The MemTrax Test Compared to the Montreal Cognitive Assessment Estimation of Mild Cognitive Impairment

Boston Naming Test as a Screening Tool for Early Postoperative Cognitive Dysfunction in Elderly Patients After Major Noncardiac Surgery

PURPOSE

The Boston naming test (BNT), as a simple, fast, and easily administered neuropsychological test, was demonstrated to be useful in detecting language function. In this study, BNT was investigated whether it could be a screening tool for early postoperative cognitive dysfunction (POCD).

METHODS

This prospective observational cohort study included 132 major noncardiac surgery patients and 81 nonsurgical controls. All participants underwent a mini-mental state examination (MMSE) and BNT 1 day before and 7 days after surgery. Early POCD was assessed by reliable change index and control group results.

RESULTS

Seven days after surgery, among 132 patients, POCD was detected in 30 (22.7%) patients (95% CI, 15.5%-30.0%) based on MMSE, and 45 (34.1%) patients (95% CI, 26.3%-41.9%) were found with postoperative language function decline based on BNT and MMSE. Agreement between the BNT spontaneous naming and MMSE total scoring was moderate (Kappa .523), and the sensitivity of BNT spontaneous naming for detecting early POCD was .767. Further analysis showed that areas under receiver operating characteristics curves (AUC) did not show statistically significant differences when BNT spontaneous naming (AUC .862) was compared with MMSE language functional subtests (AUC .889), or non-language functional subtests (AUC .933).

CONCLUSION

This study indicates the feasibility of implementing the BNT spontaneous naming test to screen early POCD in elderly patients after major noncardiac surgery.

Toward better understanding and management of chemobrain: the potential utilities of the MemTrax memory test

OBJECTIVE

To study the effects of chemotherapy on cognitive function in breast cancer patients, and to investigate the relationship of MemTrax test of memory and related functions to the FACT-Cog functional self-assessment for the evaluation and management of chemobrain.

METHODS

In this prospective cohort study, clinical information of pathologically confirmed female breast cancer patients who decided to receive chemotherapy were collected in a questionnaire which was developed for this study and provided as a supplementary file. The FACT-Cog self-assessment and MemTrax test were administered before and after the chemotherapy treatments. Patients with chemobrain were identified using published criteria based on FACT-Cog scores, and MemTrax scores from chemobrain patients were analyzed.

RESULTS

Fifty-six patients participated in this study, of which 41 participants completed 4 or more cycles of chemotherapy and were included in the final analyses here. Using the reported high end of minimal clinical differences (10.6 points) of FACT-Cog before and after chemotherapy, 18 patients suffered from chemobrain in this study. In these 18 chemobrain patients, no cognitive impairments were detected by MemTrax, which paradoxically demonstrated an improvement in the normal cognitive range.

CONCLUSION

The cognitive impairment induced by chemotherapy in breast cancer patients is detectable by the FACT-Cog in a Chinese cohort but is not detected by the MemTrax memory test. The fact that the more objective MemTrax could not detect the impairment could alleviate patients' concerns which in turn would be beneficial for patients' mental health.

Addressing cortex dysregulation in youth through brain health check coaching and prophylactic brain development

The Carter Center has estimated that the addiction crisis in the United States (US), if continues to worsen at the same rate, may cost the country approximately 16 trillion dollars by 2030. In recent years, the well-being of youth has been compromised by not only the coronavirus disease 2019 pandemic but also the alarming global opioid crisis, particularly in the US. Each year, deadly opioid drugs claim hundreds of thousands of lives, contributing to an ever-rising death toll. In addition, maternal usage of opioids and other drugs during pregnancy could compromise the neurodevelopment of children. A high rate of DNA polymorphic antecedents compounds the occurrence of epigenetic insults involving methylation of specific essential genes related to normal brain function. These genetic antecedent insults affect healthy DNA and mRNA transcription, leading to a loss of proteins required for normal brain development and function in youth. Myelination in the frontal cortex, a process known to extend until the late 20s, delays the development of proficient executive function and decision-making abilities. Understanding this delay in brain development, along with the presence of potential high-risk antecedent polymorphic variants or alleles and generational epigenetics, provides a clear rationale for embracing the Brain Research Commission's suggestion to mimic fitness programs with an adaptable brain health check (BHC). Implementing the BHC within the educational systems in the US and other countries could serve as an effective initiative for proactive therapies aimed at reducing juvenile mental health problems and eventually criminal activities, addiction, and other behaviors associated with reward deficiency syndrome.

Episodic memory assessment: effects of sex and age on performance and response time during a continuous recognition task

Introduction

Continuous recognition tasks (CRTs) assess episodic memory (EM), the central functional disturbance in Alzheimer's disease and several related disorders. The online MemTrax computerized CRT provides a platform for screening and assessment that is engaging and can be repeated frequently. MemTrax presents complex visual stimuli, which require complex involvement of the lateral and medial temporal lobes and can be completed in less than 2 min. Results include number of correct recognitions (HITs), recognition failures (MISSes = 1-HITs), correct rejections (CRs), false alarms (FAs = 1-CRs), total correct (TC = HITs + CRs), and response times (RTs) for each HIT and FA. Prior analyses of MemTrax CRT data show no effects of sex but an effect of age on performance. The number of HITs corresponds to faster RT-HITs more closely than TC, and CRs do not relate to RT-HITs. RT-HITs show a typical skewed distribution, and cumulative RT-HITs fit a negative survival curve (RevEx). Thus, this study aimed to define precisely the effects of sex and age on HITS, CRs, RT-HITs, and the dynamics of RTs in an engaged population.

Methods

MemTrax CRT online data on 18,255 individuals was analyzed for sex, age, and distributions of HITs, CRs, MISSes, FAs, TC, and relationships to both RT-HITs and RT-FAs.

Results

HITs corresponded more closely to RT-HITs than did TC because CRs did not relate to RT-HITs. RT-FAs had a broader distribution than RT-HITs and were faster than RT-HITs in about half of the sample, slower in the other half. Performance metrics for men and women were the same. HITs declined with age as RT-HITs increased. CRs also decreased with age and RT-FAs increased, but with no correlation. The group over aged 50 years had RT-HITs distributions slower than under 50 years. For both age ranges, the RevEx model explained more than 99% of the variance in RT-HITs.

Discussion

The dichotomy of HITs and CRs suggests opposing cognitive strategies: (1) less certainty about recognitions, in association with slower RT-HITs and lower HIT percentages suggests recognition difficulty, leading to more MISSes, and (2) decreased CRs (more FAs) but faster RTs to HITs and FAs, suggesting overly quick decisions leading to errors. MemTrax CRT performance provides an indication of EM (HITs and RT-HITs may relate to function of the temporal lobe), executive function (FAs may relate to function of the frontal lobe), processing speed (RTs), cognitive ability, and age-related changes. This CRT provides potential clinical screening utility for early Alzheimer's disease and other conditions affecting EM, other cognitive functions, and more accurate impairment assessment to track changes over time.

The MemTrax memory test for detecting and assessing cognitive impairment in Parkinson's disease

INTRODUCTION

A valid, reliable, accessible measurement for the early detection of cognitive decline in patients with Parkinson's disease (PD) is in urgent demand. The objective of the study is to assess the clinical utility of the MemTrax Memory Test in detecting cognitive impairment in patients with PD.

METHODS

The MemTrax, a fast on-line cognitive screening tool based on continuous recognition task, and Montreal Cognitive Assessment (MoCA) were administered to 61 healthy controls (HC), 102 PD patients with normal cognition (PD-N), 74 PD patients with mild cognitive impairment (PD-MCI) and 52 PD patients with dementia (PD-D). The total percent correct (MTx- %C), average response time (MTx-RT), composite score (MTx-Cp) of MemTrax and the MoCA scores were comparatively analyzed.

RESULTS

The MoCA scores were similar between HC and PD-N, however, MTx- %C and MTx-Cp were lower in PD-N than HC(p < 0.05). MTx- %C, MTx-Cp and the MoCA scores were significantly lower in PD-MCI versus PD-N and in PD-D versus PD-MCI (p ≤ 0.001), while MTx-RT was statistically longer in PD-D versus PD-MCI (p ≤ 0.001). For PD groups, the MemTrax performance correlated with the MoCA scores. To detect PD-MCI, the optimal MTx- %C and MTx-Cp cutoff were 75 % and 50.0, respectively. To detect PD-D, the optimal MTx- %C, MTx-RT and MTx-Cp cutoff were 69 %, 1.341s and 40.6, respectively.

CONCLUSION

The MemTrax provides rapid, valid and reliable metrics for assessing cognition in PD patients which could be useful for identifying PD-MCI at early stage and monitoring cognitive function decline during the progression of disease.

Validity and Reliability Study of Online Cognitive Tracking Software (BEYNEX)

Background

Detecting cognitive impairment such as Alzheimer's disease early and tracking it over time is essential for individuals at risk of cognitive decline.

Objective

This research aimed to validate the Beynex app's gamified assessment tests and the Beynex Performance Index (BPI) score, which monitor cognitive performance across seven categories, considering age and education data.

Methods

Beynex test cut-off scores of participants (n = 91) were derived from the optimization function and compared to the Montreal Cognitive Assessment (MoCA) test. Validation and reliability analyses were carried out with data collected from an additional 214 participants.

Results

Beynex categorization scores showed a moderate agreement with MoCA ratings (weighted Cohen's Kappa = 0.48; 95% CI: 0.38-0.60). Calculated Cronbach's Alpha indicates good internal consistency. Test-retest reliability analysis using a linear regression line fitted to results yielded R∧2 of 0.65 with a 95% CI: 0.58, 0.71.

Discussion

Beynex's ability to reliably detect and track cognitive impairment could significantly impact public health, early intervention strategies and improve patient outcomes.

Toward digitally screening and profiling AD: A GAMLSS approach of MemTrax in China

PURPOSES

To establish a normative range of MemTrax (MTx) metrics in the Chinese population.

METHODS

The correct response percentage (MTx-%C) and mean response time (MTx-RT) were obtained and the composite scores (MTx-Cp) calculated. Generalized additive models for location, shape and scale (GAMLSS) were applied to create percentile curves and evaluate goodness of fit, and the speed-accuracy trade-off was investigated.

RESULTS

26,633 subjects, including 13,771 (51.71%) men participated in this study. Age- and education-specific percentiles of the metrics were generated. Q tests and worm plots indicated adequate fit for models of MTx-RT and MTx-Cp. Models of MTx-%C for the low and intermediate education fit acceptably, but not well enough for a high level of education. A significant speed-accuracy trade-off was observed for MTx-%C from 72 to 94.

CONCLUSIONS

GAMLSS is a reliable method to generate smoothed age- and education-specific percentile curves of MTx metrics, which may be adopted for mass screening and follow-ups addressing Alzheimer's disease or other cognitive diseases.

HIGHLIGHTS

GAMLSS was applied to establish nonlinear percentile curves of cognitive decline. Subjects with a high level of education demonstrate a later onset and slower decline of cognition. Speed-accuracy trade-off effects were observed in a subgroup with moderate accuracy. MemTrax can be used as a mass-screen instrument for active cognition health management advice.

Using MemTrax memory test to screen for post-stroke cognitive impairment after ischemic stroke: a cross-sectional study

Background

Whereas the Montreal Cognitive Assessment (MoCA) and Addenbrooke's cognitive examination-revised (ACE-R) are commonly used tests for the detection of post-stroke cognitive impairment (PSCI), these instruments take 10-30 min to administer and do not assess processing speed, which is a critical impairment in PSCI. MemTrax (MTx) is a continuous recognition test, which evaluates complex information processing, accuracy, speed, and attention, in 2 min.

Aim

To evaluate whether MTx is an effective and practical tool for PSCI assessment.

Methods

This study enrolled acute ischemic stroke (AIS) patients who have assessed the cognitive status including MTx, clinical dementia rating (CDR), MoCA, Neuropsychiatric Inventory (NPI), Hamilton depression scale (HAMD), Hamilton anxiety scale (HAMA), the National Institute of Health Stroke Scale (NIHSS), modified Rankin scale (mRS), and Barthel Index of activity of daily living (BI) combined with the physical examinations of the neurologic system at the 90-day (D90) after the AIS. The primary endpoint of this study was establishing MTx cut-offs for distinguishing PSCI from AIS.

Results

Of the 104 participants, 60 were classified to the PSCI group. The optimized cut-off value of MTx-%C (percent correct) was 78%, with a sensitivity and specificity for detecting PSCI from Non-PSCI of 90.0 and 84.1%, respectively, and an AUC of 0.919. Regarding the MTx-Cp (Composite score = MTx-%C/MTx-RT), using 46.3 as a cut-off value, the sensitivity and specificity for detecting PSCI from Non-PSCI were 80.0 and 93.2%, with an AUC of 0.925. Multivariate linear regression showed that PSCI reduced the MTx-%C (Coef. -14.18, 95% CI -18.41∼-9.95, p < 0.001) and prolonged the MTx-RT (response time) (Coef. 0.29, 95% CI 0.16∼0.43, p < 0.001) and reduced the MTx-CP (Coef. -19.11, 95% CI -24.29∼-13.93, p < 0.001).

Conclusion

MemTrax (MTx) is valid and effective for screening for PSCI among target patients and is a potentially valuable and practical tool in the clinical follow-up, monitoring, and case management of PSCI.

Early Diagnosis of Mild Cognitive Impairment due to Alzheimer's Disease Using a Composite of MemTrax and Blood Biomarkers

BACKGROUND

Accessible measurements for the early detection of mild cognitive impairment (MCI) due to Alzheimer's disease (AD) are urgently needed to address the increasing prevalence of AD.

OBJECTIVE

To determine the benefits of a composite MemTrax Memory Test and AD-related blood biomarker assessment for the early detection of MCI-AD in non-specialty clinics.

METHODS

The MemTrax Memory Test and Montreal Cognitive Assessment were administered to 99 healthy seniors with normal cognitive function and 101 patients with MCI-AD; clinical manifestation and peripheral blood samples were collected. We evaluated correlations between the MemTrax Memory Test and blood biomarkers using Spearman's rank correlation analyses and then built discrimination models using various machine learning approaches that combined the MemTrax Memory Test and blood biomarker results. The models' performances were assessed according to the areas under the receiver operating characteristic curve.

RESULTS

The MemTrax Memory Test and Montreal Cognitive Assessment areas under the curve for differentiating patients with MCI-AD from the healthy controls were similar. The MemTrax Memory Test strongly correlated with phosphorylated tau 181 and amyloid-β 42/40. The area under the curve for the best composite MemTrax Memory Test and blood biomarker model was 0.975 (95% confidence interval: 0.950-0.999).

CONCLUSION

Combining MemTrax Memory Test and blood biomarker results is a promising new technique for the early detection of MCI-AD.

Dissociation of Arousal Index Between REM and NREM Sleep in Elderly Adults with Cognitive Impairment, No Dementia: A Pilot Study

BACKGROUND

Sleep disruption in elderly has been associated with an increased risk of cognitive impairment and its transition into Alzheimer's disease (AD). High arousal indices (AIs) during sleep may serve as an early-stage biomarker of cognitive impairment non-dementia (CIND).

OBJECTIVE

Using full-night polysomnography (PSG), we investigated whether CIND is related to different AIs between NREM and REM sleep stages.

METHODS

Fourteen older adults voluntarily participated in this population-based study that included Mini-Mental State Examination, Neuropsi battery, Katz Index of Independence in Activities of Daily Living, and single-night PSG. Subjects were divided into two groups (n = 7 each) according to their results in Neuropsi memory and attention subtests: cognitively unimpaired (CU), with normal results; and CIND, with -2.5 standard deviations in memory and/or attention subtests. AIs per hour of sleep during N1, N2, N3, and REM stages were obtained and correlated with Neuropsi total score (NTS).

RESULTS

AI (REM)  was significantly higher in CU group than in CIND group. For the total sample, a positive correlation between AI (REM)  and NTS was found (r = 0.68, p = 0.006), which remained significant when controlling for the effect of age and education. In CIND group, the AI (N2)  was significantly higher than the AI (REM) .

CONCLUSION

In CIND older adults, this attenuation of normal arousal mechanisms in REM sleep are dissociated from the relative excess of arousals observed in stage N2. We propose as probable etiology an early hypoactivity at the locus coeruleus noradrenergic system, associated to its early pathological damage, present in the AD continuum.

Correctness and response time distributions in the MemTrax continuous recognition task: Analysis of strategies and a reverse-exponential model

A critical issue in addressing medical conditions is measurement. Memory measurement is difficult, especially episodic memory, which is disrupted by many conditions. On-line computer testing can precisely measure and assess several memory functions. This study analyzed memory performances from a large group of anonymous, on-line participants using a continuous recognition task (CRT) implemented at https://memtrax.com. These analyses estimated ranges of acceptable performance and average response time (RT). For 344,165 presumed unique individuals completing the CRT a total of 602,272 times, data were stored on a server, including each correct response (HIT), Correct Rejection, and RT to the thousandth of a second. Responses were analyzed, distributions and relationships of these parameters were ascertained, and mean RTs were determined for each participant across the population. From 322,996 valid first tests, analysis of correctness showed that 63% of these tests achieved at least 45 correct (90%), 92% scored at or above 40 correct (80%), and 3% scored 35 correct (70%) or less. The distribution of RTs was skewed with 1% faster than 0.62 s, a median at 0.890 s, and 1% slower than 1.57 s. The RT distribution was best explained by a novel model, the reverse-exponential (RevEx) function. Increased RT speed was most closely associated with increased HIT accuracy. The MemTrax on-line memory test readily provides valid and reliable metrics for assessing individual episodic memory function that could have practical clinical utility for precise assessment of memory dysfunction in many conditions, including improvement or deterioration over time.

Digital Cognitive Biomarker for Mild Cognitive Impairments and Dementia: A Systematic Review

The dementia population is increasing as the world's population is growing older. The current systematic review aims to identify digital cognitive biomarkers from computerized tests for detecting dementia and its risk state of mild cognitive impairment (MCI), and to evaluate the diagnostic performance of digital cognitive biomarkers. A literature search was performed in three databases, and supplemented by a Google search for names of previously identified computerized tests. Computerized tests were categorized into five types, including memory tests, test batteries, other single/multiple cognitive tests, handwriting/drawing tests, and daily living tasks and serious games. Results showed that 78 studies were eligible. Around 90% of the included studies were rated as high quality based on the Newcastle-Ottawa Scale (NOS). Most of the digital cognitive biomarkers achieved comparable or even better diagnostic performance than traditional paper-and-pencil tests. Moderate to large group differences were consistently observed in cognitive outcomes related to memory and executive functions, as well as some novel outcomes measured by handwriting/drawing tests, daily living tasks, and serious games. These outcomes have the potential to be sensitive digital cognitive biomarkers for MCI and dementia. Therefore, digital cognitive biomarkers can be a sensitive and promising clinical tool for detecting MCI and dementia.

Digital biomarkers and sex impacts in Alzheimer's disease management - potential utility for innovative 3P medicine approach

Digital biomarkers are defined as objective, quantifiable physiological and behavioral data that are collected and measured by means of digital devices. Their use has revolutionized clinical research by enabling high-frequency, longitudinal, and sensitive measurements. In the field of neurodegenerative diseases, an example of a digital biomarker-based technology is instrumental activities of daily living (iADL) digital medical application, a predictive biomarker of conversion from mild cognitive impairment (MCI) due to Alzheimer's disease (AD) to dementia due to AD in individuals aged 55 + . Digital biomarkers show promise to transform clinical practice. Nevertheless, their use may be affected by variables such as demographics, genetics, and phenotype. Among these factors, sex is particularly important in Alzheimer's, where men and women present with different symptoms and progression patterns that impact diagnosis. In this study, we explore sex differences in Altoida's digital medical application in a sample of 568 subjects consisting of a clinical dataset (MCI and dementia due to AD) and a healthy population. We found that a biological sex-classifier, built on digital biomarker features captured using Altoida's application, achieved a 75% ROC-AUC (receiver operating characteristic - area under curve) performance in predicting biological sex in healthy individuals, indicating significant differences in neurocognitive performance signatures between males and females. The performance dropped when we applied this classifier to more advanced stages on the AD continuum, including MCI and dementia, suggesting that sex differences might be disease-stage dependent. Our results indicate that neurocognitive performance signatures built on data from digital biomarker features are different between men and women. These results stress the need to integrate traditional approaches to dementia research with digital biomarker technologies and personalized medicine perspectives to achieve more precise predictive diagnostics, targeted prevention, and customized treatment of cognitive decline.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13167-022-00284-3.

Now is the Time to Improve Cognitive Screening and Assessment for Clinical and Research Advancement

Alzheimer’s disease (AD) is the only cause of death ranked in the top ten globally without precise early diagnosis or effective means of prevention or treatment. Further, AD was identified as a pandemic [1] well before COVID-19 was dubbed a 21st century pandemic [2]. And now, with the realization of the prominent secondary impacts of pandemics, there is a growing, widespread recognition of the tremendous magnitude of the impending burden from AD in an aging world population in the coming decades [3]. This appreciation has amplified the growing and pressing need for a new, efficacious, and practical platform to detect and track cognitive decline, beginning in the preliminary (prodromal) phases of the disease, sensitively, accurately, effectively, reliably, efficiently, and remotely [4–7]. Moreover, the parallel necessity of clarifying and understanding risk factors, developing successful prevention strategies [8–17], and discovering and monitoring viable and effective treatments could all benefit from accurate and efficient screening and assessment platforms. Modern recognition of AD [18] as a common affliction of the elderly began in 1968 with a paper by Blessed, Tomlinson, & Roth [19] in which two tests, one a brief assessment of cognitive function and the other a measure of daily function, demonstrated impairment which was associated with the postmortem counts of neurofibrillary tangles, composed mainly of microtubule-associated protein-tau (tau), in the brain, though not to senile plaques, composed mainly of amyloid-β (Aβ). Even in more recent analyses, the tangles correspond with the severity of dementia more than the plaques [20, 21]. Since 1960, a plethora of cognitive tests, paper and pencil [22, 23], simple screening models [24], and computerized [25–27], have been developed to assess the dysfunction associated with AD. However, there has been limited application of Modern Test Theory, which includes Item Characteristic Curve Analysis, used in the technological development of such tools [28–31], along with widespread failure to understand the underlying AD pathological process to guide test development [32, 33]. The lack of such development has likely been a major contributor to the failure of the field to develop timely screening approaches for AD [34, 35], inaccurate assessment of the progression of AD [36], and even now, failure to find an effective approach to stopping AD.

Evaluation of the Accuracy of Cognitive Screening Tests in Detecting Dementia Associated with Alzheimer's Disease: A Hierarchical Bayesian Latent Class Meta-Analysis

BACKGROUND

Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE) are neuropsychological tests commonly used by physicians for screening cognitive dysfunction of Alzheimer's disease (AD). Due to different imperfect reference standards, the performance of MoCA and MMSE do not reach consensus. It is necessary to evaluate the consistence and differentiation of MoCA and MMSE in the absence of a gold standard for AD.

OBJECTIVE

We aimed to assess the accuracy of MoCA and MMSE in screening AD without a gold standard reference test.

METHODS

Studies were identified from PubMed, Web of Science, CNKI, Chinese Wanfang Database, China Science and Technology Journal Database, and Cochrane Library. Our search was limited to studies published in English and Chinese before August 2021. A hierarchical Bayesian latent class model was performed in meta-analysis when the gold standard was absent.

RESULTS

A total of 67 studies comprising 5,554 individuals evaluated for MoCA and 76,862 for MMSE were included in this meta-analysis. The pooled sensitivity was 0.934 (95% CI 0.906 to 0.954) for MoCA and 0.883 (95% CI 0.859 to 0.903) for MMSE, while the pooled specificity was 0.899 (95% CI 0.859 to 0.928) for MoCA and 0.903 (95% CI 0.879 to 0.923) for MMSE. MoCA was useful to rule out dementia associated with AD with lower negative likelihood ratio (LR-) (0.074, 95% CI 0.051 to 0.108). MoCA showed better performance with higher diagnostic odds ratio (DOR) (124.903, 95% CI 67.459 to 231.260).

CONCLUSION

MoCA had better performance than MMSE in screening dementia associated with AD from patients with mild cognitive impairment or healthy controls.

Diagnostic performance of digital cognitive tests for the identification of MCI and dementia: A systematic review

BACKGROUND

The use of digital cognitive tests is getting common nowadays. Older adults or their family members may use online tests for self-screening of dementia. However, the diagnostic performance across different digital tests is still to clarify. The objective of this study was to evaluate the diagnostic performance of digital cognitive tests for MCI and dementia in older adults.

METHODS

Literature searches were systematically performed in the OVID databases. Validation studies that reported the diagnostic performance of a digital cognitive test for MCI or dementia were included. The main outcome was the diagnostic performance of the digital test for the detection of MCI or dementia.

RESULTS

A total of 56 studies with 46 digital cognitive tests were included in this study. Most of the digital cognitive tests were shown to have comparable diagnostic performances with the paper-and-pencil tests. Twenty-two digital cognitive tests showed a good diagnostic performance for dementia, with a sensitivity and a specificity over 0.80, such as the Computerized Visuo-Spatial Memory test and Self-Administered Tasks Uncovering Risk of Neurodegeneration. Eleven digital cognitive tests showed a good diagnostic performance for MCI such as the Brain Health Assessment. However, all the digital tests only had a few validation studies to verify their performance.

CONCLUSIONS

Digital cognitive tests showed good performances for MCI and dementia. The digital test can collect digital data that is far beyond the traditional ways of cognitive tests. Future research is suggested on these new forms of cognitive data for the early detection of MCI and dementia.

Clinical Outcome Measure Crosswalks in Alzheimer's Disease: A Systematic Review

BACKGROUND

A key challenge in studies that model outcomes, disease progression, and cost-effectiveness of existing and emerging dementia treatments is the lack of conversion criteria to translate, or 'crosswalk', scores on multiple measurement scales. Clinical status in dementia is commonly characterized in the cognitive, functional, and behavioral domains.

OBJECTIVE

We conducted a systematic review of peer-reviewed dementia measure crosswalks in the three domains.

METHODS

We systematically reviewed published literature for crosswalks between scales used to measure cognitive, functional, or behavioral outcomes in Alzheimer's and related dementias. The search was conducted in PubMed, and additional crosswalks were identified through snowballing and expert input from dementia modelers.

RESULTS

Of the reviewed articles, 2,334 were identified through a PubMed search, 842 articles were sourced from backward and forward citation snowballing, and 8 additional articles were recommended through expert input. 31 papers were eligible for inclusion, listing 74 unique crosswalks. Of those, 62 (83.8%) were between endpoints of the cognitive domain and 12 (16.2%) were either between endpoints of the functional domain or were hybrid in nature. Among crosswalks exclusively in the cognitive domain, a majority involved the Mini-Mental State Examination (MMSE) (37 crosswalks) or the Montreal Cognitive Assessment (MoCA) and its variants (25 crosswalks). MMSE was directly compared to MoCA or MoCA variants in 16 crosswalks.

CONCLUSION

Existing crosswalks between measures of dementia focus largely on a limited selection of outcome measures, particularly MMSE and MoCA. Few crosswalks exist in the functional domain, and no crosswalks were identified for solely behavioral measures.

Validity of the MemTrax Memory Test Compared to the Montreal Cognitive Assessment in the Detection of Mild Cognitive Impairment and Dementia due to Alzheimer's Disease in a Chinese Cohort

BACKGROUND

A valid, reliable, accessible, engaging, and affordable digital cognitive screen instrument for clinical use is in urgent demand.

OBJECTIVE

To assess the clinical utility of the MemTrax memory test for early detection of cognitive impairment in a Chinese cohort.

METHODS

The 2.5-minute MemTrax and the Montreal Cognitive Assessment (MoCA) were performed by 50 clinically diagnosed cognitively normal (CON), 50 mild cognitive impairment due to AD (MCI-AD), and 50 Alzheimer's disease (AD) volunteer participants. The percentage of correct responses (MTx-% C), the mean response time (MTx-RT), and the composite scores (MTx-Cp) of MemTrax and the MoCA scores were comparatively analyzed and receiver operating characteristic (ROC) curves generated.

RESULTS

Multivariate linear regression analyses indicated MTx-% C, MTx-Cp, and the MoCA score were significantly lower in MCI-AD versus CON and in AD versus MCI-AD groups (all with p≤0.001). For the differentiation of MCI-AD from CON, an optimized MTx-% C cutoff of 81% had 72% sensitivity and 84% specificity with an area under the curve (AUC) of 0.839, whereas the MoCA score of 23 had 54% sensitivity and 86% specificity with an AUC of 0.740. For the differentiation of AD from MCI-AD, MTx-Cp of 43.0 had 70% sensitivity and 82% specificity with an AUC of 0.799, whereas the MoCA score of 20 had 84% sensitivity and 62% specificity with an AUC of 0.767.

CONCLUSION

MemTrax can effectively detect both clinically diagnosed MCI and AD with better accuracy as compared to the MoCA based on AUCs in a Chinese cohort.

Blood TDP-43 Combined with Demographics Information Predicts Dementia Occurrence in Community Non-Dementia Elderly

BACKGROUND

TAR DNA-binding protein-43 (TDP-43) and neurofilament light chain (NfL) are promising fluid biomarkers of disease progression for various dementia.

OBJECTIVE

We would explore whether blood levels of NfL and TDP-43 could predict the long-term progression to dementia, and the relationship of TDP-43 levels between cerebrospinal fluid (CSF) and blood.

METHODS

A total of 86 non-dementia elderly received 7-year follow-up, and were divided into 49 stable normal control (NC)/mild cognitive impairment (MCI) subjects, 19 subjects progressing from NC to MCI, and 18 subjects progressing from NC/MCI to dementia. Blood TDP-43 and NfL levels, and cognitive functions were measured in all subjects. Furthermore, another cohort of 23 dementia patients, including 13 AD and 10 non-AD patients received blood and CSF measurements of TDP-43.

RESULTS

In cohort 1, compared to stable NC/MCI group, there were higher levels of blood TDP-43 at baseline in subjects progressing from NC/MCI to dementia. The combination of baseline blood TDP-43 levels with demographics including age, education, and diabetes had the detection for dementia occurrence. Baseline blood levels of NfL are negatively associated with cognitive function at 7-year follow-up. In cohort 2, we found there were no relationship between CSF and blood levels of TDP-43. Moreover, the levels of TDP-43 in CSF was positively associated with the age of patients, especially in AD group.

CONCLUSION

Single blood TDP-43 could not estimate dementia occurrence; however, TDP-43 combined with demographics has the predictive effect for dementia occurrence and NfL level is associated with a decrease of cognitive function.

Episodic-Memory Performance in Machine Learning Modeling for Predicting Cognitive Health Status Classification

BACKGROUND

Memory dysfunction is characteristic of aging and often attributed to Alzheimer's disease (AD). An easily administered tool for preliminary assessment of memory function and early AD detection would be integral in improving patient management.

OBJECTIVE

Our primary aim was to utilize machine learning in determining initial viable models to serve as complementary instruments in demonstrating efficacy of the MemTrax online Continuous Recognition Tasks (M-CRT) test for episodic-memory screening and assessing cognitive impairment.

METHODS

We used an existing dataset subset (n = 18,395) of demographic information, general health screening questions (addressing memory, sleep quality, medications, and medical conditions affecting thinking), and test results from a convenience sample of adults who took the M-CRT test. M-CRT performance and participant features were used as independent attributes: true positive/negative, percent responses/correct, response time, age, sex, and recent alcohol consumption. For predictive modeling, we used demographic information and test scores to predict binary classification of the health-related questions (yes/no) and general health status (healthy/unhealthy), based on the screening questions.

RESULTS

ANOVA revealed significant differences among HealthQScore groups for response time true positive (p = 0.000) and true positive (p = 0.020), but none for true negative (p = 0.0551). Both % responses and % correct had significant differences (p = 0.026 and p = 0.037, respectively). Logistic regression was generally the top-performing learner with moderately robust prediction performance (AUC) for HealthQScore (0.648-0.680) and selected general health questions (0.713-0.769).

CONCLUSION

Our novel application of supervised machine learning and predictive modeling helps to demonstrate and validate cross-sectional utility of MemTrax in assessing early-stage cognitive impairment and general screening for AD.

Utility of MemTrax and Machine Learning Modeling in Classification of Mild Cognitive Impairment

Background:

The widespread incidence and prevalence of Alzheimer’s disease and mild cognitive impairment (MCI) has prompted an urgent call for research to validate early detection cognitive screening and assessment.

Objective:

Our primary research aim was to determine if selected MemTrax performance metrics and relevant demographics and health profile characteristics can be effectively utilized in predictive models developed with machine learning to classify cognitive health (normal versus MCI), as would be indicated by the Montreal Cognitive Assessment (MoCA).

Methods:

We conducted a cross-sectional study on 259 neurology, memory clinic, and internal medicine adult patients recruited from two hospitals in China. Each patient was given the Chinese-language MoCA and self-administered the continuous recognition MemTrax online episodic memory test on the same day. Predictive classification models were built using machine learning with 10-fold cross validation, and model performance was measured using Area Under the Receiver Operating Characteristic Curve (AUC). Models were built using two MemTrax performance metrics (percent correct, response time), along with the eight common demographic and personal history features.

Results:

Comparing the learners across selected combinations of MoCA scores and thresholds, Naïve Bayes was generally the top-performing learner with an overall classification performance of 0.9093. Further, among the top three learners, MemTrax-based classification performance overall was superior using just the top-ranked four features (0.9119) compared to using all 10 common features (0.8999).

Conclusion:

MemTrax performance can be effectively utilized in a machine learning classification predictive model screening application for detecting early stage cognitive impairment.

The Dichotomy of Alzheimer's Disease Pathology: Amyloid-β and Tau

In this issue, an article by Tiepolt et al. shows that PET scanning using [¹¹C]PiB can demonstrate both cerebral blood flow (CBF) changes and amyloid-β (Aβ) deposition in patients with mild cognitive dysfunction or mild dementia of Alzheimer’s disease (AD). The CBF changes can be determined because the early scan counts (1–9 minutes) reflect the flow of the radiotracer in the blood passing through the brain, while the Aβ levels are measured by later scan counts (40–70 minutes) after the radiotracer has been cleared from regions to which the radiotracer did not bind. Thus, two different diagnostic measures are obtained with a single injection. Unexpectedly, the mild patients with Aβ positivity had scan data with only a weak relationship to memory, while the relationships to executive function and language function were relatively strong. This divergence of findings from studies of severely impaired patients highlights the importance of determining how AD pathology affects the brain. A possibility suggested in this commentary is that Aβ deposits occur early in AD and specifically in critical areas of the neocortex affected only later by the neurofibrillary pathology indicating a different role of the amyloid-β protein precursor (AβPP) in the development of those neocortical regions, and a separate component of AD pathology may selectively impact functions of these neocortical regions. The effects of adverse AβPP metabolism in the medial temporal and brainstem regions occur later possibly because of different developmental issues, and the later, different pathology is clearly more cognitively and socially devastating.

Treatment of Alzheimer's Disease: Trazodone, Sleep, Serotonin, Norepinephrine, and Future Directions

In this issue, an article by La et al. provides evidence that trazodone delayed cognitive decline in 25 participants with Alzheimer's disease (AD), mild cognitive impairment, or normal cognition. For participants considered to have AD pathology, trazodone non-users declined at a rate 2.4 times greater than those taking trazodone for sleep over a 4-year period. In the analysis of sleep complaints, the relationship between trazodone, a widely used medication for sleep problems in the elderly, and cognition was associated with subjective improvement of sleep disruption. Due to the design of the study, it was not possible to prove that the benefit of slowing cognitive decline was due specifically to the improvement in sleep. However, trazodone uniquely improves the deeper phases of slow-wave sleep. Other sedative medications are generally associated with worse cognitive function over time, and they do not improve sleep characteristics as does trazodone. Trazodone has a variety of effects on several monoaminergic mechanisms: a potent serotonin 5-HT2A and α1-adrenergic receptor antagonist, a weak serotonin reuptake inhibitor, and a weak antihistamine or histamine H1 receptor inverse agonist. Because of the potential importance of this finding, further discussion is provided on the roles that trazodone may play in the modulation of monoamines, cognition, and the development of AD. If trazodone really does provide such a dramatic slowing in the development of dementia associated with AD, a great deal more research on trazodone is needed, including environmental and behavioral factors related to improvement of sleep, energy management, and neuroplasticity.

Brief Cognitive Tests Used in Primary Care Cannot Accurately Differentiate Mild Cognitive Impairment from Subjective Cognitive Decline

BACKGROUND

Differentiating mild cognitive impairment (MCI) from subjective cognitive decline (SCD) is important because of the higher progression rate to dementia for MCI and when considering future disease-modifying drugs that will have treatment indications at the MCI stage.

OBJECTIVE

We examined if the two most widely-used cognitive tests, the Mini-Mental State Examination (MMSE) and clock-drawing test (CDT), and a test of attention/executive function (AQT) accurately can differentiate MCI from SCD.

METHODS

We included 466 consecutively recruited non-demented patients with cognitive complaints from the BioFINDER study who had been referred to memory clinics, predominantly from primary care. They were classified as MCI (n = 258) or SCD (n = 208) after thorough neuropsychological assessments. The accuracy of MMSE, CDT, and AQT for identifying MCI was examined both in training and validation samples and in the whole population.

RESULTS

As a single test, MMSE had the highest accuracy (sensitivity 73%, specificity 60%). The best combination of two tests was MMSE < 27 points or AQT > 91 seconds (sensitivity 56%, specificity 78%), but in logistic regression models, their AUC (0.76) was not significantly better than MMSE alone (AUC 0.75). CDT and AQT performed significantly worse (AUC 0.71; p < 0.001-0.05); otherwise no differences were seen between any combination of two or three tests.

CONCLUSION

Neither single nor combinations of tests could differentiate MCI from SCD with adequately high accuracy. There is a great need to further develop, validate, and implement accurate screening-tests for primary care to improve accurate identification of MCI among individuals that seek medical care due to cognitive symptoms.

Advances in screening instruments for Alzheimer's disease

At its fundamental basis, Alzheimer's disease (AD) is a pathological process that affects neuroplasticity, leading to a specific disruption of episodic memory. This review will provide a rationale for calls to screen for the early detection of AD, appraise the currently available cognitive instruments for AD detection, and focus on the development of the MemTrax test, which provides a new approach to detect the early manifestations and progression of the dementia associated with AD. MemTrax assesses metrics that reflect the effects of neuroplastic processes on learning, memory, and cognition, which are affected by age and AD, particularly episodic memory functions, which cannot presently be measured with enough precision for meaningful use. Further development of MemTrax would be of great value to the early detection of AD and would provide support for the testing of early interventions.

A Computerized Continuous-Recognition Task for Measurement of Episodic Memory

Based on clinical observations of severe episodic memory (EM) impairment in dementia of Alzheimer’s disease (AD), a brief, computerized EM test was developed for AD patient evaluation. A continuous recognition task (CRT) was chosen because of its extensive use in EM research. Initial experience with this computerized CRT (CCRT) showed patients were very engaged in the test, but AD patients had marked failure in recognizing repeated images. Subsequently, the test was administered to audiences, and then a two-minute online version was implemented (http://www.memtrax.com). The online CCRT shows 50 images, 25 unique and 25 repeats, which subjects respectively either try to remember or indicate recognition as quickly as possible. The pictures contain 5 sets of 5 images of scenes or objects (e.g., mountains, clothing, vehicles, etc.). A French company (HAPPYneuron, SAS) provided the test for 2 years, with these results. Of 18,477 individuals, who indicated sex and age 21–99 years and took the test for the first time, 18,007 individuals performed better than chance. In this group, age explained 1.5% of the variance in incorrect responses and 3.5% of recognition time variance, indicating considerable population variability. However, when averaging for specific year of age, age explained 58% of percent incorrect variance and 78% of recognition time variance, showing substantial population variability but a major age effect. There were no apparent sex effects. Further studies are indicated to determine the value of this CCRT as an AD screening test and validity as a measure of EM impairment in other clinical conditions.