Altered dynamic amplitude of low-frequency fluctuation in individuals at high risk for Alzheimer's disease.

The brain's dynamic spontaneous neural activity is significant in supporting cognition; however, how brain dynamics go awry in subjective cognitive decline (SCD) and mild cognitive impairment (MCI) remains unclear. Thus, the current study aimed to investigate the dynamic amplitude of low-frequency fluctuation (dALFF) alterations in patients at high risk for Alzheimer's disease and to explore its correlation with clinical cognitive assessment scales, to identify an early imaging sign for these special populations. A total of 152 participants, including 72 SCD patients, 44 MCI patients and 36 healthy controls (HCs), underwent a resting-state functional magnetic resonance imaging and were assessed with various neuropsychological tests. The dALFF was measured using sliding-window analysis. We employed canonical correlation analysis (CCA) to examine the bi-multivariate correlations between neuropsychological scales and altered dALFF among multiple regions in SCD and MCI patients. Compared to those in the HC group, both the MCI and SCD groups showed higher dALFF values in the right opercular inferior frontal gyrus (voxel P < .001, cluster P < .05, correction). Moreover, the CCA models revealed that behavioural tests relevant to inattention correlated with the dALFF of the right middle frontal gyrus and right opercular inferior frontal gyrus, which are involved in frontoparietal networks (R = .43, P = .024). In conclusion, the brain dynamics of neural activity in frontal areas provide insights into the shared neural basis underlying SCD and MCI.

Visual art therapy and its effects in older people with mild cognitive impairment: A systematic review.

INTRODUCTION: Mild cognitive impairment (MCI) is a known risk factor for the development of dementia. The potential benefits on cognition from non-pharmacological measures such as art-based interventions are of increasing interest. This systematic review examines the evidence for the impact of one form of art-based intervention, visual art therapy (VAT), on the cognition and psychological wellbeing of older people with MCI. METHODS: Randomised controlled and quasi-experimental trials evaluating the efficacy of VAT in older persons aged over 60 years with MCI were included. A search was performed on electronic databases: MEDLINE, CINAHL, Embase and PsycINFO. Joanna Briggs Institute critical appraisal and extraction tools were utilised for risk of bias assessment and data extraction, respectively. A narrative descriptive approach was used to outline the findings. RESULTS: Seven studies were identified from 4311 articles screened. Improvement in cognition was reported in five studies, with two of these reporting sustained improvement at 6-9 months, while the remaining three studies showed improvement only at the immediate post-intervention period. A positive impact was reported in four of six studies that examined the effect of VAT on participant psychological wellbeing. The overall methodological quality of the studies ranged from moderate in four of five RCTs, to high in the quasi-experimental studies and one RCT. However, the low study power in the context of small sample sizes limits the applicability of these studies to the population of interest. CONCLUSIONS: VAT is potentially an effective non-pharmacological intervention that may enhance cognition and provide benefits for psychological wellbeing in older persons with MCI. Given the limited studies available, with the majority emerging over the last 5 years, further research is required to confirm these reported benefits, as well as to determine whether VAT impacts on the progression of cognitive decline in MCI.

Atrophy of the cholinergic regions advances from early to late mild cognitive impairment.

PURPOSE: We investigated the volumetric changes in the components of the cholinergic pathway for patients with early mild cognitive impairment (EMCI) and those with late mild cognitive impairment (LMCI). The effect of patients' apolipoprotein 4 (APOE-ε4) allele status on the structural changes were analyzed. METHODS: Structural magnetic resonance imaging data were collected. Patients' demographic information, plasma data, and validated global cognitive composite scores were included. Relevant features were extracted for constructing machine learning models to differentiate between EMCI (n = 312) and LMCI (n = 541) and predict patients' neurocognitive function. The data were analyzed primarily through one-way analysis of variance and two-way analysis of covariance. RESULTS: Considerable differences were observed in cholinergic structural changes between patients with EMCI and LMCI. Cholinergic atrophy was more prominent in the LMCI cohort than in the EMCI cohort (P < 0.05 family-wise error corrected). APOE-ε4 differentially affected cholinergic atrophy in the LMCI and EMCI cohorts. For LMCI cohort, APOE-ε4 carriers exhibited increased brain atrophy (left amygdala: P = 0.001; right amygdala: P = 0.006, and right Ch123, P = 0.032). EMCI and LCMI patients showed distinctive associations of gray matter volumes in cholinergic regions with executive (R2 = 0.063 and 0.030 for EMCI and LMCI, respectively) and language (R2 = 0.095 and 0.042 for EMCI and LMCI, respectively) function. CONCLUSIONS: Our data confirmed significant cholinergic atrophy differences between early and late stages of mild cognitive impairment. The impact of the APOE-ε4 allele on cholinergic atrophy varied between the LMCI and EMCI groups.

Multi-domain cognition dysfunction accompanies frontoparietal and temporal amyloid accumulation in the elderly.

It is helpful to understand the pathology of Alzheimer's disease by exploring the relationship between amyloid-ß accumulation and cognition. The study explored the relationship between regional amyloid-ß accumulation and multiple cognitions and study their application value in the Alzheimer's disease diagnosis. 135 participants completed 18F-florbetapir Positron Emission Tomography (PET), structural MRI, and a cognitive battery. Partial correlation was used to examine the relationship between global and regional amyloid-ß accumulation and cognitions. Then, a support vector machine was applied to determine whether cognition-related accumulation regions can adequately distinguish the cognitively normal controls (76 participants) and mild cognitive impairment (30 participants) groups or mild cognitive impairment and Alzheimer's disease (29 participants) groups. The result showed that amyloid-ß accumulation regions were mainly located in the frontoparietal cortex, calcarine fissure, and surrounding cortex and temporal pole regions. Episodic memory-related regions included the frontoparietal cortices; executive function-related regions included the frontoparietal, temporal, and occipital cortices; and processing speed-related regions included the frontal and occipital cortices. Support vector machine analysis showed that only episodic memory-related amyloid-ß accumulation regions had better classification performance during the progression of Alzheimer's disease. Assessing regional changes in amyloid, particularly in frontoparietal regions, can aid in the early detection of amyloid-related decline in cognitive function.

Altered structural covariance of locus coeruleus in individuals with significant memory concern and patients with mild cognitive impairment.

The locus coeruleus (LC) is the site where tau accumulation is preferentially observed pathologically in Alzheimer's disease (AD) patients, but the changes in gray matter co-alteration patterns between the LC and the whole brain in the predementia phase of AD remain unclear. In this study, we estimated and compared the gray matter volume of the LC and its structural covariance (SC) with the whole brain among 161 normal healthy controls (HCs), 99 individuals with significant memory concern (SMC) and 131 patients with mild cognitive impairment (MCI). We found that SC decreased in MCI groups, which mainly involved the salience network and default mode network. These results imply that seeding from LC, the gray matter network disruption and disconnection appears early in the MCI group. The altered SC network seeding from the LC can serve as an imaging biomarker for discriminating the patients in the potential predementia phase of AD from the normal subjects.

Effects of square dance exercise on cognitive function in elderly individuals with mild cognitive impairment: the mediating role of balance ability and executive function.

BACKGROUND: Square dancing is a kind of aerobic fitness exercise without environmental restrictions that yields many benefits for physical and mental health; this exercise is popular among middle-aged and elderly people in China and in these populations in other countries. This study aimed to evaluate the effects of square dance exercise on the overall cognitive function of elderly individuals with mild cognitive impairment (MCI) and to research its mechanisms. METHODS: A total of 60 elderly people with MCI (60-69 years old) without square dance experience were selected and randomly divided into an experimental group (n = 30) and a control group (n = 30). The experimental group participated in square dance exercise for 12 weeks, while the control group maintained their original lifestyle habits. One week before and after the intervention period, the overall cognitive function, physical fitness, and executive function of both groups were measured. RESULTS: According to the results, square dance exercise directly improved the overall cognitive function of elderly individuals with MCI and indirectly affected overall cognitive function through the mediating effects of balance ability and executive function. CONCLUSIONS: Square dance exercise represents a nonpharmacological intervention for the prevention and treatment of MCI. Importantly, it is best to combine this exercise with other forms of physical exercise and comprehensive treatment programs such as cognitive training, social interaction, and psychological intervention to realize its maximum effect.

Early postoperative neurocognitive complications in elderly patients: comparing those with and without preexisting mild cognitive impairment- a prospective study.

BACKGROUND: As societies age, increasing numbers of older adults undergo surgeries with anesthesia. Postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) frequently occur in older surgical patients. Most of these patients already have preoperative mild cognitive impairment (MCI). However, the correlation between MCI and POD remains unclear. This study aimed to determine the incidence of POD in elderly patients with and without preexisting MCI. METHODS: A prospective study enrolled patients aged 60 years and above scheduled for major surgeries between December 2017 and April 2022. Preoperative MCI was determined by a Montreal Cognitive Assessment (MoCA) score between 18 and 24. POD was diagnosed using criteria from the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). POCD was characterized by a MoCA score reduction of 2 or more points from the preoperative score. The primary outcome was the incidence of POD within the first 72 h postoperatively. Secondary outcomes encompassed other postoperative complications, including POCD. RESULTS: The study comprised 223 elderly patients with MCI and 56 without MCI. The incidence of POD was 16.6% in the MCI group and 14.3% in the non-MCI group (P = 0.839). POCD occurred in 24.3% of MCI patients and 50% of non-MCI patients (P = 0.001). There were no significant differences in other postoperative complications between the groups. Postoperatively, the MCI group notably declined in visuospatial, attention, and orientation domains, while the non-MCI group declined in all domains except delayed recall. CONCLUSIONS: The incidence of POD was similar in the MCI and non-MCI groups. However, the non-MCI group demonstrated a higher incidence of POCD than the MCI group. This was identified by a reduction in postoperative MoCA scores for the visuospatial, naming, attention, language, abstraction, and orientation domains. These findings underscore the importance of postoperative cognitive assessments for both elderly patients with preexisting MCI and those with previously intact cognitive functions. TRIAL REGISTRATION: This trial was retrospectively registered in the Thai Clinical Trials Registry on 15/01/2019 (registration number: TCTR20190115001).

A mediation approach in resting-state connectivity between the medial prefrontal cortex and anterior cingulate in mild cognitive impairment.

Mild cognitive impairment (MCI) is recognized as the prodromal phase of dementia, a condition that can be either maintained or reversed through timely medical interventions to prevent cognitive decline. Considerable studies using functional magnetic resonance imaging (fMRI) have indicated that altered activity in the medial prefrontal cortex (mPFC) serves as an indicator of various cognitive stages of aging. However, the impacts of intrinsic functional connectivity in the mPFC as a mediator on cognitive performance in individuals with and without MCI have not been fully understood. In this study, we recruited 42 MCI patients and 57 healthy controls, assessing their cognitive abilities and functional brain connectivity patterns through neuropsychological evaluations and resting-state fMRI, respectively. The MCI patients exhibited poorer performance on multiple neuropsychological tests compared to the healthy controls. At the neural level, functional connectivity between the mPFC and the anterior cingulate cortex (ACC) was significantly weaker in the MCI group and correlated with multiple neuropsychological test scores. The result of the mediation analysis further demonstrated that functional connectivity between the mPFC and ACC notably mediated the relationship between the MCI and semantic fluency performance. These findings suggest that altered mPFC-ACC connectivity may have a plausible causal influence on cognitive decline and provide implications for early identifications of neurodegenerative diseases and precise monitoring of disease progression.

Prediction and validation of mild cognitive impairment in occupational dust exposure population based on machine learning.

OBJECTIVE: Workers exposed to dust for extended periods may experience varying degrees of cognitive impairment. However, limited research exists on the associated risk factors. This study aims to identify key variables using machine learning algorithms (ML) and develop a model to predict the occurrence of mild cognitive impairment in miners. METHODS: A total of 1938 miners were included in the study. Univariate analysis and multivariable logistic regression were employed to identify independent risk factors for cognitive impairment among miners. The dataset was randomly divided into a training set and a validation set in an 8:2 ratio of 1550 and 388 individuals, respectively. An additional group of 351 miners was collected as a test set for cognitive impairment assessment. Seven machine learning algorithms, including XGBoost, Logistic Regression, Random Forest, Complement Naive Bayes, Multi-layer Perceptron, Support Vector Machine, and K-Nearest Neighbors, were used to establish a predictive model for mild cognitive impairment in the dust-exposed population, based on baseline characteristics of the workers. The predictive performance of the models was evaluated using the Area Under the Receiver Operating Characteristic Curve (AUC), and the XGBoost model was further explained using the Shapley Additive exPlanations (SHAP) package. Cognitive function assessments using rank sum tests were conducted to compare differences in cognitive domains between the mild cognitive impairment group and the normal group. RESULTS: Univariate and multivariable logistic regression analyses revealed that education level, Age, Work years, SSRS (Self-Rating Scale for Stress), and HAMA (Hamilton Anxiety Rating Scale) were independent risk factors for cognitive impairment among dust-exposed workers. Comparative analysis of the performance of the seven machine learning algorithms demonstrated that XGBoost (training set: AUC=0.959, validation set: AUC=0.795) and Logistic Regression (training set: AUC=0.818, validation set: AUC=0.816) models exhibited superior predictive performance. Results from the test set showed that the AUC of the XGBoost model (AUC=0.913) outperformed the Logistic Regression model (AUC=0.778). Miners with mild cognitive impairment exhibited significant impairments (p<0.05) in visual-spatial abilities, attention, abstract thinking, and memory areas. CONCLUSION: Machine learning algorithms can predict the risk of cognitive impairment in this population, with the XGBoost algorithm showing the best performance. The developed model can guide the implementation of appropriate preventive measures for dust-exposed workers.

Effects of a dual intervention (motor and virtual reality-based cognitive) on cognition in patients with mild cognitive impairment: a single-blind, randomized controlled trial.

BACKGROUND: The increase in cases of mild cognitive impairment (MCI) underlines the urgency of finding effective methods to slow its progression. Given the limited effectiveness of current pharmacological options to prevent or treat the early stages of this deterioration, non-pharmacological alternatives are especially relevant. OBJECTIVE: To assess the effectiveness of a cognitive-motor intervention based on immersive virtual reality (VR) that simulates an activity of daily living (ADL) on cognitive functions and its impact on depression and the ability to perform such activities in patients with MCI. METHODS: Thirty-four older adults (men, women) with MCI were randomized to the experimental group (n = 17; 75.41 ± 5.76) or control (n = 17; 77.35 ± 6.75) group. Both groups received motor training, through aerobic, balance and resistance activities in group. Subsequently, the experimental group received cognitive training based on VR, while the control group received traditional cognitive training. Cognitive functions, depression, and the ability to perform activities of daily living (ADLs) were assessed using the Spanish versions of the Montreal Cognitive Assessment (MoCA-S), the Short Geriatric Depression Scale (SGDS-S), and the of Instrumental Activities of Daily Living (IADL-S) before and after 6-week intervention (a total of twelve 40-minutes sessions). RESULTS: Between groups comparison did not reveal significant differences in either cognitive function or geriatric depression. The intragroup effect of cognitive function and geriatric depression was significant in both groups (p < 0.001), with large effect sizes. There was no statistically significant improvement in any of the groups when evaluating their performance in ADLs (control, p = 0.28; experimental, p = 0.46) as expected. The completion rate in the experimental group was higher (82.35%) compared to the control group (70.59%). Likewise, participants in the experimental group reached a higher level of difficulty in the application and needed less time to complete the task at each level. CONCLUSIONS: The application of a dual intervention, through motor training prior to a cognitive task based on Immersive VR was shown to be a beneficial non-pharmacological strategy to improve cognitive functions and reduce depression in patients with MCI. Similarly, the control group benefited from such dual intervention with statistically significant improvements. TRIAL REGISTRATION: ClinicalTrials.gov NCT06313931; https://clinicaltrials.gov/study/NCT06313931 .

Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study.

INTRODUCTION: We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. METHODS: We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. RESULTS: We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. DISCUSSION: We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. HIGHLIGHTS: Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect of single-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.

Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: Algorithms and dataset.

For automatic EEG diagnosis, this paper presents a new EEG data set with well-organized clinical annotations called Chung-Ang University Hospital EEG (CAUEEG), which has event history, patient's age, and corresponding diagnosis labels. We also designed two reliable evaluation tasks for the low-cost, non-invasive diagnosis to detect brain disorders: i) CAUEEG-Dementia with normal, mci, and dementia diagnostic labels and ii) CAUEEG-Abnormal with normal and abnormal. Based on the CAUEEG dataset, this paper proposes a new fully end-to-end deep learning model, called the CAUEEG End-to-end Deep neural Network (CEEDNet). CEEDNet pursues to bring all the functional elements for the EEG analysis in a seamless learnable fashion while restraining non-essential human intervention. Extensive experiments showed that our CEEDNet significantly improves the accuracy compared with existing methods, such as machine learning methods and Ieracitano-CNN (Ieracitano et al., 2019), due to taking full advantage of end-to-end learning. The high ROC-AUC scores of 0.9 on CAUEEG-Dementia and 0.86 on CAUEEG-Abnormal recorded by our CEEDNet models demonstrate that our method can lead potential patients to early diagnosis through automatic screening.

Human hippocampal astrocytes: Computational dissection of their transcriptome, sexual differences and exosomes across ageing and mild-cognitive impairment.

The role of astrocytes in Alzheimer's disease is often disregarded. Hence, characterization of astrocytes along their early evolution toward Alzheimer would be greatly beneficial. However, due to their exquisite responsiveness, in vivo studies are difficult. So public microarray data of hippocampal homogenates from (healthy) young, (healthy) elder and elder with mild cognitive impairment (MCI) were subjected to re-analysis by a multi-step computational pipeline. Ontologies and pathway analyses were compared after determining the differential genes that, belonging to astrocytes, have splice forms. Likewise, the subset of molecules exportable to exosomes was also determined. The results showed that astrocyte's phenotypes changed significantly. While already 'activated' astrocytes were found in the younger group, major changes occurred during ageing (increased vascular remodelling and response to mechanical stimulus, diminished long-term potentiation and increased long-term depression). MCI's astrocytes showed some 'rejuvenated' features, but their sensitivity to shear stress was markedly lost. Importantly, most of the changes showed to be sex biassed. Men's astrocytes are enriched in a type 'endfeet-astrocytome', whereas women's astrocytes appear close to the 'scar-forming' type (prone to endothelial dysfunction, hypercholesterolemia, loss of glutamatergic synapses, Ca+2 dysregulation, hypoxia, oxidative stress and 'pro-coagulant' phenotype). In conclusion, the computational dissection of the networks based on the hippocampal gene isoforms provides a relevant proxy to in vivo astrocytes, also revealing the occurrence of sexual differences. Analyses of the astrocytic exosomes did not provide an acceptable approximation to the overall functioning of astrocytes in the hippocampus, probably due to the selective cellular mechanisms which charge the cargo molecules.

Memory performance mediates subjective sleep quality associations with cerebrospinal fluid Alzheimer's disease biomarker levels and hippocampal volume among individuals with mild cognitive symptoms.

Sleep disturbances are prevalent in Alzheimer's disease (AD), affecting individuals during its early stages. We investigated associations between subjective sleep measures and cerebrospinal fluid (CSF) biomarkers of AD in adults with mild cognitive symptoms from the European Prevention of Alzheimer's Dementia Longitudinal Cohort Study, considering the influence of memory performance. A total of 442 participants aged >50 years with a Clinical Dementia Rating (CDR) score of 0.5 completed the Pittsburgh Sleep Quality Index questionnaire and underwent neuropsychological assessment, magnetic resonance imaging acquisition, and CSF sampling. We analysed the relationship of sleep quality with CSF AD biomarkers and cognitive performance in separated multivariate linear regression models, adjusting for covariates. Poorer cross-sectional sleep quality was associated with lower CSF levels of phosphorylated tau and total tau alongside better immediate and delayed memory performance. After adjustment for delayed memory scores, associations between CSF biomarkers and sleep quality became non-significant, and further analysis revealed that memory performance mediated this relationship. In post hoc analyses, poorer subjective sleep quality was associated with lesser hippocampal atrophy, with memory performance also mediating this association. In conclusion, worse subjective sleep quality is associated with less altered AD biomarkers in adults with mild cognitive symptoms (CDR score 0.5). These results could be explained by a systematic recall bias affecting subjective sleep assessment in individuals with incipient memory impairment. Caution should therefore be exercised when interpreting subjective sleep quality measures in memory-impaired populations, emphasising the importance of complementing subjective measures with objective assessments.

Neuropsychological evaluation of phenoconversion risk in REM sleep behaviour disorder: A scoping review.

The objective of this study was to assess the role of cognitive evaluation in the prediction of phenoconversion in polysomnography-confirmed idiopathic or isolated rapid eye movement sleep behaviour disorder, through a scoping review focussing on a longitudinal comprehensive neuropsychological assessment of patients with idiopathic REM sleep behaviour disorder. A literature search (2006-2022) yielded 1034 records, and 20 were selected for analysis. The sample included 899 patients from eight different cohorts and five countries. We extracted data on clinical evolution, mild cognitive impairment diagnosis, neuropsychological tests used, and classification of cognitive domains. Tests, cognitive domains, and mild cognitive impairment definitions were heterogeneous across the studies, precluding a meta-analysis. Ten studies (50%) evaluated the presence of mild cognitive impairment; 14 studies (70%) grouped neuropsychological tests into between three (6 studies, 21.4%) and seven (1 study, 7.1%) cognitive domains. The most frequently used tests were semantic fluency, Stroop colour word test, trail making test A and B, digit span, Rey auditory verbal learning test, and Rey-Osterrieth figure. All except digit span showed a role in predicting phenoconversion. The authors did not consistently assign tests to specific cognitive domains. In conclusion, we discuss methodological differences between the studies and highlight the need for a standardised framework for neuropsychological data acquisition and presentation, based on a multilevel approach covering test selection, domain assignment, and mild cognitive impairment diagnostic criteria.

Living well while providing support: validation of LTCQ-Carer for assessing informal carers' quality of life.

PURPOSE: Despite international policies to support the health and wellbeing of informal (family) caregivers, there is no consensus on how to evaluate the effectiveness of carer support. We aimed to develop and validate a new quality-of-life measure for carers (LTCQ-Carer) and to assess its potential for use within a clinical pathway. METHODS: Psychometric properties of LTCQ-Carer were tested through cognitive interviews (qualitative phase) and a pilot survey (quantitative phase). Participants were family caregivers of people recently diagnosed with mild cognitive impairment (MCI) or dementia, recruited through one of 14 memory clinics in south-east England. They self-completed the new measure and comparative existing measures (EQ-5D, ASCOT-Carer). Ongoing feedback from memory clinic staff on potential use of LTCQ-Carer was collected. RESULTS: Interview participants (n = 10) found all draft items of LTCQ-Carer relevant and prompted inclusion of a new item on 'time to yourself'. Responses from survey participants (n = 107) indicated acceptability (low missing data), high internal reliability (Cronbach's α = 0.95), and a general construct (single factor loadings 0.43-0.86 for all items). Observation of predicted associations with EQ-5D and ASCOT-Carer supported construct validity. Responsiveness requires further testing as evidence was inconclusive. Clinical staff feedback on potential use was positive. CONCLUSION: LTCQ-Carer is a valid new measure for assessing family caregivers' quality of life across broad health and social care domains, expanding the range of high-quality tools for evaluating carer support. When used concurrently with patient assessment, it could highlight carer needs and prompt appropriate family support at the earliest point in the clinical pathway.

Cognitive profile of people with mild behavioral impairment in Brain Health Registry participants.

OBJECTIVES: Dementia assessment includes cognitive and behavioral testing with informant verification. Conventional testing is resource-intensive, with uneven access. Online unsupervised assessments could reduce barriers to risk assessment. The aim of this study was to assess the relationship between informant-rated behavioral changes and participant-completed neuropsychological test performance in older adults, both measured remotely via an online unsupervised platform, the Brain Health Registry (BHR). DESIGN: Observational cohort study. SETTING: Community-dwelling older adults participating in the online BHR. Informant reports were obtained using the BHR Study Partner Portal. PARTICIPANTS: The final sample included 499 participant-informant dyads. MEASUREMENTS: Participants completed online unsupervised neuropsychological assessment including Forward Memory Span, Reverse Memory Span, Trail Making B, and Go/No-Go tests. Informants completed the Mild Behavioral Impairment Checklist (MBI-C) via the BHR Study Partner portal. Cognitive performance was evaluated in MBI+/- individuals, as was the association between cognitive scores and MBI symptom severity. RESULTS: Mean age of the 499 participants was 67, of which 308/499 were females (61%). MBI + status was associated with significantly lower memory and executive function test scores, measured using Forward and Reverse Memory Span, Trail Making Errors and Trail Making Speed. Further, significant associations were found between poorer objectively measured cognitive performance, in the domains of memory and executive function, and MBI symptom severity. CONCLUSION: These findings support the feasibility of remote, informant-reported behavioral assessment utilizing the MBI-C, supporting its validity by demonstrating a relationship to online unsupervised neuropsychological test performance, using a previously validated platform capable of assessing early dementia risk markers.

New balance capability index as a screening tool for mild cognitive impairment.

BACKGROUND: Mild cognitive impairment (MCI) is not just a prodrome to dementia, but a very important intervention point to prevent dementia caused by Alzheimer's disease (AD). It has long been known that people with AD have a higher frequency of falls with some gait instability. Recent evidence suggests that vestibular impairment is disproportionately prevalent among individuals with MCI and dementia due to AD. Therefore, we hypothesized that the measurement of balance capability is helpful to identify individuals with MCI. METHODS: First, we developed a useful method to evaluate balance capability as well as vestibular function using Nintendo Wii balance board as a stabilometer and foam rubber on it. Then, 49 healthy volunteers aged from 56 to 75 with no clinically apparent cognitive impairment were recruited and the association between their balance capability and cognitive function was examined. Cognitive functions were assessed by MoCA, MMSE, CDR, and TMT-A and -B tests. RESULTS: The new balance capability indicator, termed visual dependency index of postural stability (VPS), was highly associated with cognitive impairment assessed by MoCA, and the area under the receiver operating characteristic (ROC) curve was more than 0.8, demonstrating high sensitivity and specificity (app. 80% and 60%, respectively). CONCLUSIONS: Early evidence suggests that VPS measured using Nintendo Wii balance board as a stabilometer helps identify individuals with MCI at an early and preclinical stage with high sensitivity, establishing a useful method to screen MCI.

The effect of Mild Cognitive Impairment (MCI) on psychological distress among older adults in Ukraine.

OBJECTIVES: Understanding the negative consequences of Mild Cognitive Impairment (MCI) in Ukraine among a population who have collectively experienced difficult life events, provided the impetus for the current study which analyzed whether the perception of psychological distress differed among older adults with two types of MCI (amnestic MCI [aMCI] & nonamnestic MCI [naMCI]) compared to their cognitively intact peers. METHOD: A sample of 132 older adults were selected from an outpatient regional hospital in Lviv, Ukraine and assigned into either an MCI or non-MCI control group. A demographic survey, and the Symptom Questionnaire (SQ) were administered to both groups. RESULTS: Results of an ANOVA comparing the SQ sub-scales between the Ukrainian MCI and control groups were analyzed. A multiple hierarchical regression analysis assessed the predictive value of MoCA scores on the SQ sub-scales. Compared to adults in the MCI group, adults in the control group reported significantly lower rates of anxiety, somatic, depressive symptoms, and total psychological distress. DISCUSSION: While the level of cognitive impairment was a significant predictor for each sub-type of distress, the explained variance was minimal suggesting that other factors also played a role. Reference was made to a similar MCI sample in the U.S. which had lower SQ psychological distress scores than the Ukraine sample, further suggesting possible environmental effects on symptoms. The importance of depression and anxiety screening and treatment for older adults with MCI was also discussed.

Assessment of subjective and objective masticatory function among elderly individuals with mild cognitive impairment.

BACKGROUND: Masticatory function is known to be related to cognitive ability; therefore, factors for improving masticatory function should be identified. AIMS: This study aimed to identify factors influencing masticatory function associated with mild cognitive impairment (MCI) in elderly individuals. METHODS: A total of 123 elderly participants [mean age: 76.5 ± 6.5 years; 82 females (66.7%), 41 males (33.3%)] were included. Cognitive function was evaluated by the Korean version of the Mini-Mental State Examination (KMMSE). Questionnaires for subjective evaluation were administered, and dynamic objective masticatory function evaluations, including chewing tests and bite force measurements, were performed. Intergroup differences were evaluated by the Wilcoxon rank-sum and chi-square test, and correlations between cognitive ability and masticatory function were evaluated by multilinear logistic regression. RESULTS: The number of teeth, number of posterior teeth, bite force, masticatory ability index (MAI) and posterior support status showed significant differences between the normal (KMMSE > 23) and MCI (KMMSE ≤ 23) groups. However, only the MAI, representing dynamic masticatory performance, was significantly associated with MCI regardless of age, sex and removable prostheses. The number of teeth and posterior teeth, bite force, subjective masticatory ability and posterior occlusal support showed no significant association with MCI. DISCUSSION: These results suggested the importance of chewing function for preventing the progression of cognitive impairment. CONCLUSIONS: Considering that only the MAI was significantly associated with MCI, it is more important to improve chewing efficiency by harmonizing therapeutic prosthetics with the surrounding masticatory system than simply increasing the number of teeth to prevent or delay cognitive impairment in elderly individuals.