Predictors of dementia misclassification when using brief cognitive assessments

Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease

Anti-amyloid treatments for early symptomatic Alzheimer disease have recently become clinically available in some countries, which has greatly increased the need for biomarker confirmation of amyloid pathology. Blood biomarker (BBM) tests for amyloid pathology are more acceptable, accessible and scalable than amyloid PET or cerebrospinal fluid (CSF) tests, but have highly variable levels of performance. The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to consider the minimum acceptable performance of BBM tests for clinical use. Amyloid PET status was identified as the reference standard. For use as a triaging test before subsequent confirmatory tests such as amyloid PET or CSF tests, the BBM Workgroup recommends that a BBM test has a sensitivity of ≥90% with a specificity of ≥85% in primary care and ≥75-85% in secondary care depending on the availability of follow-up testing. For use as a confirmatory test without follow-up tests, a BBM test should have performance equivalent to that of CSF tests - a sensitivity and specificity of ~90%. Importantly, the predictive values of all biomarker tests vary according to the pre-test probability of amyloid pathology and must be interpreted in the complete clinical context. Use of BBM tests that meet these performance standards could enable more people to receive an accurate and timely Alzheimer disease diagnosis and potentially benefit from new treatments.

Comparing the Efficacy of Two Cognitive Screening Tools in Identifying Gray and White Matter Brain Damage among Older Adults

Background

Ageing is associated with structural changes in brain regions and functional decline in cognitive domains. Noninvasive tools for identifying structural damage in the brains of older adults are relevant for early treatment.

Aims

This study aims to evaluate and compare the accuracy of the Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA©) in identifying gray and white matter brain damage in older individuals with varying degrees of cognitive impairment.

Methods

Ninety older adults (62 women) with an average age of 69 ± 7 years were enrolled and categorized as having no cognitive impairment (NCI), mild cognitive impairment (MCI), or moderate cognitive impairment (MoCI). Magnetic resonance imaging (MRI) was utilized to assess the number, volume, and distribution of brain damage. The Fazekas and Scheltens scales were applied to the brain MRIs, and inferential statistics were employed to compare variables among the groups.

Results

Cognitive impairment was observed in 56.7% of the participants (95% confidence interval (CI): 46.4-66.4%), with thirty-six older adults (40%) classified as MCI and 15 (17%) as MoCI. Cognitive impairment and medial temporal lobe (MTL) atrophy were found to be associated (p=0.001), exhibiting higher mean volume scales of the MTL atrophied area in the MoCI group (p < 0.001). The MMSE accurately revealed MTL atrophy based on the Scheltens (p < 0.05) and Fazekas (p < 0.05) scales. At the same time, the MoCA accurately identified periventricular white matter (PWM) abnormalities according to the Fazekas scale (p < 0.05).

Conclusions

The MMSE and MoCA screening tools effectively identified gray and white matter brain damage in older adults with varying degrees of cognitive impairment. Lower MMSE scores are associated with MTL atrophy and lesions, and lower MoCA scores are related to PWM lesions. The concurrent use of MMSE and MoCA is recommended for assessing structural changes in distinct brain regions.

Impact of sleep duration and sleep disturbances on the incidence of dementia and Alzheimer's disease: A 10-year follow-up study

The nature of the relationship between sleep problems and dementia remains unclear. This study investigated the relationship between sleep measures and dementia in older adults (≥ 65) using data from the English Longitudinal Study of Ageing (ELSA) and further investigated the causal association in Mendelian randomization (MR) analysis. In total of 7,223 individuals, 5.7 % developed dementia (1.7 % Alzheimer's disease (AD)) within an average of 8 (± 2.9) years. Cox regression models and MR were employed. Long sleep duration (>8 h) was associated with 64 % increased risk of incident dementia and 2-fold high risk of AD compared to ideal sleep duration (7-8 h). This association was particularly evident in older-older adults (≥70 years) and those who consumed alcohol. Short sleep duration (<7 h) was associated with lower risk of incident dementia among older-older but higher risk among younger-older adults. Sleep disturbances and perceived sleep quality were not associated with dementia or AD. The MR study did not reveal causal associations between sleep duration and dementia. These findings suggest that self-reported short sleep in younger-older and long sleep in older-older adults and those with frequent alcohol consumption are associated with dementia. Early detection of these sleep patterns may help identify individuals at higher dementia risk.

Cognitive Assessment with Cognivue Clarity®: Psychometric Properties and Normative Ranges in a Diverse Population

Background

Detecting cognitive impairment in clinical practice is challenging as most instruments do not perform well in diverse samples of older adults. These same instruments are often used for eligibility into clinical trials making it difficult to recruit minoritized adults into Alzheimer's disease (AD) studies. Cognivue Clarity® is an FDA-cleared computerized 10-minute cognitive screening platform using adaptive psychophysics to detect cognitive impairment.

Objective

Test the ability of Cognivue Clarity to measure cognitive performance in a diverse community sample compared with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS).

Methods

This study enrolled 452 participants across 6 US study sites and completed both Cognivue Clarity device and RBANS. Psychometric properties and exploratory factor analysis of Cognivue Clarity were explored and comparisons against RBANS across different age, sex, education, and ethnoracial groups were conducted.

Results

Participants had a mean age of 47.9±16.1 years (range: 18-85), 63.6% were female, 45.9% had ≤12 years of education, 31.2% were African American and 9.2% were Hispanic. Cognivue Clarity had strong internal consistency, test-retest reliability and minimal practice effects. A 4-factor structure (Memory, Attention, Visuomotor, and Discrimination) had excellent goodness-of-fit. Normalizing age effects improved performance. Race and education effects were similar to those seen with RBANS. Cognivue Clarity had strong correlations with RBANS.

Conclusions

Our study supports the use of Cognivue Clarity as an easy-to-use, brief, and valid cognitive assessment that measures cognitive performance. In the correct clinical setting, Cognivue Clarity may identify individuals with likely cognitive impairment who could be candidates for AD research studies.

Clinical classification of memory and cognitive impairment with multimodal digital biomarkers

INTRODUCTION

Early detection of Alzheimer's disease and cognitive impairment is critical to improving the healthcare trajectories of aging adults, enabling early intervention and potential prevention of decline.

METHODS

To evaluate multi-modal feature sets for assessing memory and cognitive impairment, feature selection and subsequent logistic regressions were used to identify the most salient features in classifying Rey Auditory Verbal Learning Test-determined memory impairment.

RESULTS

Multimodal models incorporating graphomotor, memory, and speech and voice features provided the stronger classification performance (area under the curve = 0.83; sensitivity = 0.81, specificity = 0.80). Multimodal models were superior to all other single modality and demographics models.

DISCUSSION

The current research contributes to the prevailing multimodal profile of those with cognitive impairment, suggesting that it is associated with slower speech with a particular effect on the duration, frequency, and percentage of pauses compared to normal healthy speech.

Scheltens ratings, clinical white matter hyperintensities and executive: Functioning in the Cache County Memory Study

OBJECTIVE

Examine the association between neuropsychologically assessed executive function and clinically identifiable white matter burden from magnetic resonance imaging, using a visual rating system (Scheltens Rating System) applied to the Cache County Memory Study (CCMS) archival database.

METHOD

We used the Scheltens Ratings Scale to quantify white matter lesion burden in the CCMS sample and used this metric as a predictor of executive function. The sample included 60 individuals with dementia and 13 healthy controls.

RESULTS

Higher Scheltens ratings were associated with poorer task performance on an Executive Function composite score of common neuropsychological tests. This association held true for both controls and dementing cases.

CONCLUSIONS

The current findings support extensive prior literature demonstrating the association between brain vascular health determined by white matter burden and clinical outcomes based on neuropsychological assessment of cognitive performance.

Artificial intelligence for dementia research methods optimization

Artificial intelligence (AI) and machine learning (ML) approaches are increasingly being used in dementia research. However, several methodological challenges exist that may limit the insights we can obtain from high-dimensional data and our ability to translate these findings into improved patient outcomes. To improve reproducibility and replicability, researchers should make their well-documented code and modeling pipelines openly available. Data should also be shared where appropriate. To enhance the acceptability of models and AI-enabled systems to users, researchers should prioritize interpretable methods that provide insights into how decisions are generated. Models should be developed using multiple, diverse datasets to improve robustness, generalizability, and reduce potentially harmful bias. To improve clarity and reproducibility, researchers should adhere to reporting guidelines that are co-produced with multiple stakeholders. If these methodological challenges are overcome, AI and ML hold enormous promise for changing the landscape of dementia research and care. HIGHLIGHTS: Machine learning (ML) can improve diagnosis, prevention, and management of dementia. Inadequate reporting of ML procedures affects reproduction/replication of results. ML models built on unrepresentative datasets do not generalize to new datasets. Obligatory metrics for certain model structures and use cases have not been defined. Interpretability and trust in ML predictions are barriers to clinical translation.

Content development of the VISION-Cog: a novel tool to assess cognitive impairment in visually impaired older adults in Singapore

OBJECTIVES

Current cognitive screening and diagnostic instruments rely on visually dependent tasks and are, therefore, not suitable to assess cognitive impairment (CI) in visually impaired older adults. We describe the content development of the VISually Independent test battery Of NeuroCOGnition (VISION-Cog)-a new diagnostic tool to evaluate CI in visually impaired older Singaporean adults.

DESIGN

The content development phase consisted of two iterative stages: a neuropsychological consultation and literature review (stage 1) and an expert-panel discussion (stage 2). In stage 1, we investigated currently available neuropsychological test batteries for CI to inform constructions of our preliminary test battery. We then deliberated this battery during a consensus meeting using the Modified Nominal Group technique (stage 2) to decide, via agreement of five experts, the content of a pilot neuropsychological battery for the visually impaired.

SETTING

Singapore Eye Research Institute.

PARTICIPANTS

Stakeholders included researchers, psychologists, neurologists, neuro-ophthalmologists, geriatricians and psychiatrists.

OUTCOME MEASURE

pilot VISION-Cog.

RESULTS

The two-stage process resulted in a pilot VISION-Cog consisting of nine vision-independent neuropsychological tests, including the modified spatial memory test, list learning, list recall and list recognition, adapted token test, semantic fluency, modified spatial analysis, verbal subtests of the frontal battery assessment, digit symbol, digit span forwards, and digit span backwards. These tests encompassed five cognitive domains-memory and learning, language, executive function, complex attention, and perceptual-motor abilities. The expert panel suggested improvements to the clarity of test instructions and culturally relevant test content. These suggestions were incorporated and iteratively pilot-tested by the study team until no further issues emerged.

CONCLUSIONS

We have developed a five-domain and nine-test VISION-Cog pilot instrument capable of replacing vision-dependent diagnostic batteries in aiding the clinician-based diagnosis of CI in visually impaired older adults. Subsequent phases will examine the VISION-Cog's feasibility, comprehensibility and acceptability; and evaluate its diagnostic performance.

Lexical Speech Features of Spontaneous Speech in Older Persons With and Without Cognitive Impairment: Reliability Analysis

Background

Speech analysis data are promising digital biomarkers for the early detection of Alzheimer disease. However, despite its importance, very few studies in this area have examined whether older adults produce spontaneous speech with characteristics that are sufficiently consistent to be used as proxy markers of cognitive status.

Objective

This preliminary study seeks to investigate consistency across lexical characteristics of speech in older adults with and without cognitive impairment.

Methods

A total of 39 older adults from a larger, ongoing study (age: mean 81.1, SD 5.9 years) were included. Participants completed neuropsychological testing and both picture description tasks and expository tasks to elicit speech. Participants with T-scores of ≤40 on ≥2 cognitive tests were categorized as having mild cognitive impairment (MCI). Speech features were computed automatically by using Python and the Natural Language Toolkit.

Results

Reliability indices based on mean correlations for picture description tasks and expository tasks were similar in persons with and without MCI (with r ranging from 0.49 to 0.65 within tasks). Intraindividual variability was generally preserved across lexical speech features. Speech rate and filler rate were the most consistent indices for the cognitively intact group, and speech rate was the most consistent for the MCI group.

Conclusions

Our findings suggest that automatically calculated lexical properties of speech are consistent in older adults with varying levels of cognitive impairment. These findings encourage further investigation of the utility of speech analysis and other digital biomarkers for monitoring cognitive status over time.

Early Identification of Cognitive Impairment: Utility of the Mini-Cog in Non-Clinical Settings

While we currently cannot cure Alzheimer's disease or change the course of the disease, there are advantages to early detection. Routine, evidence based, brief cognitive screens offer destigmatized opportunities for diagnosis and improve the possibility of early identification of cognitive impairment. This community-based participatory research project evaluated the use of the Mini-Cog™ instrument to detect cognitive impairment in vulnerable community-dwelling older adults when administered by trained social services providers. Over 9 months, a case manager screened 69 clients ages 65 to 94 (mean 74.67) who met inclusion criteria for the pilot; 84.1% were female, 53.6% were Black, 26% were living with undetected cognitive impairment. Although participants agreed to Mini-Cog™ screening, two-thirds with Mini-Cog™ scores indicating cognitive impairment refused referrals for further evaluation. Future interventions should reduce stigma by educating the public about dementia and engaging members of racial and cultural communities in outreach.

Association of Performance on Olfactory and Cognitive Screening Tests With Conversion to Dementia in a Biracial Cohort of Older Adults

BACKGROUND AND OBJECTIVES

Odor identification deficits are associated with transition to dementia, whereas intact odor identification and global cognition test performance may identify lack of transition. The purpose of this study was to examine intact odor identification and global cognition as prognostic indicators of lack of transition to dementia in a biracial (Black and White) cohort.

METHODS

In a community-dwelling sample of older adults from the Health, Aging, and Body Composition study, odor identification was measured using the Brief Smell Identification Test (BSIT), and global cognition was measured using the Teng Modified Mini-Mental State Examination (3MS). Survival analyses for dementia transition over 4 and 8 years of follow-up used Cox proportional hazards models.

RESULTS

A total of 2,240 participants had an average age of 75.5 years (SD 2.8). Approximately 52.7% were female individuals. Approximately 36.7% were Black and 63.3% were White individuals. Impaired odor identification (hazard ratio [HR] 2.29, 95% CI 1.79-2.94, p < 0.001) and global cognition (HR 3.31, 95% CI 2.26-4.84, p < 0.001) were each independently associated with transition to dementia (n = 281). Odor identification remained robustly associated with transition to dementia for Black (HR 2.02, 95% CI 1.36-3.00, p < 0.001, n = 821) and White participants (HR 2.45, 95% CI 1.77-3.38, p < 0.001, n = 1,419), whereas global cognition was associated with transition among Black participants only (HR 5.06, 95% CI 3.18-8.07, p < 0.001). ApoE genotype was consistently associated with transition among White participants only (HR 1.75, 95% CI 1.20-2.54, p < 0.01). Among participants with intact performance on both odor identification (BSIT ≥9/12 correct) and global cognition (3MS ≥ 78/100 correct), 8.8% transitioned to dementia over 8 years. Intact performance on both measures had high positive predictive value for identifying individuals who did not transition to dementia over 4 years (0.98 for ages 70-75 years with only 2.3% transitioning, 0.94 for ages 76-82 years with only 5.8% transitioning).

DISCUSSION

Odor identification testing paired with a global cognitive screening test identified individuals at low risk of transition to dementia in a biracial community cohort with a pronounced effect in the eighth decade of life. Identification of such individuals can reduce the need for extensive investigation to establish a diagnosis. Odor identification deficits showed utility in both Black and White participants, unlike the race-dependent utility of a global cognitive test and ApoE genotype.

Artificial Intelligence for Dementia Research Methods Optimization

INTRODUCTION

Machine learning (ML) has been extremely successful in identifying key features from high-dimensional datasets and executing complicated tasks with human expert levels of accuracy or greater.

METHODS

We summarize and critically evaluate current applications of ML in dementia research and highlight directions for future research.

RESULTS

We present an overview of ML algorithms most frequently used in dementia research and highlight future opportunities for the use of ML in clinical practice, experimental medicine, and clinical trials. We discuss issues of reproducibility, replicability and interpretability and how these impact the clinical applicability of dementia research. Finally, we give examples of how state-of-the-art methods, such as transfer learning, multi-task learning, and reinforcement learning, may be applied to overcome these issues and aid the translation of research to clinical practice in the future.

DISCUSSION

ML-based models hold great promise to advance our understanding of the underlying causes and pathological mechanisms of dementia.

Long-term use of metformin and Alzheimer's disease: beneficial or detrimental effects

Alzheimer's disease (AD) is the most common neurodegenerative disease characterized by extracellular deposition of amyloid beta (Aβ) leading to cognitive decline. Evidence from epidemiological studies has shown the association between type 2 diabetes mellitus (T2DM) and the development of AD. T2DM and peripheral insulin resistance (IR) augment the risk of AD with the development of brain IR with inhibition of neuronal insulin receptors. These changes impair clearance of Aβ, increase secretion of Aβ_1-42, reduce brain glucose metabolism, and abnormal deposition of Aβ plaques. Insulin-sensitizing drug metformin inhibits aggregation of Aβ by increasing the activity of the insulin-degrading enzyme (IDE) and neprilysin (NEP) levels. Additionally, different studies raised conflicting evidence concerning long-term metformin therapy in T2DM patients, as it may increase the risk of AD or it may prevent the progression of AD. Therefore, the objective of this review was to clarify the beneficial and detrimental effects of long-term metformin therapy in T2DM patients and risk of AD. Evidence from clinical trial studies revealed the little effect of metformin on AD. Various animal studies showed that metformin increases Aβ formation by activation of amyloid precursor protein (APP)-cleaving enzymes with the generation of insoluble tau species. Of note, the metformin effect on cognitive function relative to AD pathogenesis is mostly assessed in animal model studies. The duration of metformin therapy was short in most animal studies, this finding cannot apply to the long-term duration of metformin in humans. Therefore, large-scale prospective and comparative studies involving long-term metformin therapy in both diabetic and non-diabetic patients are required to exclude the effect of T2DM-induced AD.

Neighborhood greenspace and cognition: The cardiovascular health study

OBJECTIVES

We examined whether greenspace measures (overall percent greenspace and forest, and number of greenspace types) were associated with clinically adjudicated dementia status.

METHODS

In a sample of non-demented older adults (n = 2141, average age = 75.3 years) from the Cardiovascular Health and Cognition Study, Cox proportional hazard and logistic regression analyses were used to estimate associations of baseline greenspace with risks of incident dementia and MCI, respectively, while adjusting for demographics, co-morbidities, and other neighborhood factors. We derived quartiles of percent greenness (greenspace), forest (percent tree canopy cover), and tertiles of greenspace diversity (number of greenspace types) for 5-km radial buffers around participant's residences at study entry (1989-1990) from the 1992 National Land Cover Dataset. Dementia status and mild cognitive impairment (MCI) over 10 years was clinically adjudicated.

RESULTS

We observed no significant association between overall percent greenspace and risk of mild cognitive impairment or dementia and mostly null results for forest and greenspace diversity. Forest greenspace was associated with lower odds of MCI (OR quartile 4 versus 1: 0.54, 95% CI: 0.29-0.98) and greenspace diversity was associated with lower hazard of incident dementia (HR tertile 2 versus 1: 0.70, 95% CI = 0.50-0.99).

DISCUSSION

We found divergent results for different types of greenspace and mild cognitive impairment or dementia. Improved greenspace type and diversity measurement could better characterize the association between greenspace and cognition.

Education bias in typical brief cognitive tests used for the detection of dementia in elderly population with low educational level: a critical review

Dementia is a significant decline in cognition that interfere with independent, daily functioning. Dementia is a syndrome caused by a myriad and include primary neurologic, neuropsychiatric, and medical conditions. It has been projected that the prevalence of dementia will triple in the elderly population by the year 2050. Despite the benefits of early diagnosis, there is an effective under-detection of around 62% of people with mild cognitive impairment (MCI) or dementia. One of the factors associated with this problem is that diagnostic techniques are affected by the educational level of those evaluated. This is an important aspect to consider in the use of brief cognitive tests for the detection of dementia. This review presents and critically analyzes the available evidence regarding the effect of educational level on the diagnostic utility of three of the most widely used tools in the clinical setting: the Mini-mental Test Examination (MMSE), the Montreal Cognitive Assessment (MoCA), and the Addenbrooke's Cognitive Examination (ACE). Previous evidence shows that the tasks that require reading, writing, calculation, phonological fluency, and visuoconstruction are affected by educational level. These results lead to discourage the use of these tests in older people with less than 6 years of schooling. The development of brief cognitive tests appropriate for people with a low educational level is recommended. We posit that adequate cognitive tests should not consider tasks or items that resemble characteristics of academic contexts and should be more analogous to daily activities situations.

Comprehensive assessment of neurocognitive function, inflammation markers, and adiposity in treated HIV and control

To compare the neurocognitive scores between persons living with human immunodeficiency virus (PLWH) and persons without human immunodeficiency virus (HIV) and assess the relationship between neurocognition, HIV status and variables, inflammation, and body composition measures. Cross-sectional study involving 225 participants (126 PLWH on antiretroviral therapy [ART] and 99 persons without HIV). For the first time in HIV, we used Cognivue®, an food and drug administration (FDA)-approved computer-based test to assess cognitive function. The test was calibrated to individuals' unique cognitive ability and measured 6 cognitive domains and 2 performance parameters. Markers of inflammation, immune activation, insulin resistance, and body fat composition (using dual-energy X-ray absorptiometry scan) were collected. Classical t tests, chi-square tests, and spearman correlations were used to compare and explore relationships between variables. Inverse probability weighting adjusted average treatment effect models were performed to evaluate the differences between PLWH and persons without HIV, adjusting for age, race, sex, and heroin use. Overall, 64% were male, 46% were Black, with a mean age of 43 years. Among PLWH, 83% had an undetectable HIV-1 RNA level (≤20 copies/mL). Compared persons without HIV, PLWH performed poorer across 4 domains: visuospatial (P = .035), executive function (P = .029), naming/language (P = .027), and abstraction (P = .018). In addition, PLWH had a significantly longer processing speed time compared to controls (1686.0 ms vs 1606.0 ms [P = .007]). In PLWH, lower cognitive testing domain scores were associated with higher inflammatory markers (high sensitivity C-reactive protein [hsCRP]) and with higher total fat and visceral adipose tissue (P < .05). Neurocognitive impairment (NCI) in HIV is associated with inflammation and total and central adiposity.

A Retrospective Study on Clinical Assessment of Cognitive Impairment in a Swedish Cohort: Is There Inequality Between Natives and Foreign-Born?

BACKGROUND

People with a migration background are underrepresented in dementia research and disfavored in assessment and treatment, and many foreign-born individuals with dementia remain undiagnosed.

OBJECTIVE

The aim of this study was to examine whether there is inequality in the clinical assessment of dementia between native and foreign-born individuals in Sweden.

METHODS

Information was gathered retrospectively from a cohort of 91 native and 36 foreign-born patients attending four memory clinics in Skåne, Sweden. Data included information on cognitive test results, cerebrospinal fluid biomarkers, scores at structural imaging scales of global cortical atrophy (GCA), medial temporal lobe atrophy (MTA) and the Fazekas scale, laboratory measures of thyroid-stimulating hormone, calcium, albumin, homocysteine, hemoglobin, cobalamin (vitamin B12), and folate (vitamin B9), contact with health care, and treatment.

RESULTS

Foreign-born patients had lower educational level and scored lower on Mini-Mental State Examination and Clock Drawing Test (p &lt; 0.001-0.011). Relatives initiated contact with health care to a higher extent in the foreign-born group (p = 0.031). Foreign-born patients had less white matter lesions (p = 0.018). Additionally, Alzheimer's disease (AD) biomarkers were significantly less used in foreign-born patients to support an AD diagnosis (p = 0.001). No significant differences were found for scores on GCA and MTA, laboratory measures, or initiated treatment.

CONCLUSION

Although native and foreign-born patients were predominantly homogenous regarding examined variables, differences in the diagnostic process and underlying biological correlates of dementia exist and need to be further investigated in a larger sample.

Clinical Ratings of White Matter Hyperintensities, Hippocampal Ratings, and Neuropsychological Functioning from The Cache County Memory Study

Objective

White matter burden and medial temporal atrophy are associated with cognitive health. A large epidemiological database, such as the Cache County Memory Study (CCMS), can provide additional insight into how visual clinical ratings of brain structural integrity predict cognition in older adults.

Method

We used the Scheltens Ratings Scale to quantify white matter lesion burden and medial temporal atrophy in the CCMS sample to determine if these qualitative markers are predictive of memory function. We performed clinical ratings of MRI scans across two ascertainment periods among 187 community-dwelling older adults and correlated these ratings with MMSE, CERAD memory performance, and general cognitive ability.

Results

Higher Scheltens ratings measuring white matter and basal ganglia hyperintensities were associated with lower memory performance (r = 0.21). The strongest correlations were observed between medial temporal atrophy and general cognition performance (r = 0.32).

Conclusions

The current findings support previous research that the integrity of different regions of the brain correlate to function in a meaningful way.

Many Changes in Speech through Aging Are Actually a Consequence of Cognitive Changes

Background: During aging, changes in human speech may arise because of the neurophysiological deterioration associated with age, or as the result of an impairment in the cognitive processes underlying speech production. Some speech parameters show specific alterations under the presence of dementia. The objective of our study is to identify which of these parameters change because of age, cognitive state, or the interaction of both. Methods: The sample includes 400 people over 55 years old, who were divided into four groups, according to their age. The cognitive state of the participants was assessed through the MMSE test and three ranks were stablished. Gender was also considered in the analysis. Results: Certain temporal, fluency, rhythm, amplitude and voice quality parameters were found to be related to the cognitive state, while disturbance parameters changed due to age. Frequency parameters were exclusively influenced by gender. Conclusions: Understanding how speech parameters are specifically affected by age, cognitive state, or the interaction of both, is determinant to advance in the use of speech as a clinical marker for the detection of cognitive impairments.

Effects of Changes in Physical Activity with Cognitive Decline in Korean Home-Dwelling Older Adults

Purpose

Patients and Methods

Results

Conclusion

Diagnostic Precision in the Detection of Mild Cognitive Impairment: A Comparison of Two Approaches

OBJECTIVE

This study compared diagnostic rates and clinical predictors of discrepancies between diagnoses conferred via: 1) a comprehensive neuropsychological evaluation and National Institute on Aging-Alzheimer's Association (NIA-AA) criteria versus 2) a cognitive screener and Diagnostic Statistical Manual of Mental Disorders (DSM-5) criteria.

DESIGN

Cross-sectional examination of baseline data from the Prevention of Alzheimer's dementia (AD) using Cognitive remediation and transcranial direct current stimulation in Mild Cognitive Impairment (MCI) and Depression (PACt-MD; ClinicalTrials.gov Identifier: NCT02386670) trial.

SETTING

Five geriatric psychiatry and memory clinics located at academic hospitals affiliated with the Department of Psychiatry, University of Toronto.

PARTICIPANTS

Older adults (N = 431) with a history of major depressive disorder (MDD) in remission, MCI, or both.

MEASUREMENTS

Main outcome was a comparison of NIA-AA diagnostic rates of MCI or dementia versus DSM-5 rates of mild or major neurocognitive disorder. Secondary analyses examined demographic, race, gender, premorbid intellectual ability, psychosocial, health-related, and genetic predictors of discrepancy between DSM-5 and NIA-AA diagnoses.

RESULTS

There were 103 (23.8%) discrepant cases, with most (91; 88.3%) of these discrepant cases reflecting more impairment with the detailed neuropsychological testing and NIA-AA criteria. Discrepancies were more likely in individuals with a history of MDD or who had at least one ApoE4 allele.

CONCLUSION

The NIA-AA criteria, in conjunction with comprehensive neuropsychological testing, identified a greater prevalence of cognitive impairment than DSM-5 criteria, in conjunction with the Montreal Cognitive Assessment. Detailed neuropsychological evaluations are recommended for older adults who have a history of MDD or a genetic vulnerability to dementia.

Sleep Disturbances, Changes in Sleep, and Cognitive Function in Low-Income African Americans

BACKGROUND

Sleep problems may contribute to the disproportionate burden of Alzheimer's disease and related dementias (ADRD) among African Americans (AAs).

OBJECTIVE

To examine the role of sleep problems in contributing to cognitive function and clinically adjudicated cognitive impairment in a predominantly AA sample.

METHODS

This study (n = 216, 78.8% female; mean age = 67.7 years) examined associations between 1) the level (i.e., measured in 2018) and 2) change over time (from 2013 to 2018; n = 168) in actigraphy-assessed sleep with domain-specific cognitive function and clinically adjudicated cognitive impairment (2018) in a community-dwelling, predominantly AA (96.9%) sample. A comprehensive cognitive battery assessed global cognitive function (3MS) and domain-specific cognitive function (attention, visuo-spatial ability, language, delayed recall, immediate recall, and executive function) in 2018. Sleep was measured in 2013 and 2018 via actigraphy.

RESULTS

Higher sleep efficiency and less wakefulness after sleep onset (WASO; measured in 2018) were associated with greater attention, executive function, and visuospatial ability. Increases in sleep efficiency between 2013 and 2018 were associated with better executive function, language, immediate recall, and visuospatial ability, whereas increases in WASO (2013-2018) were associated with poorer attention, executive function, and visuospatial ability. Level or change in sleep duration were not associated with domain-specific cognitive function, nor were any sleep measures associated with clinically adjudicated cognitive impairment.

CONCLUSION

In a predominantly AA sample of older adults, both the level and change (i.e., worsening) of sleep efficiency and WASO were associated with poorer cognitive function. Improving sleep health may support ADRD prevention and reduce health disparities.

Performance of Machine Learning Algorithms for Predicting Progression to Dementia in Memory Clinic Patients

IMPORTANCE

Machine learning algorithms could be used as the basis for clinical decision-making aids to enhance clinical practice.

OBJECTIVE

To assess the ability of machine learning algorithms to predict dementia incidence within 2 years compared with existing models and determine the optimal analytic approach and number of variables required.

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study used data from a prospective cohort of 15 307 participants without dementia at baseline to perform a secondary analysis of factors that could be used to predict dementia incidence. Participants attended National Alzheimer Coordinating Center memory clinics across the United States between 2005 and 2015. Analyses were conducted from March to May 2021.

EXPOSURES

258 variables spanning domains of dementia-related clinical measures and risk factors.

MAIN OUTCOMES AND MEASURES

The main outcome was incident all-cause dementia diagnosed within 2 years of baseline assessment.

RESULTS

In a sample of 15 307 participants (mean [SD] age, 72.3 [9.8] years; 9129 [60%] women and 6178 [40%] men) without dementia at baseline, 1568 (10%) received a diagnosis of dementia within 2 years of their initial assessment. Compared with 2 existing models for dementia risk prediction (ie, Cardiovascular Risk Factors, Aging, and Incidence of Dementia Risk Score, and the Brief Dementia Screening Indicator), machine learning algorithms were superior in predicting incident all-cause dementia within 2 years. The gradient-boosted trees algorithm had a mean (SD) overall accuracy of 92% (1%), sensitivity of 0.45 (0.05), specificity of 0.97 (0.01), and area under the curve of 0.92 (0.01) using all 258 variables. Analysis of variable importance showed that only 6 variables were required for machine learning algorithms to achieve an accuracy of 91% and area under the curve of at least 0.89. Machine learning algorithms also identified up to 84% of participants who received an initial dementia diagnosis that was subsequently reversed to mild cognitive impairment or cognitively unimpaired, suggesting possible misdiagnosis.

CONCLUSIONS AND RELEVANCE

These findings suggest that machine learning algorithms could accurately predict incident dementia within 2 years in patients receiving care at memory clinics using only 6 variables. These findings could be used to inform the development and validation of decision-making aids in memory clinics.

Validity and Cultural Generalisability of a 5-Minute AI-Based, Computerised Cognitive Assessment in Mild Cognitive Impairment and Alzheimer's Dementia

Introduction: Early detection and monitoring of mild cognitive impairment (MCI) and Alzheimer's Disease (AD) patients are key to tackling dementia and providing benefits to patients, caregivers, healthcare providers and society. We developed the Integrated Cognitive Assessment (ICA); a 5-min, language independent computerised cognitive test that employs an Artificial Intelligence (AI) model to improve its accuracy in detecting cognitive impairment. In this study, we aimed to evaluate the generalisability of the ICA in detecting cognitive impairment in MCI and mild AD patients. Methods: We studied the ICA in 230 participants. 95 healthy volunteers, 80 MCI, and 55 mild AD participants completed the ICA, Montreal Cognitive Assessment (MoCA) and Addenbrooke's Cognitive Examination (ACE) cognitive tests. Results: The ICA demonstrated convergent validity with MoCA (Pearson r=0.58, p<0.0001) and ACE (r=0.62, p<0.0001). The ICA AI model was able to detect cognitive impairment with an AUC of 81% for MCI patients, and 88% for mild AD patients. The AI model demonstrated improved performance with increased training data and showed generalisability in performance from one population to another. The ICA correlation of 0.17 (p = 0.01) with education years is considerably smaller than that of MoCA (r = 0.34, p < 0.0001) and ACE (r = 0.41, p < 0.0001) which displayed significant correlations. In a separate study the ICA demonstrated no significant practise effect over the duration of the study. Discussion: The ICA can support clinicians by aiding accurate diagnosis of MCI and AD and is appropriate for large-scale screening of cognitive impairment. The ICA is unbiased by differences in language, culture, and education.

Learning From Clinical Consensus Diagnosis in India to Facilitate Automatic Classification of Dementia: Machine Learning Study

BACKGROUND

The Harmonized Diagnostic Assessment of Dementia for the Longitudinal Aging Study in India (LASI-DAD) is the first and only nationally representative study on late-life cognition and dementia in India (n=4096). LASI-DAD obtained clinical consensus diagnosis of dementia for a subsample of 2528 respondents.

OBJECTIVE

This study develops a machine learning model that uses data from the clinical consensus diagnosis in LASI-DAD to support the classification of dementia status.

METHODS

Clinicians were presented with the extensive data collected from LASI-DAD, including sociodemographic information and health history of respondents, results from the screening tests of cognitive status, and information obtained from informant interviews. Based on the Clinical Dementia Rating (CDR) and using an online platform, clinicians individually evaluated each case and then reached a consensus diagnosis. A 2-step procedure was implemented to train several candidate machine learning models, which were evaluated using a separate test set for predictive accuracy measurement, including the area under receiver operating curve (AUROC), accuracy, sensitivity, specificity, precision, F1 score, and kappa statistic. The ultimate model was selected based on overall agreement as measured by kappa. We further examined the overall accuracy and agreement with the final consensus diagnoses between the selected machine learning model and individual clinicians who participated in the clinical consensus diagnostic process. Finally, we applied the selected model to a subgroup of LASI-DAD participants for whom the clinical consensus diagnosis was not obtained to predict their dementia status.

RESULTS

Among the 2528 individuals who received clinical consensus diagnosis, 192 (6.7% after adjusting for sampling weight) were diagnosed with dementia. All candidate machine learning models achieved outstanding discriminative ability, as indicated by AUROC >.90, and had similar accuracy and specificity (both around 0.95). The support vector machine model outperformed other models with the highest sensitivity (0.81), F1 score (0.72), and kappa (.70, indicating substantial agreement) and the second highest precision (0.65). As a result, the support vector machine was selected as the ultimate model. Further examination revealed that overall accuracy and agreement were similar between the selected model and individual clinicians. Application of the prediction model on 1568 individuals without clinical consensus diagnosis classified 127 individuals as living with dementia. After applying sampling weight, we can estimate the prevalence of dementia in the population as 7.4%.

CONCLUSIONS

The selected machine learning model has outstanding discriminative ability and substantial agreement with a clinical consensus diagnosis of dementia. The model can serve as a computer model of the clinical knowledge and experience encoded in the clinical consensus diagnostic process and has many potential applications, including predicting missed dementia diagnoses and serving as a clinical decision support tool or virtual rater to assist diagnosis of dementia.

Brief Screening for Four Mental Illnesses of the Elderly in Community Mental Health Services: the BS4MI-Elderly

OBJECTIVE

Early detection and proper management of mental illness can help to prevent severe deterioration. However, with limited financial and human resources of community mental health services, it is not practical to carry out all conventional screening tools simultaneously. In this study, we aimed to develop and validate a brief but comprehensive screening questionnaire for four common mental illnesses of the elderly.

METHODS

The brief screening for four mental illnesses of elderly (BS4MI-elderly) is a 14-item binary response questionnaire that covers dementia, depressive disorder, sleep disorder, and hwa-byung. To test validity, we compared conventional scale scores for three groups of participants classified using the BS4MI-elderly. The sensitivity, specificity, predictive value of positive test, likelihood ratio of positive test and internal consistency of the BS4MI-elderly were assessed. Finally, a correlation analysis between the BS4MI-elderly and general mental health scales was conducted.

RESULTS

A total of 254 participants aged over 65 years were recruited. The BS4MI-elderly showed moderate to high sensitivity for the test that distinguishes the normal group from the risk and disorder groups (dementia: 0.61, depressive disorder: 0.88, sleep disorder: 0.85, hwa-byung: 0.94) and high specificity for the test that distinguishes the disorder group from the normal and risk groups (dementia: 0.91, depressive disorder: 0.93, hwa-byung: 0.84, sleep disorder: 0.84). The BS4MI-elderly also exhibited good internal consistency and significant correlations with general mental health scales.

CONCLUSION

The BS4MI-elderly, a brief but comprehensive screening tool, could be a useful instrument for screening the elderly in community mental health services.

Guideline-conform translation and cultural adaptation of the Addenbrooke's Cognitive Examination III into German

Objective: Age-related disorders, such as dementia, significantly contribute to the global burden of disease. Adequate screening in the primary care setting is critical for early detection and proper management. The Addenbrooke's Cognitive Examination III (ACE-III) is an open-source neuropsychological test with superior diagnostic quality in comparison to the Mini-Mental State Examination (MMSE). Our aim was to perform a guideline-conform English-German translation and cultural adaptation of the ACE-III in order to enable implementation in German-speaking countries. Methods: The translation and cultural adaptation were performed in accordance with the "Principles of Good Practice for the Translation and Cultural Adaptation Process for Patient-Reported Outcomes (PRO) Measures" from the International Society for Pharmacoeconomics and Outcome Research (ISPOR) (Wild et al. 2005). Four separate English-German translations were compiled into one German consensus translation, which was then translated back into English and compared to the original English version. After comparison, the German consensus translation was revised with emphasis on the identified differences between the English original version and the English translated version. This revised German consensus translation was subsequently evaluated for clinical applicability on a 5-point scale (0 - not applicable; 5 - applicable without any restrictions) by 20 practitioners experienced in the field of neuropsychological testing, using an anonymized, paper-based 22-item survey. Results: Nineteen of the 20 practitioners (95.0%) rated the German ACE-III translation as overall applicable. The median rating was 4.0 [IQR (4.0/5.0)]. When evaluating survey items assessing the applicability of the individual 19 subtests of the ACE-III, all of them (100%) were rated as applicable with a median rating of 4.5 [IQR (4.1/4.9)]. Conclusion: The German ACE-III translation in its current form is generally applicable and can be utilized for clinical and scientific purposes.

Cognitive Impairment in Aging Physicians: Current Challenges and Possible Solutions

Aging physicians are at a higher risk of cognitive impairment, undermining patient safety and unraveling physicians' careers. Neurologists, occupational health physicians, and psychiatrists will participate in both health system policy decisions and individual patient evaluations. We address cognitive impairment in aging physicians and attendant risks and benefits. If significant cognitive impairment is found after an appropriate evaluation, precautions to confidentially support physicians' practicing safely for as long as possible should be instituted. Understanding that there is heterogeneity and variability in the course of cognitive disorders is crucial to supporting cognitively impaired, practicing physicians. Physicians who are no longer able to practice clinically have other meaningful options.

Screening for Cognitive Impairment in Older Adults: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

IMPORTANCE

Early identification of cognitive impairment may improve patient and caregiver health outcomes.

OBJECTIVE

To systematically review the test accuracy of cognitive screening instruments and benefits and harms of interventions to treat cognitive impairment in older adults (≥65 years) to inform the US Preventive Services Task Force.

DATA SOURCES

MEDLINE, PubMed, PsycINFO, and Cochrane Central Register of Controlled Trials through January 2019, with literature surveillance through November 22, 2019.

STUDY SELECTION

Fair- to good-quality English-language studies of cognitive impairment screening instruments, and pharmacologic and nonpharmacologic treatments aimed at persons with mild cognitive impairment (MCI), mild to moderate dementia, or their caregivers.

DATA EXTRACTION AND SYNTHESIS

Independent critical appraisal and data abstraction; random-effects meta-analyses and qualitative synthesis.

MAIN OUTCOMES AND MEASURES

Sensitivity, specificity; patient, caregiver, and clinician decision-making; patient function, quality of life, and neuropsychiatric symptoms; caregiver burden and well-being.

RESULTS

The review included 287 studies with more than 280 000 older adults. One randomized clinical trial (RCT) (n = 4005) examined the direct effect of screening for cognitive impairment on patient outcomes, including potential harms, finding no significant differences in health-related quality of life at 12 months (effect size, 0.009 [95% CI, -0.063 to 0.080]). Fifty-nine studies (n = 38 531) addressed the accuracy of 49 screening instruments to detect cognitive impairment. The Mini-Mental State Examination was the most-studied instrument, with a pooled sensitivity of 0.89 (95% CI, 0.85 to 0.92) and specificity of 0.89 (95% CI, 0.85 to 0.93) to detect dementia using a cutoff of 23 or less or 24 or less (15 studies, n = 12 796). Two hundred twenty-four RCTs and 3 observational studies including more than 240 000 patients or caregivers addressed the treatment of MCI or mild to moderate dementia. None of the treatment trials were linked with a screening program; in all cases, participants were persons with known cognitive impairment. Medications approved to treat Alzheimer disease (donepezil, galantamine, rivastigmine, and memantine) improved scores on the ADAS-Cog 11 by 1 to 2.5 points over 3 months to 3 years. Psychoeducation interventions for caregivers resulted in a small benefit for caregiver burden (standardized mean difference, -0.24 [95% CI, -0.36 to -0.13) over 3 to 12 months. Intervention benefits were small and of uncertain clinical importance.

CONCLUSIONS AND RELEVANCE

Screening instruments can adequately detect cognitive impairment. There is no empirical evidence, however, that screening for cognitive impairment improves patient or caregiver outcomes or causes harm. It remains unclear whether interventions for patients or caregivers provide clinically important benefits for older adults with earlier detected cognitive impairment or their caregivers.

Validity, reliability, and psychometric properties of a computerized, cognitive assessment test (Cognivue®)

BACKGROUND

Cognitive issues such as Alzheimer’s disease and other dementias confer a substantial negative impact. Problems relating to sensitivity, subjectivity, and inherent bias can limit the usefulness of many traditional methods of assessing cognitive impairment.

AIM

To determine cut-off scores for classification of cognitive impairment, and assess Cognivue^® safety and efficacy in a large validation study.

METHODS

Adults (age 55-95 years) at risk for age-related cognitive decline or dementia were invited via posters and email to participate in two cohort studies conducted at various outpatient clinics and assisted- and independent-living facilities. In the cut-off score determination study (n = 92), optimization analyses by positive percent agreement (PPA) and negative percent agreement (NPA), and by accuracy and error bias were conducted. In the clinical validation study (n = 401), regression, rank linear regression, and factor analyses were conducted. Participants in the clinical validation study also completed other neuropsychological tests.

RESULTS

For the cut-off score determination study, 92 participants completed St. Louis University Mental Status (SLUMS, reference standard) and Cognivue^® tests. Analyses showed that SLUMS cut-off scores of < 21 (impairment) and > 26 (no impairment) corresponded to Cognivue^® scores of 54.5 (NPA = 0.92; PPA = 0.64) and 78.5 (NPA = 0.5; PPA = 0.79), respectively. Therefore, conservatively, Cognivue^® scores of 55-64 corresponded to impairment, and 74-79 to no impairment. For the clinical validation study, 401 participants completed ≥ 1 testing session, and 358 completed 2 sessions 1-2 wk apart. Cognivue^® classification scores were validated, demonstrating good agreement with SLUMS scores (weighted κ 0.57; 95%CI: 0.50-0.63). Reliability analyses showed similar scores across repeated testing for Cognivue^® (R² = 0.81; r = 0.90) and SLUMS (R² = 0.67; r = 0.82). Psychometric validity of Cognivue^® was demonstrated vs. traditional neuropsychological tests. Scores were most closely correlated with measures of verbal processing, manual dexterity/speed, visual contrast sensitivity, visuospatial/executive function, and speed/sequencing.

CONCLUSION

Cognivue^® scores ≤ 50 avoid misclassification of impairment, and scores ≥ 75 avoid misclassification of unimpairment. The validation study demonstrates good agreement between Cognivue^® and SLUMS; superior reliability; and good psychometric validity.

Estimating dementia cases amongst migrants living in Europe

BACKGROUND AND PURPOSE

The phenomenon of dementia amongst migrants and ethnic minorities represents an emerging concern for European healthcare systems, posing additional challenges in terms of clinical approach, access to care and resource utilization. The aim of the present study was to estimate the cases of dementia amongst immigrant older subjects living in Europe and in each European country.

METHODS

The estimated cases of dementia amongst older (i.e. 65+) migrants living in the European Union (EU-28) and European Free Trade Association member states were calculated by multiplying the number of migrants (obtained through the data provided by Eurostat) with the age- and sex-specific prevalence rates (derived by a recent meta-analysis).

RESULTS

Overall, 6 507 360 older migrants lived in Europe in 2017. In addition, 1 204 671 migrants were registered in Germany in 2010. Nearly 475 000 dementia cases (329 028 women, 147 410 men) were estimated in this population by applying age- and sex-specific prevalence rates. When considering each European country, the number of estimated cases ranged from 108 (Iceland) to 119 161 (France). In parallel, the proportion of dementia cases occurring in migrants ranged from 0.9% (Czech Republic) to 51.2% (Liechtenstein).

CONCLUSIONS

The issue of dementia in migrants and ethnic minorities is emerging but already relevant for European healthcare systems. The magnitude of this phenomenon and its complexities reinforce the need for coordinated initiatives both at a national and continental level. These epidemiological data should ideally be integrated with those coming from 'real world' services in order to better calibrate these actions.