Screening For Cognitive Impairment Research Articles

Brain Health Registry Study Partner Portal: Novel infrastructure for digital, dyadic data collection.

In Alzheimer's disease (AD) research, subjective reports of cognitive and functional decline from participant-study partner dyads is an efficient method of assessing cognitive impairment and clinical progression. Demographics and subjective cognitive/functional decline (Everyday Cognition Scale [ECog]) scores from dyads enrolled in the Brain Health Registry (BHR) Study Partner Portal were analyzed. Associations between dyad characteristics and both ECog scores and study engagement were investigated. A total of 10,494 BHR participants (mean age=66.9±12.16 standard deviations, 67.4% female) have enrolled study partners (mean age=64.3±14.3 standard deviations, 49.3% female), including 8987 dyads with a participant 55 years of age or older. Older and more educated study partners were more likely to complete tasks and return for follow-up. Twenty-five percent to 27% of older adult participants had self and study partner-report ECog scores indicating a possible cognitive impairment. The BHR Study Partner Portal is a unique digital tool for capturing dyadic data, with high impact applications in the clinical neuroscience and AD fields. Highlights The Brain Health Registry (BHR) Study Partner Portal is a novel, digital platform of>10,000 dyads. Collection of dyadic online subjective cognitive and functional data is feasible. The portal has good usability as evidenced by positive study partner feedback. The portal is a potential scalable strategy for cognitive impairment screening in older adults.

An explainable machine learning model of cognitive decline derived from speech.

Traditional Alzheimer's disease (AD) and mild cognitive impairment (MCI) screening lacks the sensitivity and timeliness required to detect subtle indicators of cognitive decline. Multimodal artificial intelligence technologies using only speech data promise improved detection of neurodegenerative disorders. Speech collected over the telephone from 91 older participants who were cognitively healthy (n=29) or had diagnoses of AD (n=30) or amnestic MCI (aMCI; n=32) was analyzed with multimodal natural language and speech processing methods. An explainable ensemble decision tree classifier for the multiclass prediction of cognitive decline was created. This approach was 75% accurate overall-an improvement over traditional speech-based screening tools and a unimodal language-based model. We include a dashboard for the examination of the results, allowing for novel ways of interpreting such data. This work provides a foundation for a meaningful change in medicine as clinical translation, scalability, and user friendliness were core to the methodologies. Remote assessments and artificial intelligence (AI) models allow greater access to cognitive decline screening.Speech impairments differ significantly between mild AD, amnestic mild cognitive impairment (aMCI), and healthy controls.AI predictions of cognitive decline are more accurate than experts and standard tools.The AI model was 75% accurate in classifying mild AD, aMCI, and healthy controls.

Improving clinical efficiency in screening for cognitive impairment due to Alzheimer's.

To reduce demands on expert time and improve clinical efficiency, we developed a framework to evaluate whether inexpensive, accessible data could accurately classify Alzheimer's disease (AD) clinical diagnosis and predict the likelihood of progression. We stratified relevant data into three tiers: obtainable at primary care (low-cost), mostly available at specialty visits (medium-cost), and research-only (high-cost). We trained several machine learning models, including a hierarchical model, an ensemble model, and a clustering model, to distinguish between diagnoses of cognitively unimpaired, mild cognitive impairment, and dementia due to AD. All models showed viable classification, but the hierarchical and ensemble models outperformed the conventional model. Classifier "error" was predictive of progression rates, and cluster membership identified subgroups with high and low risk of progression within 1.5 to 3 years. Accessible, inexpensive clinical data can be used to guide AD diagnosis and are predictive of current and future disease states. Classification performance using cost-effective features was accurate and robustHierarchical classification outperformed conventional multinomial classificationClassification labels indicated significant changes in conversion risk at follow-upA clustering-classification method identified subgroups at high risk of decline.

Psychology-based analysis of cognitive barriers of corporate financial risk assessors and countermeasures

BackgroundIn corporate financial risk assessment, the cognitive ability of personnel plays an important role in accurately assessing and predicting risks. Therefore, it is of great significance to study the cognitive impairment of corporate financial risk assessment personnel and their countermeasures by combining psychological analysis.Subjects and MethodsThis study used psychological scales and cognitive paradigms for research. The study selected 50 staff members from a financial enterprise as the research subjects and randomly divided them into an experimental group and a control group, each consisting of 25 people. Data analysis was conducted using the Simplified Mental Intelligence Scale and the Code-recognition episodic memory paradigm, and the data was processed using SPSS22.0.ResultsBy simplifying the analysis of MMSE sub-items, the two items with the strongest discriminative ability for MCI were identified, namely MMSE12 and MMSE19. The average cognitive speed score of the evaluators in the experimental group was 0.56 seconds, while the average cognitive speed score of the evaluators in the control group was 0.42 seconds. The t-test results showed a significant difference in cognitive speed between the two groups (P<0.01).ConclusionsBABRI-mini MMSE and BABRI-EMT are suitable for rapid screening of cognitive impairment for corporate financial risk assessors. MMSE12 and MMSE19 can be used as valid indicators for assessing cognitive impairment, and the application of the situational memory scale can further improve discriminative ability. This suggests that psychology-based analysis can help corporate financial risk assessors detect and respond to cognitive impairment promptly and improve the accuracy and reliability of assessment.AcknowledgementThe Hunan Provincial Department of Science and Technology, Hunan International Economics University (No. 2014GK3147); Provincial soft Science Key Project of Science and Technology Department of Hunan Province (No. 2013ZK2024).

Cost Evaluation of Professional Services in a Rural Community Pharmacy: A Monocentric Exploratory Approach.

The increasing pressure on healthcare systems (HCSs) is a cause for concern worldwide. Rising costs, uncertainty about sustainability, and aging populations are the main issues that make it challenging to allocate scarce resources to the needs of HCSs. Clinical professional pharmacy services (PSs) have been shown to help alleviate system stress and to reach the entire population, although a cost of provision is borne. The objective of this study was to evaluate the provision costs of three PSs, a medicine-dispensing service (MDS), a multicompartmental compliance aid system service (MCAS), and a cognitive impairment screening service (CISS), in a rural community pharmacy. A cost analysis was performed using a time-driven activity-based costing model. The time dedicated to PS provision was appropriately recorded, and the corresponding expenses were extracted from the accounting records. A provision time of 4.80 min and a cost of EUR 2.24 were estimated for the MDS, while 18.33 min and EUR 8.73 were calculated for the MCAS, and 122.20 min and EUR 56.72 were calculated for the CISS. The total provision time represented 85% of the pharmacist's effective working time. Tailored cost analysis is a useful tool for making decisions on the implementation of a PS. Larger studies including a variety of pharmacies and locations are necessary to accurately assess costs and engage in discussions on funding and remuneration.

Post-traumatic stress disorder symptoms and quality of life among older patients with cancer during the COVID-19 pandemic

IntroductionThe Coronavirus (COVID-19) pandemic and its associated health restrictions have harmed the population psychologically. We aimed to compare the post-traumatic stress disorder (PTSD) symptoms and Quality of Life (QoL) in older French patients with cancer to the younger ones. Materials and MethodsThis longitudinal multicenter study named COVIPACT began in April 2020 during the first French lockdown and has included 579 outpatients receiving treatment for a solid or hematological malignancy. Data were collected every three months, namely at the first release period (M3), at the second lockdown (M6), at the second release period (M9), and finally at the last curfew period (M12) in France. Standardized validated self-questionnaires were used to assess PTSD symptoms (using the Event Scale–Revised self-questionnaire), insomnia (through the Insomnia Severity Index questionnaire), QoL (using the Functional Assessment of Cancer Therapy - General questionnaire), and cognitive complaints (through the Functional Assessment of Cancer Therapy – Cognition questionnaire). Student (or Wilcoxon) tests and Chi-squared tests were used for continuous or discrete variables, respectively. We conducted linear mixed model to study the change during follow-up. ResultsOut of 579 included patients, 157 (27%) were ≥ 70 years old at baseline, of whom 104 participated in the longitudinal study. At baseline, older patients reported fewer PTSD symptoms (17% versus 23%, p = .06), insomnia (17% versus 27%, p = .02), and cognitive complaint (3% versus 16%, p < .01) than younger patients. QoL at baseline was similar between age subgroups. We observed no significant difference in the trajectory of PTSD symptoms, insomnia, or emotional well-being between both groups during the follow-up. Cognitive complaints were lower at baseline in older patients but steadily increased during the follow-up and reached the same level as younger patients at one year. DiscussionOne in five older patients reported PTSD symptoms, evolving similarly to younger patients during the first year of the COVID-19 pandemic. While cognitive complaints tend to recover in a bell-shaped curve at one year in younger patients, the trend is increasing in older ones. Screening for PTSD symptoms and late cognitive impairment should be given special attention in older patients.Trial Registration:Clinicaltrials.gov identifier: NCT04366154

Detection of Mild Cognitive Impairment Using a Spiral Drawing Test

Information and communication technology-based monitoring services for the elderly can be improved by using a monitoring function that automatically detects cognitive decline. Therefore, we developed a system that provides a brief screening for mild cognitive impairment (MCI). This screening is performed by measuring the performance of two tasks completed simultaneously on a tablet device, such as drawing a spiral and counting color changes. First, we used this system to measure and analyze three groups: elderly persons suspected of having MCI, elderly persons with no cognitive impairment, and healthy young adults. We extracted evaluation parameters relevant for determining MCI through analysis. Furthermore, we developed a detection method using the evaluation parameters and performed an evaluation. Cross-validation revealed that the sensitivity and specificity of this method were 90.0% and 75.0%, respectively.

Normative Data for Single-Letter Controlled Oral Word Association Test in Older White Australians and Americans, African-Americans, and Hispanic/Latinos.

The Controlled Oral Word Association Test (COWAT) is a commonly used measure of verbal fluency. While a normal decline in verbal fluency occurs in late adulthood, significant impairments may indicate brain injury or diseases such as Alzheimer's disease. Normative data is essential to identify when test performance falls below expected levels based on age, gender, and education level. This study aimed to establish normative performance data on single-letter COWAT for older community-dwelling adults. Over 19,000 healthy men and women, without a diagnosis of dementia or a Modified Mini-Mental State Examination score below 77/100, were recruited for the ASPREE trial. Neuropsychological assessments, including the COWAT with letter F, were administered at study entry. Median participant age was 75 years (range 65-98), with 56.5% being women. The majority of participants had 9-11 years of education in Australia and over 12 years in the U.S. The COWAT performance varied across ethno-racial groups and normative data were thus presented separately for 16,335 white Australians, 1,084 white Americans, 896 African-Americans, and 316 Hispanic/Latinos. Women generally outperformed men in the COWAT, except for Hispanic/Latinos. Higher education levels consistently correlated with better COWAT performance across all groups, while the negative association with age was weaker. This study provides comprehensive normative data for the COWAT stratified by ethno-racial groups in Australia and the U.S., considering age, gender, and education level. These norms can serve as reference standards for screening cognitive impairments in older adults in both clinical and research settings.

Which cut-off value of the Montreal Cognitive Assessment should be used for post-stroke cognitive impairment? A systematic review and meta-analysis of studies on diagnostic test accuracy.

Post-stroke cognitive impairment (PSCI) is one of the serious complications of stroke. The Montreal Cognitive Assessment (MoCA), as a brief cognitive impairment screening tool, is widely used in stroke survivors. However, some studies have suggested that the use of the universal cut-off value of 26 may be inappropriate for detecting cognitive impairments in stroke settings. We conducted this study to identify the optimal cut-off value of the MoCA in screening for PSCI. PubMed, CINAHL, Embase, the Cochrane Library, and Web of Science were searched for eligible studies until March 23, 2023. All studies were screened by two independent researchers. The quality of each article was evaluated by the Quality Assessment of Diagnostic Accuracy Studies-2 tool. A bivariate mixed effects model was used to pool sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and the summary receiver operating characteristic curve. 24 studies with a total of 4,231 patients were included in this review. Despite the lack of evidence of publication bias, a high degree of heterogeneity was observed. Meta-analysis revealed that a cut-off value of 21/22 yielded the best diagnostic accuracy. The optimal cut-off varied in different regions, stroke types, and stroke phases as well. The optimal cut-off of MoCA was 21/22 for stroke populations rather than the initially recommended cut-off of 26. A revised (lower) cut-off should be considered for stroke survivors.

Diagnostic accuracy of Ascertain Dementia 8-item Questionnaire by participant and informant-A systematic review and meta-analysis.

The Ascertain Dementia 8-item Questionnaire (AD8) is a screening tool for cognitive impairment that can be administered to older persons and/or their informants. To evaluate the diagnostic accuracy and compare the predictive parameters of the informant and participant-completed Ascertain Dementia 8-item Questionnaire (iAD8 and pAD8, respectively) in older adults with cognitive impairment. We searched ten electronic databases (including MEDLINE (Ovid), Embase) from tool inception to March 2022. We included studies with patients ≥60 years old that were screened for cognitive impairment using AD8 in any healthcare setting. Predictive parameters were assessed against reference standards to estimate accuracy and diagnostic ability using bivariate random-effects meta-analyses. We used QUADAS-2 criteria to assess risk of bias. A cut-off of ≥2/8 was used to classify mild cognitive impairment (MCI), dementia, and cognitive impairment (MCI or dementia). Seven studies using the iAD8 (n = 794) showed a sensitivity of 80% and specificity of 79% to detect MCI. Nine studies using the iAD8 (n = 2393) established 91% sensitivity and 64% specificity to detect dementia. To detect MCI using the pAD8, four studies (n = 836) showed 57% sensitivity and 71% specificity. To detect dementia using the pAD8, four studies (n = 3015) demonstrated 82% sensitivity and 75% specificity. Recurring high or unclear risk of bias was noted in the domains of "Index test" and "reference standard". The diagnostic accuracy of iAD8 is superior to that of pAD8 when screening for cognitive impairment. The AD8 may be an acceptable alternative to screen for cognitive impairment in older adults when there are limitations to formal testing.

Prediction of conversion to dementia disorders based on timed up and go dual-task test verbal and motor outcomes: a five-year prospective memory-clinic-based study

BackgroundWhile assessment tools can increase the detection of cognitive impairment, there is currently insufficient evidence regarding clinical outcomes based on screening for cognitive impairment in older adults.MethodsThe study purpose was to investigate whether Timed Up and Go dual-task test (TUGdt) results, based on TUG combined with two different verbal tasks (name different animals, TUGdt-NA, and recite months in reverse order, TUGdt-MB), predicted dementia incidence over a period of five years among patients (N = 186, mean = 70.7 years; 45.7% female) diagnosed with Subjective Cognitive Impairment (SCI) and Mild Cognitive Impairment (MCI) following assessment at two memory clinics. Associations between TUG parameters and dementia incidence were examined in Cox regression models.ResultsDuring follow-up time (median (range) 3.7 (0.1–6.1) years) 98 participants converted to dementia. Novel findings indicated that the TUGdt parameter words/time, after adjustment for age, gender, and education, can be used for the prediction of conversion to dementia in participants with SCI or MCI over a period of five years. Among the TUG-related parameters investigated, words/time showed the best predictive capacity, while time scores of TUG and TUGdt as well as TUGdt cost did not produce significant predictive results. Results further showed that the step parameter step length during TUGdt predicts conversion to dementia before adjustment for age, gender, and education. Optimal TUGdt cutoffs for predicting dementia at 2- and 4-year follow-up based on words/time were calculated. The sensitivity of the TUGdt cutoffs was high at 2-year follow-up: TUGdt-NA words/time, 0.79; TUGdt-MB words/time, 0.71; reducing respectively to 0.64 and 0.65 at 4-year follow-up.ConclusionsTUGdt words/time parameters have potential as cost-efficient tools for conversion-to-dementia risk assessment, useful for research and clinical purposes. These parameters may be able to bridge the gap of insufficient evidence for such clinical outcomes.Trial registrationClinicalTrials.gov Identifier: NCT05893524: https://www.clinicaltrials.gov/study/NCT05893524?id=NCT05893524&rank=1.

Optimal cut-off MoCA score for screening for mild cognitive impairment in elderly individuals in China: A systematic review and meta-analysis.

To evaluate the optimal cut-off MoCA score for elderly individuals with MCI. A systematic review and meta-analysis. Articles were retrieved from PubMed, Ovid, Embase, The Cochrane Library, PsycINFO, CBM, CNKI, WanFang and CQVIP and were assessed by using the Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). Figures of the assessment were made by using Review Manager 5.3, and a meta-analysis of the data was conducted by using Bivariate Random-effects Meta-Analysis (BRMA) via Stata 14.0. Seventeen articles were retrieved from the database, and when the cut-offs were 24/25 and 25/26, they represented the same diagnostic value; in addition, the AUC was 0.96, which demonstrated high predictive validity for mild cognitive impairment screening. However, the sensitivity was higher with 25/26 (se=0.95, sp=0.80), whereas the specificity was higher with 24/25 (se=0.92, sp=0.89).

The impact of cognitive impairment in urologic implants: a narrative review.

With the general population aging and thus more patients developing bothersome erectile dysfunction, stress urinary incontinence and overactive bladder, there will likely be a higher demand for three common interactive implants in urology, the penile prosthesis, artificial urinary sphincter (AUS) and sacral neuromodulation (SNM). Further, the prevalence of mild and major neurocognitive disorders (also known as mild cognitive impairment and dementia, respectively) is expected to increase. While the aforementioned urologic implants have excellent short and long term outcomes, there are also known device issues such as malfunction or misuse that may require surgical removal and/or revision. The objective of this narrative review is to describe the association of cognitive impairment and urologic implants. We performed a search on PubMed between the years 1975-2023 for English language articles that reported on any type or severity of cognitive impairment and its association with penile prosthesis, AUS and/or SNM. While peer-reviewed published manuscripts were prioritized, abstracts that fit our search criteria were also included. Data assessing outcomes of patients with cognitive impairment who undergo placement of a urologic implant are limited. There is an association between AUS failure or misuse with cognitive impairment. SNM is efficacious in this population in the short term. In patients who develop dementia, an inflatable penile prosthesis can be deflated via in-office needle puncture and an AUS can be deactivated. The Memory Alteration Test, Quick Screen for Mild Cognitive Impairment and the Saint Louis University Mental Status Examination are relatively quick screening tests with good sensitivity and specificity for mild cognitive impairment. While data on the association between urologic implants and cognitive impairment are sparse, there are tools that urologists can use to screen patients for cognitive impairment. With screening, urologists can provide appropriate preoperative counseling (including recommending against implantation) and can provide closer postoperative monitoring. Further study is required to assess which patients should be excluded from device implantation and how to properly assess for cognitive impairment in a manner that is both beneficial for the patient and convenient and efficient for a urologist.

Diagnostic Sensitivity and Specificity of Cognitive Tests for Mild Cognitive Impairment and Alzheimer's Disease in Patients with Down Syndrome: A Systematic Review and Meta-Analysis.

Improved health care for people with Down syndrome (DS) has resulted in an increase in their life expectancy therefore increasing comorbidities associated with age-related problems in this population, the most frequent being Alzheimer's disease (AD). To date, several cognitive tests have been developed to evaluate cognitive changes related to the development of mild cognitive impairment (MCI) and AD in people with DS. Identify and evaluate available cognitive tests for the diagnosis of MCI and AD in people with DS. A systematic search of the Pubmed and PsycInfo databases was performed to identify articles published from January 1, 2000 and July 1, 2022. Keysearch terms were DS, AD or MCI, cognition, and assessment. Relevant studies assessing the diagnostic accuracy of cognitive tests for AD or MCI with standard clinical evaluation were extracted. Risk of bias was assessed using the QUADAS 2. We identified 15 batteries, 2 intelligence scales, 14 memory tests, 11 executive, functioning tests, 11 motor and visuospatial functioning tests, 5 language tests, 3 attention tests, and 2 orientation tests. Analysis showed that the CAMCOG-DS present a fair to excellent diagnostic accuracy for detecting AD in patients with DS. However, for the diagnosis of MCI, this battery showed poor to good diagnostic accuracy. The findings highlight important limitations of the current assessment available for the screening of mild cognitive impairment and AD in patients with DS and support the need for more clinical trials to ensure better screening for this highly at-risk population.

Shanghai Cognitive Screening: A Mobile Cognitive Assessment Tool Using Voice Recognition to Detect Mild Cognitive Impairment and Dementia in the Community.

A rapid digital instrument is needed to facilitate community-based screening of mild cognitive impairment (MCI) and Alzheimer's disease (AD) in China. We developed a voice recognition-based cognitive assessment (Shanghai Cognitive Screening, SCS) on mobile devices and evaluated its diagnostic performance. Participants (N = 251) including healthy controls (N = 98), subjective cognitive decline (SCD, N = 42), MCI (N = 80), and mild AD (N = 31) were recruited from the memory clinic at Shanghai Sixth People's Hospital. The SCS is fully self-administered, takes about six minutes and measures the function of visual memory, language, and executive function. Participants were instructed to complete SCS tests, gold-standard neuropsychological tests and standardized structural 3T brain MRI. The Cronbach's alpha was 0.910 of the overall scale, indicating high internal consistency. The SCS total score had an AUC of 0.921 to detect AD (sensitivity = 0.903, specificity = 0.945, positive predictive value = 0.700, negative predictive value = 0.986, likelihood ratio = 16.42, number needed for screening utility = 0.639), and an AUC of 0.838 to detect MCI (sensitivity = 0.793, specificity = 0.671, positive predictive value = 0.657, negative predictive value = 0.803, likelihood ratio = 2.41, number needed for screening utility = 0.944). The subtests demonstrated moderate to high correlations with the gold-standard tests from their respective cognitive domains. The SCS total score and its memory scores all correlated positively with relative volumes of the whole hippocampus and almost all subregions, after controlling for age, sex, and education. The SCS has good diagnostic accuracy for detecting MCI and AD dementia and has the potential to facilitate large-scale screening in the general community.

Sustained improvement of intrinsic capacity in community-dwelling older adults: The +AGIL Barcelona multidomain program.

Different programs promote healthy ageing through the optimization of intrinsic capacity. However, a major challenge is to assess their sustained effects over time. +AGIL Barcelona, a consolidated multidomain program, aims to optimize older adults' intrinsic capacity through a coordinated approach among primary care, geriatrics and community resources, in agreement with the integrated care for older people (ICOPE) guidelines. We aimed to evaluate the +AGIL Barcelona longitudinal effect on older adults' physical performance. All +AGIL Barcelona consecutive participants since 2016 were enrolled. After a comprehensive geriatric assessment, a tailored, multidisciplinary intervention aligned with the ICOPE guidelines is offered. It includes a 10-week boost multicomponent exercise program, nutritional and sleep-hygiene counselling, revision and optimization of pharmacological treatments and screening for cognitive impairment, depression and loneliness. Changes in physical performance after 3 and 6 months were assessed using mixed models including baseline frailty degree, time and all potential significant confounders. We included 194 participants in the analysis (mean age=81.6 [standard deviation=5.8], 68% women). An independent, clinically and statistically significant improvement in physical performance (Short Physical Performance Battery [SPPB] test, combining gait speed, strength and balance) was found at 3 months (SPPB mean change: 1.4; 95% CI: 1.1-1.6) and 6 months (SPPB mean change: 1.1; 95% CI 0.8-1.5). Equivalent results were observed for all the SPPB sub-tests. A coordinated, multidisciplinary and integrated program can benefit older adults' intrinsic capacity. The participants' empowerment and the connection with the available community resources are critical points for a successful intervention.

Screening for Mild Cognitive Impairment with Speech Interaction Based on Virtual Reality and Wearable Devices.

Significant advances in sensor technology and virtual reality (VR) offer new possibilities for early and effective detection of mild cognitive impairment (MCI), and this wealth of data can improve the early detection and monitoring of patients. In this study, we proposed a non-invasive and effective MCI detection protocol based on electroencephalogram (EEG), speech, and digitized cognitive parameters. The EEG data, speech data, and digitized cognitive parameters of 86 participants (44 MCI patients and 42 healthy individuals) were monitored using a wearable EEG device and a VR device during the resting state and task (the VR-based language task we designed). Regarding the features selected under different modality combinations for all language tasks, we performed leave-one-out cross-validation for them using four different classifiers. We then compared the classification performance under multimodal data fusion using features from a single language task, features from all tasks, and using a weighted voting strategy, respectively. The experimental results showed that the collaborative screening of multimodal data yielded the highest classification performance compared to single-modal features. Among them, the SVM classifier using the RBF kernel obtained the best classification results with an accuracy of 87%. The overall classification performance was further improved using a weighted voting strategy with an accuracy of 89.8%, indicating that our proposed method can tap into the cognitive changes of MCI patients. The MCI detection scheme based on EEG, speech, and digital cognitive parameters proposed in this study provides a new direction and support for effective MCI detection, and suggests that VR and wearable devices will be a promising direction for easy-to-perform and effective MCI detection, offering new possibilities for the exploration of VR technology in the field of language cognition.

Nutrition risk and cognitive performance in community-living older adults without cognitive impairment: a cross-sectional analysis of the Canadian Longitudinal Study on Aging.

Malnutrition is correlated with poor cognition; however, an understanding of the association between nutrition risk, which precedes malnutrition, and cognition is lacking. This study aimed to determine if nutrition risk measured with the SCREEN-8 tool is associated with cognitive performance among cognitively healthy adults aged 55+,after adjusting for demographic and lifestyle covariates. Sex- and age-stratified analyses were also explored. Baseline data from the Canadian Longitudinal Study on Aging was used. Cognition was determined using a 6-measure composite score based on four executive functions and two memory tasks, taking into account age, sex, and education. Multivariable linear regression was performed while adjusting for body mass index (BMI), lifestyle, and health covariates in the entire sample (n=11 378) and then stratified by sex and age. Approximately half of participants were female (54.5%) aged 65+ (54.1%). Greater nutrition risk was associated with poorer cognitive performance in the entire sample (F[1, 11 368]=5.36, p=0.021) and among participants aged 55-64 (n=5227; F[1, 5217]=5.45, p=0.020). Sex differences in lifestyle and health factors associated with cognition were apparent, but nutrition risk was not associated with cognition in sex-stratified models. Based on this analysis, there may be an association between nutrition risk and cognitive performance in older adults. When screening for either cognitive impairment or nutrition risk, complementary assessments for these conditions is warranted, as early intervention may provide benefit.

Feasibility of screening for cognitive impairment among older persons and referral by community health workers in Wakiso district, Uganda.

In Uganda, cognitive impairment in older persons aged ≥ 60 years is often undiagnosed due to inadequate appreciation of the condition compounded with limitations of trained human resource able to conduct appropriate cognitive evaluations. Use of Community Health Workers (CHWs) especially in hard-to-reach communities can be an important link for older persons to the health facilities where they can receive adequate evaluations and interventions for cognitive challenges. The aim of the study was to assess the feasibility of screening for cognitive impairment among older persons and referral by CHWs in Wakiso district, Uganda. This was a sequential explanatory mixed methods study. The CHWs received a one-day training on causes, signs and symptoms, and management of cognitive impairment and screened older persons ≥ 60 years for cognitive impairment using the Alzheimer's Disease scale 8 (AD8). Psychiatric clinical officers (PCOs) administered the AD8 and the Mini Mental State Examination to the older persons after assessment by the CHWs who then referred them for appropriate clinical care. We conducted Kappa statistic for agreement between the CHWs and PCOs and compared raw scores of the CHWs to Experts scores using Bland Altman and pair plots and corresponding analyses. We also conducted focus group discussions for the older persons, caregivers and CHWs. We collected data from 385 older persons. We involved 12 CHWs and 75% were females, majority were married (58.3%) with at least a secondary education (66.7%). There was 96.4% (CI 94.5-98.2%) agreement between PCOs and CHWs in identifying cognitive impairment with the PCOs identifying 54/385 (14.0: 95%CI 10.7-17.9%) older persons compared to 58/385 (15.1: 95%CI 11.6-19.0%) identified by CHWs. Of the 58 identified to have cognitive impairment by the CHWs, 93.1% were referred for care. The average difference between the score of the expert and that of the CHW was - 0.042 with a 95% CI of -1.335 to 1.252. Corresponding Bland Altman and pair plots showed high agreement between the measurements although CHWs scored higher values with increasing scores. CHWs can be trained to identify and refer older persons with cognitive impairment in the communities.

Alzheimer's Together with Mild Cognitive Impairment Screening Using Polar Transformation of Middle Zone of Fundus Images Based Deep Learning.

Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI) are considered an increasing major health problem in elderlies. However, current clinical methods of Alzheimer's detection are expensive and difficult to access, making the detection inconvenient and unsuitable for developing countries such as Thailand. Thus, we developed a method of AD together with MCI screening by fine-tuning a pre-trained Densely Connected Convolutional Network (DenseNet-121) model using the middle zone of polar transformed fundus image. The polar transformation in the middle zone of the fundus is a key factor helping the model to extract features more effectively and that enhances the model accuracy. The dataset was divided into 2 groups: normal and abnormal (AD and MCI). This method can classify between normal and abnormal patients with 96% accuracy, 99% sensitivity, 90% specificity, 95% precision, and 97% F1 score. Parts of both MCI and AD input images that most impact the classification score visualized by Grad-CAM++ focus in superior and inferior retinal quadrants.Clinical relevance- The parts of both MCI and AD input images that have the most impact the classification score (visualized by Grad-CAM++) are superior and inferior retinal quadrants. Polar transformation of the middle zone of retinal fundus images is a key factor that enhances the classification accuracy.