Research Evaluations in the Age of COVID-19

In March 2020, the novel coronavirus (COVID-19) became a global pandemic that would cause most in-person visits for clinical studies to be put on pause. Coupled with protective stay at home guidelines, clinical research at the Icahn School of Medicine at Mount Sinai Alzheimer's Disease Research Center (ISMMS ADRC) needed to quickly adapt to remain operational and maintain our cohort of research participants. Data collected by the ISMMS ADRC as well as from other National Institute on Aging (NIA) Alzheimer Disease centers, follows the guidance of the National Alzheimer Coordinating Center (NACC). However, at the start of this pandemic, NACC had no alternative data collection mechanisms that could accommodate these safety guidelines. To stay in touch with our cohort and to ensure continued data collection under different stages of quarantine, the ISMMS ADRC redeployed their work force to continue their observational study via telehealth assessment. On the basis of this experience and that of other centers, NACC was able to create a data collection process to accommodate remote assessment in mid-August. Here we review our experience in filling the gap during this period of isolation and describe the adaptations for clinical research, which informed the national dialog for conducting dementia research in the age of COVID-19 and beyond.

A mobile app for delirium screening

OBJECTIVE

The objective of this study is to describe the algorithm and technical implementation of a mobile app that uses adaptive testing to assess an efficient mobile app for the diagnosis of delirium.

MATERIALS AND METHODS

The app was used as part of a NIH-funded project to assess the feasibility, effectiveness, administration time, and costs of the 2-step delirium identification protocol when performed by physicians and nurses, and certified nursing assistants (CNA). The cohort included 535 hospitalized patients aged 79.7 (SD = 6.6) years enrolled at 2 different sites. Each patient was assessed on 2 consecutive days by the research associate who performed the reference delirium assessment. Thereafter, physicians, nurses, and CNAs performed adaptive delirium assessments using the app. Qualitative data to assess the experience of administering the 2-step protocol, and the app usability were also collected and analyzed from 50 physicians, 189 nurses, and 83 CNAs. We used extensible hypertext markup language (XHTML) and JavaScript to develop the app for the iOS-based iPad. The App was linked to Research Electronic Data Capture (REDCap), a relational database system, via a REDCap application programming interface (API) that sent and received data from/to the app. The data from REDCap were sent to the Statistical Analysis System for statistical analysis.

RESULTS

The app graphical interface was successfully implemented by XHTML and JavaScript. The API facilitated the instant updating and retrieval of delirium status data between REDCap and the app. Clinicians performed 881 delirium assessments using the app for 535 patients. The transmission of data between the app and the REDCap system showed no errors. Qualitative data indicated that the users were enthusiastic about using the app with no negative comments, 82% positive comments, and 18% suggestions of improvement. Delirium administration time for the 2-step protocol showed similar total time between nurses and physicians (103.9 vs 106.5 seconds). Weekly enrollment reports of the app data were generated for study tracking purposes, and the data are being used for statistical analyses for publications.

DISCUSSION

The app developed using iOS could be easily converted to other operating systems such as Android and could be linked to other relational databases beside REDCap, such as electronic health records to facilitate better data retrieval and updating of patient's delirium status.

CONCLUSION

Our app operationalizes an adaptive 2-step delirium screening protocol. Its algorithm and cross-plat formed code of XHTML and JavaScript can be easily exported to other operating systems and hardware platforms, thus enabling wider use of the efficient delirium screening protocol that we have developed. The app is currently implemented as a research tool, but with adaptation could be implemented in the clinical setting to facilitate widespread delirium screening in hospitalized older adults.

Feasibility and validation of a web-based platform for the self-administered patient collection of demographics, health status, anxiety, depression, and cognition in community dwelling elderly

The coronavirus disease pandemic has brought a new urgency for the development and deployment of web-based applications which complement, and offer alternatives to, traditional one-on-one consultations and pencil-and-paper (PaP) based assessments that currently dominate clinical research. We have recently developed a web-based application that can be used for the self-administered collection of patient demographics, self-rated health, depression and anxiety, and cognition as part of a single platform. In this study we report the findings from a study with 155 cognitively healthy older adults who received established PaP versions, as well as our novel computerized measures of self-rated health, depression and anxiety, and cognition. Moderate to high correlations were observed between PaP and web- based measures of self-rated health (r = 0.77), depression and anxiety (r = 0.72), and preclinical Alzheimer’s disease cognitive composite (PACC) (r = .61). Test-retest correlations were variable with high correlations for a measure of processing speed and a measure of delayed episodic memory. Taken together, these data support the feasibility and validity of utilization of this novel web-based platform as a new alternative for collecting patient demographics and the assessment of self-rated health, depression and anxiety, and cognition in the elderly.

Diminished Learning Over Repeated Exposures (LORE) in preclinical Alzheimer's disease

INTRODUCTION

We determine whether diminished Learning Over Repeated Exposures (LORE) identifies subtle memory decrements in cognitively unimpaired (CU) older adults with Alzheimer's disease (AD) biomarker burden.

METHODS

Ninety-four CU participants (mean age = 77.6 ± 5.02) completed a challenging associative memory test, at home, monthly, for up to 1 year (mean = 9.97 months) on a study-issued iPad. Learning curves for face-name memory were computed for two versions completed monthly: same face-name pairs (A-A-A) and alternate face-name pairs (B-C-D). Positron emission tomography (PET) imaging characterized global amyloid (Pittsburgh Compound-B (PiB); amyloid beta (Aβ)+/-) and regional tau burden (flortaucipir).

RESULTS

Diminished LORE for same (but not alternate) face-name pairs was associated with greater amyloid and tau burden. Aβ+/- group differences for same face-name pairs emerged by the fourth exposure and was of medium-to-large magnitude (Cohen's d = 0.66; 95% confidence interval [CI] = 0.25-1.08).

DISCUSSION

Subtle decrements in learning related to AD pathological burden in CU are detectable over short time-intervals (ie, months). Implications for prevention trial design are discussed.

A Novel Computerized Cognitive Stress Test to Detect Mild Cognitive Impairment

BACKGROUND

The Loewenstein Acevedo Scales of Semantic Interference and Learning (LASSI-L) is a novel and increasingly employed instrument that has outperformed widely used cognitive measures as an early correlate of elevated brain amyloid and neurodegeneration in prodromal Alzheimer's Disease (AD). The LASSI-L has distinguished those with amnestic mild cognitive impairment (aMCI) and high amyloid load from aMCI attributable to other non-AD conditions. The authors designed and implemented a web-based brief computerized version of the instrument, the LASSI-BC, to improve standardized administration, facilitate scoring accuracy, real-time data entry, and increase the accessibility of the measure.

OBJECTIVE

The psychometric properties and clinical utility of the brief computerized version of the LASSI-L was evaluated, together with its ability to differentiate older adults who are cognitively normal (CN) from those with amnestic Mild Cognitive Impairment (aMCI).

METHODS

After undergoing a comprehensive uniform clinical and neuropsychological evaluation using traditional measures, older adults were classified as cognitively normal or diagnosed with aMCI. All participants were administered the LASSI-BC, a computerized version of the LASSI-L. Test-retest and discriminant validity was assessed for each LASSI-BC subscale.

RESULTS

LASSI-BC subscales demonstrated high test-retest reliability, and discriminant validity was attained.

CONCLUSIONS

The LASSI-BC, a brief computerized version of the LASSI-L is a valid and useful cognitive tool for the detection of aMCI among older adults.

The Computerized Cognitive Composite (C3) in an Alzheimer's Disease Secondary Prevention Trial

BACKGROUND

Computerized cognitive assessments may improve Alzheimer's disease (AD) secondary prevention trial efficiency and accuracy. However, they require validation against standard outcomes and relevant biomarkers.

OBJECTIVE

To assess the feasibility and validity of the tablet-based Computerized Cognitive Composite (C3).

DESIGN

Cross-sectional analysis of cognitive screening data from the A4 study (Anti-Amyloid in Asymptomatic AD).

SETTING

Multi-center international study.

PARTICIPANTS

Clinically normal (CN) older adults (65-85; n=4486).

MEASUREMENTS

Participants underwent florbetapir-Positron Emission Tomography for Aβ+/- classification. They completed the C3 and standard paper and pencil measures included in the Preclinical Alzheimer's Cognitive Composite (PACC). The C3 combines memory measures sensitive to change over time (Cogstate Brief Battery-One Card Learning) and measures shown to be declining early in AD including pattern separation (Behavioral Pattern Separation Test- Object- Lure Discrimination Index) and associative memory (Face Name Associative Memory Exam- Face-Name Matching). C3 acceptability and completion rates were assessed using qualitative and quantitative methods. C3 performance was explored in relation to Aβ+/- groups (n=1323/3163) and PACC.

RESULTS

C3 was feasible for CN older adults to complete. Rates of incomplete or invalid administrations were extremely low, even in the bottom quartile of cognitive performers (PACC). C3 was moderately correlated with PACC (r=0.39). Aβ+ performed worse on C3 compared with Aβ- [unadjusted Cohen's d=-0.22 (95%CI: -0.31,-0.13) p<0.001] and at a magnitude comparable to the PACC [d=-0.32 (95%CI: -0.41,-0.23) p<0.001]. Better C3 performance was observed in younger, more educated, and female participants.

CONCLUSIONS

These findings provide support for both the feasibility and validity of C3 and computerized cognitive outcomes more generally in AD secondary prevention trials.

The Number Symbol Coding Task: A brief measure of executive function to detect dementia and cognitive impairment

INTRODUCTION

Alzheimer's disease and related dementias (ADRD) affect over 5.7 million Americans and over 35 million people worldwide. Detection of mild cognitive impairment (MCI) and early ADRD is a challenge to clinicians and researchers. Brief assessment tools frequently emphasize memory impairment, however executive dysfunction may be one of the earliest signs of impairment. To address the need for a brief, easy-to-score, open-access test of executive function for use in clinical practice and research, we created the Number Symbol Coding Task (NSCT).

METHODS

This study analyzed 320 consecutive patient-caregiver dyads who underwent a comprehensive evaluation including the Clinical Dementia Rating (CDR), patient and caregiver versions of the Quick Dementia Rating System (QDRS), caregiver ratings of behavior and function, and neuropsychological testing, with a subset undergoing volumetric magnetic resonance imaging (MRI). Estimates of cognitive reserve were calculated using education, combined indices of education and occupation, and verbal IQ. Psychometric properties of the NSCT including data quality, data distribution, floor and ceiling effects, construct and known-groups validity, discriminability, and clinical profiles were determined.

RESULTS

The patients had a mean age of 75.3±9.2 years (range 38-98y) with a mean education of 15.7±2.8 years (range 6-26y) of education. The patients had a mean CDR-SB of 4.8±4.7 (range 0-18) and a mean MoCA score of 18.6±7.1 (range 1-30). The mean NSCT score was 30.1±13.8 and followed a normal distribution. All healthy controls and MCI cases were able to complete the NSCT. The NSCT showed moderate-to-strong correlations with clinical and neuropsychological measures with the strongest association (all p's < .001) for measures with executive components (e.g., Judgement and Problem Solving box of the CDR, Decision Making and Problem Solving domain of the QDRS, Trailmaking B, and Cognigram Attention and Executive Composite Scores). Women slightly outperformed men, and individuals with lower educational attainment and lower education-occupation indices had lower NSCT scores. Decreasing NSCT scores corresponded to older age, worse cognitive scores, higher CDR sum of boxes scores, worse caregiver ratings of function and behavior, worse patient and informant QDRS ratings, and smaller hippocampal volumes and hippocampal occupancy scores. The NSCT provided excellent discrimination (AUC: .866; 95% CI: .82-.91) with a cut-off score of 36 providing the best combination of sensitivity (0.880) and specificity (0.759). Combining the NSCT with patient QDRS and caregiver QDRS ratings improved discrimination (AUC: .908; 95% CI: .87-.94).

DISCUSSION

The NSCT is a brief, 90-second executive task that incorporates attention, planning and set-switching that can be completed by individuals into the moderate-to-severe stages of dementia. The NSCT may be a useful tool for dementia screening, case-ascertainment in epidemiological or community-based ADRD studies, and in busy primary care settings where time is limited. Combining the NSCT with a brief structured interview tool such as the QDRS may provide excellent power to detect cognitive impairment. The NSCT performed well in comparison to standardized scales of a comprehensive cognitive neurology evaluation across a wide array of sociodemographic variables in a brief fashion that could facilitate its use in clinical care and research.

Randomized Clinical Trial Examining the Impact of Lactobacillus rhamnosus GG Probiotic Supplementation on Cognitive Functioning in Middle-aged and Older Adults

PURPOSE

The gut microbiome has been linked to cognitive function and appears to worsen with aging. Probiotic supplementation has been found to improve the health of the gut microbiome. As such, it is possible that probiotic supplementation may protect the aging brain. The current study examined the cognitive benefits of probiotic supplementation (Lactobacillus rhamnosus GG) in healthy middle-aged and older adults.

MATERIALS AND METHODS

The study was a double-blind, placebo-controlled, randomized clinical trial. Two hundred community-dwelling adults aged 52-75 were enrolled (mean age=64.3, SD=5.52). A three-month intervention involved daily consumption of probiotic or placebo. Independent sample t-tests, chi-squared tests, and repeated measure ANOVAs compared groups and examined changes over time. Primary outcome was change in NIH Toolbox Total Cognition Score from baseline to follow-up.

RESULTS

A total of 145 participants were examined in primary analyses (probiotic=77, placebo=68) and excluded persons due to discontinuation, low adherence, missing data, or outlier values. Established criteria (ie ≥1 subtest t-scores ≤35; n=19, n=23) were used to operationally define cognitive impairment. Repeated measures ANOVAs revealed that persons with cognitive impairment who consumed probiotics exhibited a greater total cognition score improvement than persons with cognitive impairment in the placebo group and cognitively intact persons in probiotic or placebo groups.

CONCLUSION

Lactobacillus rhamnosus GG probiotic supplementation was associated with improved cognitive performance in middle-aged and older adults with cognitive impairment. Probiotic supplementation may be a novel method for protecting cognitive health in aging.

Associations between NIH Toolbox Cognition Battery and in vivo brain amyloid and tau pathology in non-demented older adults

INTRODUCTION

The National Institutes of Health (NIH) Toolbox Cognition Battery (NIHTB-CB) was developed to be a common assessment metric across a broad array of research studies. We investigated associations between NIHTB-CB and brain amyloid and tau deposition in cognitively unimpaired older adults.

METHODS

One hundred eighteen community-based volunteers completed magnetic resonance imaging (MRI), Pittsburgh compound B (PiB)-PET (positron emission tomography) and AV-1451-PET neuroimaging, a neuropsychological evaluation, NIHTB-CB, and the Clinical Dementia Rating (CDR) scale. Demographically adjusted regression models evaluated cognition-biomarker associations; standardized effect sizes allowed comparison of association strength across measures.

RESULTS

No NIHTB-CB measures were associated with amyloid deposition. NIHTB-CB measures of fluid cognition, including Pattern Comparison Processing Speed, Dimensional Change Card Sort, and Fluid Cognition Composite, were associated with tau deposition in higher Braak regions. Pattern Comparison Processing Speed was the most robust association with sensitivity analyses.

DISCUSSION

NIHTB-CB tasks of processing speed and executive functions may be sensitive to pathologic tau deposition on imaging in normal aging.

Diagnostic and Prognostic Accuracy of the Cogstate Brief Battery and Auditory Verbal Learning Test in Preclinical Alzheimer's Disease and Incident Mild Cognitive Impairment: Implications for Defining Subtle Objective Cognitive Impairment

BACKGROUND

There are detectable cognitive differences in cognitively unimpaired (CU) individuals with preclinical Alzheimer's disease (AD).

OBJECTIVE

To determine whether cross-sectional performance on the Cogstate Brief Battery (CBB) and Auditory Verbal Learning Test (AVLT) could identify 1) CU participants with preclinical AD defined by neuroimaging biomarkers of amyloid and tau, and 2) incident mild cognitive impairment (MCI)/dementia.

METHOD

CU participants age 50+ were eligible if they had 1) amyloid (A) and tau (T) imaging within two years of their baseline CBB or 2) at least one follow-up visit. AUROC analyses assessed the ability of measures to differentiate groups. We explored the frequency of cross-sectional subtle objective cognitive impairment (sOBJ) defined as performance ≤-1 SD on CBB Learning/Working Memory Composite (Lrn/WM) or AVLT delayed recall using age-corrected normative data.

RESULTS

A+T+ (n = 33, mean age 79.5) and A+T- (n = 61, mean age 77.8) participants were older than A-T- participants (n = 146, mean age 66.3), and comparable on sex and education. Lrn/WM did not differentiate A + T+or A+T- from A-T- participants. AVLT differentiated both A+T+ and A+T- from A-T- participants; 45% of A+T+ and 25% of A+T- participants met sOBJ criteria. The follow-up cohort included 150 CU individuals who converted to MCI/dementia and 450 age, sex, and education matched controls. Lrn/WM and AVLT differentiated between stable and converter CU participants.

CONCLUSION

Among CU participants, AVLT helped differentiate A+T+ and A+T- from A-T- participants. The CBB did not differentiate biomarker subgroups, but showed potential for predicting incident MCI/dementia. Results inform future definitions of sOBJ.

Neurocognitive and functional impairment in adult and paediatric tuberculous meningitis

In those who survive tuberculous meningitis (TBM), the long-term outcome is uncertain; individuals may suffer neurocognitive, functional and psychiatric impairment, which may significantly affect their ability to lead their lives as they did prior to their diagnosis of TBM. In children who survive, severe illness has occurred at a crucial timepoint in their development, which can lead to behavioural and cognitive delay. The extent and nature of this impairment is poorly understood, particularly in adults. This is in part due to a lack of observational studies in this area but also inconsistent inclusion of outcome measures which can quantify these deficits in clinical studies. This leads to a paucity of appropriate rehabilitative therapies available for these individuals and their caregivers, as well as burden at a socioeconomic level. In this review, we discuss what is known about neurocognitive impairment in TBM, draw on lessons learnt from other neurological infections and discuss currently available and emerging tools to evaluate function and cognition and their value in TBM. We make recommendations on which measures should be used at what timepoints to assess for impairment, with a view to optimising and standardising assessment of neurocognitive and functional impairment in TBM research.

Psychometric Properties of the NIH Toolbox Cognition Battery in Healthy Older Adults: Reliability, Validity, and Agreement with Standard Neuropsychological Tests

OBJECTIVE

Few independent studies have examined the psychometric properties of the NIH Toolbox Cognition Battery (NIHTB-CB) in older adults, despite growing interest in its use for clinical purposes. In this paper we report the test-retest reliability and construct validity of the NIHTB-CB, as well as its agreement or concordance with traditional neuropsychological tests of the same construct to determine whether tests could be used interchangeably.

METHODS

Sixty-one cognitively healthy adults ages 60-80 completed "gold standard" (GS) neuropsychological tests, NIHTB-CB, and brain MRI. Test-retest reliability, convergent/discriminant validity, and agreement statistics were calculated using Pearson's correlations, concordance correlation coefficients (CCC), and root mean square deviations.

RESULTS

Test-retest reliability was acceptable (CCC = .73 Fluid; CCC = .85 Crystallized). The NIHTB-CB Fluid Composite correlated significantly with cerebral volumes (r's = |.35-.41|), and both composites correlated highly with their respective GS composites (r's = .58-.84), although this was more variable for individual tests. Absolute agreement was generally lower (CCC = .55 Fluid; CCC = .70 Crystallized) due to lower precision in fluid scores and systematic overestimation of crystallized composite scores on the NIHTB-CB.

CONCLUSIONS

These results support the reliability and validity of the NIHTB-CB in healthy older adults and suggest that the fluid composite tests are at least as sensitive as standard neuropsychological tests to medial temporal atrophy and ventricular expansion. However, the NIHTB-CB may generate different estimates of performance and should not be treated as interchangeable with established neuropsychological tests.

Biomarker-Based Signature of Alzheimer's Disease in Pre-MCI Individuals

Alzheimer’s disease (AD) pathology begins decades before the onset of clinical symptoms. It is recognized as a clinicobiological entity, being detectable in vivo independently of the clinical stage by means of pathophysiological biomarkers. Accordingly, neuropathological studies that were carried out on healthy elderly subjects, with or without subjective experience of cognitive decline, reported evidence of AD pathology in a high proportion of cases. At present, mild cognitive impairment (MCI) represents the only clinically diagnosed pre-dementia stage. Several attempts have been carried out to detect AD as early as possible, when subtle cognitive alterations, still not fulfilling MCI criteria, appear. Importantly, pre-MCI individuals showing the positivity of pathophysiological AD biomarkers show a risk of progression similar to MCI patients. In view of successful treatment with disease modifying agents, in a clinical setting, a timely diagnosis is mandatory. In clinical routine, biomarkers assessment should be taken into consideration whenever a subject with subtle cognitive deficits (pre-MCI), who is aware of his/her decline, requests to know the cause of such disturbances. In this review, we report the available neuropsychological and biomarkers data that characterize the pre-MCI patients, thus proposing pre-MCI as the first clinical manifestation of AD.

Utility of the NIH Toolbox for assessment of prodromal Alzheimer's disease and dementia

INTRODUCTION

The NIH Toolbox Cognition Battery (NIHTB-CB) is a computer-based protocol not yet validated for clinical assessment.

METHODS

We administered the NIHTB-CB and traditional neuropsychological tests to 247 Memory Disorders and Alzheimer's Prevention Clinic patients with subjective cognitive decline, mild cognitive impairment, mild dementia due to Alzheimer's disease, and normal cognition. Principal component analysis, partial correlations, and univariate general linear model tests were performed to assess construct validity. Discriminant function analyses compared classification accuracy.

RESULTS

Principal component analysis identified three conceptually coherent factors: memory (MEMNIH), executive function (EFNIH), and crystallized intelligence (CINIH). These factors were strongly associated with corresponding traditional tests and differed across diagnostic groups as expected. Both NIHTB and traditional batteries yielded strong overall discriminative ability (>80%).

DISCUSSION

The NIHTB-CB is a valid method to assess neurocognitive domains pertinent to aging and dementia and has utility for applications in a memory clinic setting.

EU/US/CTAD Task Force: Lessons Learned from Recent and Current Alzheimer's Prevention Trials

At a meeting of the EU/US/Clinical Trials in Alzheimer's Disease (CTAD) Task Force in December 2016, an international group of investigators from industry, academia, and regulatory agencies reviewed lessons learned from ongoing and planned prevention trials, which will help guide future clinical trials of AD treatments, particularly in the pre-clinical space. The Task Force discussed challenges that need to be addressed across all aspects of clinical trials, calling for innovation in recruitment and retention, infrastructure development, and the selection of outcome measures. While cognitive change provides a marker of disease progression across the disease continuum, there remains a need to identify the optimal assessment tools that provide clinically meaningful endpoints. Patient- and informant-reported assessments of cognition and function may be useful but present additional challenges. Imaging and other biomarkers are also essential to maximize the efficiency of and the information learned from clinical trials.

Device-Embedded Cameras for Eye Tracking-Based Cognitive Assessment: Validation With Paper-Pencil and Computerized Cognitive Composites

BACKGROUND

As eye tracking-based assessment of cognition becomes more widely used in older adults, particularly those at risk for dementia, reliable and scalable methods to collect high-quality data are required. Eye tracking-based cognitive tests that utilize device-embedded cameras have the potential to reach large numbers of people as a screening tool for preclinical cognitive decline. However, to fully validate this approach, more empirical evidence about the comparability of eyetracking-based paradigms to existing cognitive batteries is needed.

OBJECTIVE

Using a population of clinically normal older adults, we examined the relationship between a 30-minute Visual Paired Comparison (VPC) recognition memory task and cognitive composite indices sensitive to a subtle decline in domains associated with Alzheimer disease. Additionally, the scoring accuracy between software used with a commercial grade eye tracking camera at 60 frames per second (FPS) and a manually scored procedure used with a laptop-embedded web camera (3 FPS) on the VPC task was compared, as well as the relationship between VPC task performance and domain-specific cognitive function.

METHODS

A group of 49 clinically normal older adults completed a 30-min VPC recognition memory task with simultaneous recording of eye movements by a commercial-grade eye-tracking camera and a laptop-embedded camera. Relationships between webcam VPC performance and the Preclinical Alzheimer Cognitive Composite (PACC) and National Institutes of Health Toolbox Cognitive Battery (NIHTB-CB) were examined. Inter-rater reliability for manually scored tests was analyzed using Krippendorff's kappa formula, and we used Spearman's Rho correlations to investigate the relationship between VPC performance scores with both cameras. We also examined the relationship between VPC performance with the device-embedded camera and domain-specific cognitive performance.

RESULTS

Modest relationships were seen between mean VPC novelty preference and the PACC (r=.39, P=.007) and NIHTB-CB (r=.35, P=.03) composite scores, and additional individual neurocognitive task scores including letter fluency (r=.33, P=.02), category fluency (r=.36, P=.01), and Trail Making Test A (-.40, P=.006). Robust relationships were observed between the 60 FPS eye tracker and 3 FPS webcam on both trial-level VPC novelty preference (r=.82, P<.001) and overall mean VPC novelty preference (r=.92 P<.001). Inter-rater agreement of manually scored web camera data was high (kappa=.84).

CONCLUSIONS

In a sample of clinically normal older adults, performance on a 30-minute VPC task correlated modestly with computerized and paper-pencil based cognitive composites that serve as preclinical Alzheimer disease cognitive indices. The strength of these relationships did not differ between camera devices. We suggest that using a device-embedded camera is a reliable and valid way to assess performance on VPC tasks accurately and that these tasks correlate with existing cognitive composites.

Patient perspectives of the experience of a computerized cognitive assessment in a clinical setting

INTRODUCTION

Computerized assessments are becoming widely accepted in the clinical setting and as a potential outcome measure in clinical trials. To gain patient perspectives of this experience, the aim of the present study was to investigate patient attitudes and perceptions of the Cognigram [Cogstate], a computerized cognitive assessment.

METHODS

Semi-structured interviews were conducted with 19 older adults undergoing a computerized cognitive assessment at the University of British Columbia Hospital Clinic for Alzheimer Disease and Related Disorders. Thematic analysis was applied to identify key themes and relationships within the data.

RESULTS

The analysis resulted in three categories: attitudes toward computers in healthcare, the cognitive assessment process, and evaluation of the computerized assessment experience. The results show shared views on the need for balance between human and computer intervention, as well as room for improvement in test design and utility.

DISCUSSION

Careful design and user-testing should be made a priority in the development of computerized assessment interfaces, as well as reevaluating the cognitive assessment process to minimize patient anxiety and discomfort. Future research should move toward continuous data capture within clinical trials and ensuring instruments of high reliability to reduce variance.