Mini-Mental State Examination (MMSE) for the detection of Alzheimer's disease and other dementias in people with mild cognitive impairment (MCI)

Prevalence and Risk Factors of Cognitive Frailty in Patients Undergoing Maintenance Hemodialysis: A Systematic Review and Meta-Analysis

BACKGROUND

The purpose of this study is to investigate the prevalence and risk factor of cognitive frailty in patients undergoing maintenance hemodialysis.

METHODS

Systematically searched PubMed, EmBase, Web of Science, Cochrane Library, SinoMed, China Knowledge Resource Integrated Database, Wanfang Database, and Weipu Database from inception until January 1, 2024. Two researchers were independently screened and cross-checked. Stata 15.1 software was used to perform the meta-analysis.

RESULTS

A total of 15 articles were included, including 5398 patients. The results showed that the prevalence of cognitive frailty in patients undergoing maintenance hemodialysis was 24%. Among them, age (odds ratio [OR] = 1.33, 95% CI [1.16, 1.53]), waist circumference (OR = 1.05, 95% CI [1.03, 1.08]), malnutrition (OR = 2.91, 95% CI [1.94, 4.35]), comorbidities (OR = 1.93, 95% CI [1.47, 2.54]), stroke history (OR = 2.94, 95% CI [1.72, 5.03]), and depression (OR = 3.26, 95% CI [1.91, 5.57]) were the main risk factors for cognitive frailty in patients undergoing maintenance hemodialysis. Education level (OR = 0.48, 95% CI [0.31, 0.73]) was protective factors for cognitive frailty in patients undergoing maintenance hemodialysis.

CONCLUSIONS

Current evidence showed that the prevalence of cognitive frailty in patients undergoing maintenance hemodialysis was high, and there were many risk factors. Therefore, early identification and intervention of cognitive frailty in maintenance hemodialysis patients should be carried out, which may be helpful to reduce the prevalence rate and occurrence of adverse events and improve the prognosis of patients.

Effectiveness and safety of Governor vessel acupuncture therapy for post-stroke cognitive impairment: A meta-analysis of randomized controlled trials

OBJECTIVE

The purpose of this study was to evaluate the effectiveness of Governor vessel acupuncture (GV Ac) in treating post-stroke cognitive impairment (PSCI).

METHODS

There was a total of seven databases examined. Four English databases (Cochrane Library, PubMed, Embase, and Medline) and three Chinese databases (Chinese National Knowledge Infrastructure (CNKI), Chinese Science and Technology Periodical Databases (VIP), and Wan Fang Database) contain all randomized controlled trials (RCTs) comparing Governor vessel acupuncture to other treatments or none acupuncture for PSCI. The exact dates for the search period are from January 1, 2000, to January 1, 2023.Two researchers independently reviewed the literature, gathered RCT data, and performed statistical analysis. All data were analyzed using Review Manager software (Rev Man) 5.3.

RESULTS

This meta-analysis includes a total of 39 trials with 2044 patients. There were 1022 participants in each of the test and control groups. Following 12-120 days of acupuncture treatment, a meta-analysis revealed that the treatment groups (GV Ac combined with conventional treatment groups) significantly increased their scores on the Curative ratio (OR = 3.00, 95 %CI = 2.37-3.79, P = 0.98, I² = 0 %), Montreal Cognitive Assessment (MoCA)(MD = 1.82, 95 %CI = 1.60-2.03, P = 0.11, I² = 25 %), Mini-Mental State Examination (MMSE)(MD = 2.18, 95 %CI = 1.64-2.72, P<0.005, I² = 92 %), and Activity of Daily Living (ADL)(MD = 5.99, 95 %CI = 5.33-6.64, P = 0.19, I² = 26 %).

CONCLUSION

The results suggested that acupuncture on points of the Governor vessel enhanced cognitive function in stroke survivors.

Assessing and recovering Alzheimer's disease: a comparative analysis of standard neuropsychological approaches and virtual reality interventions with the use of digital storytelling

Background

Alzheimer's disease (AD), the most common form of dementia, is a progressive neurodegenerative disorder that predominantly affects the elderly population. Traditional assessment methods, including neuropsychological tests like the MMSE, have been the cornerstone of AD diagnosis for decades. These methods are grounded in a wealth of research and clinical experience, providing a robust framework for understanding the cognitive deficits of AD. The evolution of AD assessment and rehabilitation has recently been tackled with the introduction of Virtual Reality (VR) technologies.

Objectives

To evaluate the use of storytelling and reminiscence therapy in virtual reality programs as a complementary and enhancing modality alongside standard assessment and rehabilitation for Alzheimer's patients. To explore how regular interaction with VR narratives can slow cognitive decline or improve relevant features of cognitive functioning over the time. To propose a new assessment and rehabilitative tool based on the use of VR and digital storytelling.

Method

A comparative analysis of Standard Neuropsychological Approaches and Virtual Reality Interventions in patients with Alzheimer disorder was carried out. A literature overview on the empirical studies between 2019 and 2024 was conducted.

Results

We propose a new VR-based setup mediated by the use of storytelling for the assessment and recovery of AD.

Conclusion

The employment of storytelling within VR programs for the assessment and rehabilitation of Alzheimer's disease can positively impact both the cognitive and emotional realms of patients, with beneficial outcomes on caregivers' and families' burden. The successful implementation of this approach requires careful consideration of accessibility, data interpretation, and standard validation protocols.

Enhancing identification performance of cognitive impairment high-risk based on a semi-supervised learning method

BACKGROUND

Cognitive assessment plays a pivotal role in the early detection of cognitive impairment, particularly in the prevention and management of cognitive diseases such as Alzheimer's and Lewy body dementia. Large-scale screening relies heavily on cognitive assessment scales as primary tools, with some low sensitivity and others expensive. Despite significant progress in machine learning for cognitive function assessment, its application in this particular screening domain remains underexplored, often requiring labor-intensive expert annotations.

AIMS

This paper introduces a semi-supervised learning algorithm based on pseudo-label with putback (SS-PP), aiming to enhance model efficiency in predicting the high risk of cognitive impairment (HR-CI) by utilizing the distribution of unlabeled samples.

DATA

The study involved 189 labeled samples and 215,078 unlabeled samples from real world. A semi-supervised classification algorithm was designed and evaluated by comparison with supervised methods composed by 14 traditional machine-learning methods and other advanced semi-supervised algorithms.

RESULTS

The optimal SS-PP model, based on GBDT, achieved an AUC of 0.947. Comparative analysis with supervised learning models and semi-supervised methods demonstrated an average AUC improvement of 8% and state-of-art performance, repectively.

CONCLUSION

This study pioneers the exploration of utilizing limited labeled data for HR-CI predictions and evaluates the benefits of incorporating physical examination data, holding significant implications for the development of cost-effective strategies in relevant healthcare domains.

Small-Vessel Disease and Intracranial Large Artery Disease in Brain MRI Predict Dementia and Acute Coronary Syndrome, Respectively: A Prospective, Observational Study in the Population at High Vascular Risk

BACKGROUND

We aimed to clarify the predictive value of cerebral small-vessel disease and intracranial large artery disease (LAD) observed in magnetic resonance imaging of the brain and magnetic resonance angiography on future vascular events and cognitive impairment.

METHODS AND RESULTS

Data were derived from a Japanese cohort with evidence of cerebral vessel disease on magnetic resonance imaging. This study included 862 participants who underwent magnetic resonance angiography after excluding patients with a modified Rankin Scale score >1 and Mini-Mental State Examination score <24. We evaluated small-vessel disease such as white matter hyperintensities and lacunes in magnetic resonance imaging and LAD with magnetic resonance angiography. Outcomes were incident stroke, dementia, acute coronary syndrome, and all-cause death. Over a median follow-up period of 4.5 years, 54 incident stroke, 39 cases of dementia, and 27 cases of acute coronary syndrome were documented. Both small-vessel disease (white matter hyperintensities and lacunes) and LAD were associated with stroke; however, only white matter hyperintensities were related to dementia. In contrast, only LAD was associated with acute coronary syndrome. Among the 357 patients with no prior history of stroke, coronary or peripheral artery disease, or atrial fibrillation, white matter hyperintensities emerged as the sole predictor of future stroke and dementia, while LAD was the sole predictor of acute coronary syndrome.

CONCLUSIONS

Among cerebral vessels, small-vessel disease could underlie the cognitive impairment while LAD was associated with coronary artery disease as atherosclerotic vessel disease.

Performance of antisaccades in patients with cerebral small vessel disease accompanied by white matter hyperintensities

OBJECTIVES

The antisaccades (AS) task is considered a reliable indicator of inhibitory control of eye movements in humans. Achieving good AS performance requires efficient cognitive processes that are sensitive to changes in brain structure. White matter hyperintensities (WMH) can cause subcortical-cortical dysconnectivity, affecting diverse cognitive domains. Thus, the AS task was investigated in patients with WMH in cerebral small vessel disease (CSVD).

METHODS

In this retrospective study, 75 participants with WMH, determined by neuroimaging standards for CSVD research, were admitted to the Department of Neurology of Beijing Luhe Hospital, Capital Medical University from January 2021 to December 2022. All subjects underwent the AS task, Montreal Cognitive Assessment (MoCA), Mini-Mental State Examination (MMSE), and 3.0T brain MRI. Additionally, 61 healthy subjects were recruited to characterize WMH profiles.

RESULTS

Compared to the control group, patients with WMH had a significantly increased AS error rate (49.81%, p = 0.001) and lower gain (76.00%, p = 0.042). The AS error rate was significantly higher in patients with WMH in the frontal lobe than in those without WMH (p = 0.004). After adjusting for confounders (age), a positive correlation was found between the AS error rate and MoCA scores for patients with WMH (coefficient = 0.262, p = 0.024).

CONCLUSIONS

Patients with WMH due to CSVD exhibited abnormal AS performances, particularly in the frontal lobe. The eye movement paradigms, the new diagnostic forms in neurology, can be utilized to investigate the distributed cortical and subcortical systems involved in cognitive control processes, offering simple, well-tolerated and highly sensitive advantages over traditional measures.

Drawing a line?-Visuo-constructive function as discriminator between healthy individuals, subjective cognitive decline, mild cognitive impairment and Alzheimer's disease and predictor of disease progress compared to a multimodal approach

PURPOSE

One cognitive domain impaired in Alzheimer's disease (AD) is visuo-construction. The Vienna Visuo-constructional Test 3.0 Screening (VVT 3.0 Screening) measures this cognitive domain. This study examines how it works in the differentiation of AD from healthy controls (HC) and the prodromal stages subjective cognitive decline (SCD) and mild cognitive impairment (MCI) and also how it performs in prediction of progress compared to the Mini Mental State Examination (MMSE) and the Sunderland Clock Drawing Test (CDT).

METHODS

Data from 622 patients (33 HC, 68 SCD, 301 MCI, 220 AD) who completed all three tests were obtained. Furthermore, 117 patients were examined in a follow-up. Data were analyzed in a retrospective analysis comparing the validity of tests in diagnosis and prediction using receiver operator characteristic (ROC) curves and multinominal logistic regression.

RESULTS

The VVT 3.0 Screening shows some ability to discriminate between AD and all other participants (sensitivity: 62.1%, specificity: 83.1%), while of the three examined tests none was able to predict membership to all experimental groups or to predict disease-progress adequately. As the VVT 3.0 Screening is short, easy to apply and largely language independent, it can be considered an alternative to the MMSE in certain situations.

CONCLUSIONS

The VVT 3.0 Screening is useful to discriminate between AD and all other participants and can be an alternative to the MMSE in certain situations.

Increased extra-neurite conductivity of brain in patients with Alzheimer's disease: A pilot study

The objectives of this study were to investigate how the extra-neurite conductivity (EC) and intra-neurite conductivity (IC) were reflected in Alzheimer's disease (AD) patients compared with old cognitively normal (CN) people and patients with amnestic mild cognitive impairment (MCI) and to evaluate the association between those conductivity values and cognitive decline. To do this, high-frequency conductivity (HFC) at the Larmor frequency was obtained using MRI-based electrical property tomography (MREPT) and was decomposed into EC and IC using information of multi-shell multi-gradient direction diffusion tensor images. This prospective single-center study included 20 patients with mild or moderate AD, 25 patients with amnestic MCI, and 21 old CN participants. After decomposing EC and IC from HFC for all participants, we performed voxel-based and regions-of-interest analyses to compare conductivity between the three participant groups and to evaluate the association with either age or the Mini-Mental State Examination (MMSE) scores. We found increased EC in AD compared to CN and MCI. EC was significantly negatively associated with MMSE scores in the insula, and middle temporal gyrus. EC might be used as an imaging biomarker for helping to monitor cognitive function.

Multimodal Predictive Modeling: Scalable Imaging Informed Approaches to Predict Future Brain Health

Background

Predicting future brain health is a complex endeavor that often requires integrating diverse data sources. The neural patterns and interactions identified through neuroimaging serve as the fundamental basis and early indicators that precede the manifestation of observable behaviors or psychological states.

New Method

In this work, we introduce a multimodal predictive modeling approach that leverages an imaging-informed methodology to gain insights into future behavioral outcomes. We employed three methodologies for evaluation: an assessment-only approach using support vector regression (SVR), a neuroimaging-only approach using random forest (RF), and an image-assisted method integrating the static functional network connectivity (sFNC) matrix from resting-state functional magnetic resonance imaging (rs-fMRI) alongside assessments. The image-assisted approach utilized a partially conditional variational autoencoder (PCVAE) to predict brain health constructs in future visits from the behavioral data alone.

Results

Our performance evaluation indicates that the image-assisted method excels in handling conditional information to predict brain health constructs in subsequent visits and their longitudinal changes. These results suggest that during the training stage, the PCVAE model effectively captures relevant information from neuroimaging data, thereby potentially improving accuracy in making future predictions using only assessment data.

Comparison with Existing Methods

The proposed image-assisted method outperforms traditional assessment-only and neuroimaging-only approaches by effectively integrating neuroimaging data with assessment factors.

Conclusion

This study underscores the potential of neuroimaging-informed predictive modeling to advance our comprehension of the complex relationships between cognitive performance and neural connectivity.

The Effects of a Nonpharmacological Intervention Practice for Older Adults with Mild Cognitive Impairment and Their Family Caregivers in China

Mild cognitive impairment (MCI) marks a critical phase in the progression to dementia. In our study, social workers utilized the Multicomponent Nonpharmacological Intervention Approach (MCNIA) to aid MCI participants (N = 52) and their caregivers, dividing into intervention and control groups. The intervention group underwent an additional regimen of non-pharmacological therapies besides pharmacological treatment. Our findings highlighted that: 1) MCNIA significantly enhanced cognitive and daily living abilities in the intervention group; 2) Caregivers experienced reduced burdens and improved social support; 3) Correlation analyses involving biomarkers indicated that MCNIA was particularly effective in alleviating depression in those with slightly more severe cognitive impairment.

Deep Learning-Based Eye-Tracking Analysis for Diagnosis of Alzheimer's Disease Using 3D Comprehensive Visual Stimuli

Alzheimer's Disease (AD) is a neurodegenerative disorder that causes a continuous decline in cognitive functions and eventually results in death. An early AD diagnosis is important for taking active measures to slow its deterioration. Traditional diagnoses are usually based on clinical experience, which is limited by several realistic factors. In this paper, we focus on exploiting deep learning techniques to diagnose AD based on eye-tracking behaviors. Visual attention, as a typical eye-tracking behavior, is of great clinical value in detecting cognitive abnormalities in AD patients. To better analyze the differences in visual attention between AD patients and normals, we first conducted a 3D comprehensive visual task on a noninvasive eye-tracking system to collect visual attention heatmaps. Then a multilayered comparison convolutional neural network (MC-CNN) is proposed to distinguish the visual attention differences between AD patients and normals. In MC-CNN, the multilayered feature representations of heatmaps were obtained by hierarchical residual blocks to better encode eye movement behaviors, which were further integrated into a distance vector to benefit the comprehensive visual task. From evaluation, MC-CNN can distinguish AD patients from normals with 0.84 accuracy, 0.86 recall, 0.82 precision, 0.83 F1-score and 0.90 area under the curve (AUC). The above results demonstrate the effectiveness of the proposed MC-CNN in AD diagnosis based on the comprehensive 3D visual task.

Which Comprehensive Geriatric Assessment (CGA) instruments are currently used in Germany: a survey

BACKGROUND

The Comprehensive Geriatric Assessment (CGA) records geriatric syndromes in a standardized manner, allowing individualized treatment tailored to the patient's needs and resources. Its use has shown a beneficial effect on the functional outcome and survival of geriatric patients. A recently published German S1 guideline for level 2 CGA provides recommendations for the use of a broad variety of different assessment instruments for each geriatric syndrome. However, the actual use of assessment instruments in routine geriatric clinical practice and its consistency with the guideline and the current state of literature has not been investigated to date.

METHODS

An online survey was developed by an expert group of geriatricians and sent to all licenced geriatricians (n = 569) within Germany. The survey included the following geriatric syndromes: motor function and self-help capability, cognition, depression, pain, dysphagia and nutrition, social status and comorbidity, pressure ulcers, language and speech, delirium, and frailty. Respondents were asked to report which geriatric assessment instruments are used to assess the respective syndromes.

RESULTS

A total of 122 clinicians participated in the survey (response rate: 21%); after data cleaning, 76 data sets remained for analysis. All participants regularly used assessment instruments in the following categories: motor function, self-help capability, cognition, depression, and pain. The most frequently used instruments in these categories were the Timed Up and Go (TUG), the Barthel Index (BI), the Mini Mental State Examination (MMSE), the Geriatric Depression Scale (GDS), and the Visual Analogue Scale (VAS). Limited or heterogenous assessments are used in the following categories: delirium, frailty and social status.

CONCLUSIONS

Our results show that the assessment of motor function, self-help capability, cognition, depression, pain, and dysphagia and nutrition is consistent with the recommendations of the S1 guideline for level 2 CGA. Instruments recommended for more frequent use include the Short Physical Performance Battery (SPPB), the Montreal Cognitive Assessment (MoCA), and the WHO-5 (depression). There is a particular need for standardized assessment of delirium, frailty and social status. The harmonization of assessment instruments throughout geriatric departments shall enable more effective treatment and prevention of age-related diseases and syndromes.

Physical Activity, Sedentary Behavior, and Their Predictors Among Nursing Home Residents-Cross-Sectional Results of the BaSAlt Study

Little is known about physical activity (PA) and sedentary behavior (SB) among nursing home residents although PA is known as a health promoter. This study examined PA, SB, and their predictors among nursing home residents (n = 63). Dependent variables were accelerometry-based PA and SB. Predictor variables included in a path analysis were age, sex, body mass index, Barthel Index, cognitive status (Mini-Mental State Examination), physical performance (hand grip strength and habitual walking speed), and well-being (World Health Organization-5 well-being index). PA was very low (M steps per day = 2,433) and SB was high (M percentage of sedentary time = 89.4%). PA was significantly predicted by age (β = -0.27, p = .008), body mass index (β = -0.29, p = .002), Barthel Index (β = 0.24, p = .040), and hand grip strength (β = 0.30, p = .048). SB was significantly predicted by body mass index (β = 0.27, p = .008) and Barthel Index (β = -0.30, p = .012). Results might be helpful for everyday practice to identify individuals at high risk for low PA and high SB.

Effects of the @ctivehip telerehabilitation program on the quality of life, psychological factors and fitness level of patients with hip fracture

INTRODUCTION

Telerehabilitation has emerged in the last decade as a promising alternative to conduct the rehabilitation process at home. However, there are no studies testing the effects of telerehabilitation interventions for patients with hip fracture on quality of life nor psychological factors, whereas the evidence on fitness level is scarce. Thus, the aim of this study is to test the effects of the @ctivehip telerehabilitation program on the quality of life, psychological factors and fitness level of patients who had suffered a hip fracture.

METHODS

The present study is a non-randomized clinical trial that includes patients older than 65 years old with a hip fracture and their family caregivers (ClinicalTrials.gov; Identifier: NCT02968589). Per-protocol (64 participants) and intention-to-treat (71 participants) analyses were performed, the first being the main analysis. The intervention group received a home-based multidisciplinary telerehabilitation intervention, called @ctivehip, that lasted 12 weeks. The control group received the traditional care and rehabilitation provided by the Andalusian Public Health Care System. The outcomes measured were the patients' quality of life through the EuroQol Quality of Life Questionnaire (EQ-5D), physiological factors (anxiety and depression) using the Hospital Anxiety and Depression Scale (HADS) and the fitness level, assessed with the International Fitness Scale.

RESULTS

The quality of life of the telerehabilitation group increased, while the control group scored worsened at the 3-month follow-up (medium effect size: 0.66 SDs; p  =  0.006). The telerehabilitation group demonstrated a greater decrease than the control group in the total HADS score (medium effect size: -0.50 SDs; p  =  0.015). Lastly, the telerehabilitation group recovered a fitness level close to the pre-hip fracture in comparison with the control group (small effect size: 0.49 SDs; p  =  0.022).

DISCUSSION

The @ctivehip telerehabilitation program seems to be a promising treatment to improve the quality of life and psychological factors (i.e. anxiety and depression) of older adults after a hip fracture, as well as to recover their previous fitness level.

Meta-Analysis-Based Comparison of Annual Fall Risk between Older Adults with Alzheimer's Disease and Mild Cognitive Impairment

Background

Falls are a primary cause of injuries and hospitalization in older adults. It has been reported that cognitive impairments and dementia can increase fall risk in the older population; however, it remains unknown if fall risk differs among subgroups of dementia. This meta-analysis summarized previous studies reporting the annual fall risk of people with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and compared the fall risk between these two groups of people with dementia.

Methods

Thirty-five studies enrolling 7844 older adults with AD or MCI were included. The annual fall prevalence and average number of falls of the included studies were meta-analyzed and compared by random-effects models with inverse variance weights.

Results

The annual fall prevalence in people with AD (43.55%) was significantly higher than MCI (35.26%, p < 0.001). A χ2 test indicated that the pooled fall prevalence is significantly higher in people with AD than MCI χ2 = 158.403, p < 0.001). Additionally, the yearly average number of falls in AD was higher than in MCI (1.30 vs 0.77 falls/person).

Conclusions

The results showed that older people with AD experience a higher annual fall prevalence with a larger number of falls than older adults with MCI. The results suggested that the fall risk measurements should be reported separately between people with AD and MCI. The findings could provide preliminary guidance for the identification of individuals with dementia who experience a high fall risk.

The Interplay between Gut Microbiota and Cognitive Functioning in the Healthy Aging Population: A Systematic Review

BACKGROUND

The gut microbiota in healthy older individuals typically show a decrease in beneficial bacteria like Bifidobacterium and Lactobacillus, alongside an increase in pro-inflammatory microbes such as Enterobacteriaceae and Clostridia. These changes contrast with younger and middle-aged individuals and appear to correlate with cognitive status. Although there is extensive research on gut microbiota and cognitive functions in cognitively impaired elderly individuals, its impact on cognitively healthy elderly populations has not been extensively studied.

METHOD

A comprehensive literature search was conducted across PubMed, EBSCO, Web of Science, and Scopus databases to identify studies exploring the relationship between gut microbiota composition and cognitive functioning in healthy older adults. During the literature screening process, each record was initially assessed by its title, abstract, and keywords to exclude articles that did not align with the scope of this review. Three authors independently screened and retrieved the records. The inclusion criteria included: (1) publication in peer-reviewed journals; (2) studies involving neurologically, cognitively, and medically healthy populations; (3) participants identified as older adults, defined for this review as individuals aged 45 years and older due to the limited number of records; (4) analysis of gut microbiota; and (5) assessment of cognitive function. Subsequently, full texts were analyzed to determine eligibility. The exclusion criteria encompassed: (1) incorrect publication type; (2) inappropriate sample population; (3) unsuitable study design; (4) absence of one or more inclusion criteria; and (5) studies based on animal research. A risk of bias assessment was performed for each included study using the Joanna Briggs Institute (JBI) checklist, ensuring all selected studies met established quality standards.

RESULTS

A total of 6 eligible research articles from a possible 1752 published until March 2024 were identified and included. We categorized the included studies into two groups based on their focus: the taxonomic composition of gut microbiota and the alpha diversity, which is the variety of organisms within a sample. Additionally, two methods were identified for assessing cognition: neuropsychological tests and physiological measurements, notably electroencephalography (EEG). The studies show varying results regarding the abundance of specific bacterial taxa and their cognitive associations. Notably, the relationship between certain bacteria and cognition may vary when analyzed at different taxonomic levels, such as phylum versus family.

CONCLUSIONS

Changes in gut microbiota composition in the elderly, even without a cognitive impairment diagnosis, could potentially serve as early biological markers for Alzheimer's disease or other dementias before mild cognitive impairment appears.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol

INTRODUCTION

Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD).

METHODS AND ANALYSIS

DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies.

ETHICS AND DISSEMINATION

Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Sex differences in cognitive function trajectories and their determinants in older adults: Evidence from the Chinese longitudinal healthy longevity survey

OBJECTIVES

To examine sex differences in the cognitive trajectories of a nationally representative sample of older people living in China and to explore potential determinants of these trajectories.

METHODS

The study included 2230 women and 2171 men who were cognitively healthy and aged over 60 at the first observation from the Chinese Longitudinal Healthy Longevity Survey based on the 2008-2018 cohort. Cognitive function was measured using the Chinese version of the Mini-Mental State Examination (MMSE). Group-based trajectory modeling was used to identify potential heterogeneity of longitudinal changes over the 10 years in each gender. Logistic regression was used to investigate associations between baseline characteristics (age, education, fertility history, sleep length, physical activity, and health status and behaviors) and trajectory classes.

RESULTS

Three trajectories (labeled stable, slow decline, and rapid decline) were identified according to the changes in MMSE scores for both women and men. For the women, both the slow and rapid decline groups accounted for a larger proportion (14.7% and 11.0%, respectively) than the male decline groups (8.1% and 6.6%, respectively), and the women had a lower baseline MMSE score with a faster decline. In the multivariable logistic regression analyses, older age, less education, older age at first birth, poorer functional abilities, hearing impairment, and lower baseline MMSE scores were significantly associated with cognitive decline in both the female and male groups compared to the stable group. For the women, sleeping over 9 h was also associated with a rapid cognitive decline trajectory, while current exercise and being overweight/obese were protective factors against cognitive decline.

CONCLUSIONS

The women had an overall more serious cognitive decline than men. The potential determinants of cognitive decline identified in this study could be considered for developing specific intervention strategies aimed at promoting a healthy brain and preventing cognitive decline in different sexes, especially in low-income and developing countries.

Effect of different modalities of transcranial magnetic stimulation on Parkinson's patients cognitive impairment and long-term effectiveness: a systematic review and network meta-analysis

Objective

This study used network Meta-analysis to compare the effects of different transcranial magnetic stimulation (TMS) modalities on the effectiveness and long-term validity of improving cognitive function in Parkinson's patients.

Methods

Computer searches of the Cochrane Library, PubMed, Web of Science, Embass, CNKI and Wanfang Data were conducted to collect randomized controlled clinical studies on TMS to improve cognitive function in Parkinson's patients published from the time of library construction to December 2023.

Results

A total of 22 studies and 1,473 patients were included, comprising 5 interventions: high frequency repetitive transcranial magnetic stimulation (HF-rTMS), low frequency repetitive transcranial magnetic stimulation (LF-rTMS), intermittent theta burst stimulation (iTBS), sham stimulation and conventional rehabilitation therapy (CRT). Network Meta-analysis showed that the ranking results of different TMS intervention modalities in terms of MoCA scores were: HF-rTMS > LF-rTMS > iTBS > sham > CRT, the ranking results of different TMS intervention modalities in terms of MMSE scores were: HF-rTMS > LF-rTMS > sham > CRT. The effect of TMS on improving Parkinsonian cognitive function lasted for 1 month compared to the no-stimulation group.

Conclusion

TMS has some long-term sustained effects on improving cognitive function in Parkinson's patients. HF-rTMS is more effective in improving cognitive function in Parkinson's patients.Systematic review registration: https://www.crd.york.ac.uk/PROSPERO, identifier: CRD42023463958.

The SNP rs6859 in NECTIN2 gene is associated with underlying heterogeneous trajectories of cognitive changes in older adults

BACKGROUND

Functional decline associated with dementia, including in Alzheimer's disease (AD), is not uniform across individuals, and respective heterogeneity is not yet fully explained. Such heterogeneity may in part be related to genetic variability among individuals. In this study, we investigated whether the SNP rs6859 in nectin cell adhesion molecule 2 (NECTIN2) gene (a major risk factor for AD) influences trajectories of cognitive decline in older participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI).

METHODS

We retrospectively analyzed records on 1310 participants from the ADNI database for the multivariate analysis. We used longitudinal measures of Mini-Mental State Examination (MMSE) scores in participants, who were cognitively normal, or having AD, or other cognitive deficits to investigate the trajectories of cognitive changes. Multiple linear regression, linear mixed models and latent class analyses were conducted to investigate the association of the SNP rs6859 with MMSE.

RESULTS

The regression coefficient per one allele dose of the SNP rs6859 was independently associated with MMSE in both cross-sectional (-2.23, p < 0.01) and linear mixed models (-2.26, p < 0.01) analyses. The latent class model with three distinct subgroups (class 1: stable and gradual decline, class 2: intermediate and late decline, and class 3: lowest and irregular) performed best in the posterior classification, 42.67% (n = 559), 21.45% (n = 281), 35.88% (n = 470) were classified as class 1, class 2, and class 3. In the heterogeneous linear mixed model, the regression coefficient per one allele dose of rs6859 - A risk allele was significantly associated with MMSE class 1 and class 2 memberships and related decline; Class 1 (-2.28, 95% CI: -4.05, -0.50, p < 0.05), Class 2 (-5.56, 95% CI: -9.61, -1.51, p < 0.01) and Class 3 (-0.37, 95% CI: -1.62, 0.87, p = 0.55).

CONCLUSIONS

This study found statistical evidence supporting the classification of three latent subclass groups representing complex MMSE trajectories in the ADNI cohort. The SNP rs6859 can be suggested as a candidate genetic predictor of variation in modeling MMSE trajectory, as well as for identifying latent classes with higher baseline MMSE. Functional studies may help further elucidate this relationship.

Brain health measurement: a scoping review

OBJECTIVES

Preservation of brain health is an urgent priority for the world's ageing population. The evidence base for brain health optimisation strategies is rapidly expanding, but clear recommendations have been limited by heterogeneity in measurement of brain health outcomes. We performed a scoping review to systematically evaluate brain health measurement in the scientific literature to date, informing development of a core outcome set.

DESIGN

Scoping review.

DATA SOURCES

Medline, APA PsycArticles and Embase were searched through until 25 January 2023.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Studies were included if they described brain health evaluation methods in sufficient detail in human adults and were in English language.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently screened titles, abstracts and full texts for inclusion and extracted data using Covidence software.

RESULTS

From 6987 articles identified by the search, 727 studies met inclusion criteria. Study publication increased by 22 times in the last decade. Cohort study was the most common study design (n=609, 84%). 479 unique methods of measuring brain health were identified, comprising imaging, cognitive, mental health, biological and clinical categories. Seven of the top 10 most frequently used brain health measurement methods were imaging based, including structural imaging of grey matter and hippocampal volumes and white matter hyperintensities. Cognitive tests such as the trail making test accounted for 286 (59.7%) of all brain health measurement methods.

CONCLUSIONS

The scientific literature surrounding brain health has increased exponentially, yet measurement methods are highly heterogeneous across studies which may explain the lack of clinical translation. Future studies should aim to develop a selected group of measures that should be included in all brain health studies to aid interstudy comparison (core outcome set), and broaden from the current focus on neuroimaging outcomes to include a range of outcomes.

Estimating dementia risk in an African American population using the DCTclock

The prevalence of Alzheimer's disease (AD) and related dementias (ADRD) is increasing. African Americans are twice as likely to develop dementia than other ethnic populations. Traditional cognitive screening solutions lack the sensitivity to independently identify individuals at risk for cognitive decline. The DCTclock is a 3-min AI-enabled adaptation of the well-established clock drawing test. The DCTclock can estimate dementia risk for both general cognitive impairment and the presence of AD pathology. Here we performed a retrospective analysis to assess the performance of the DCTclock to estimate future conversion to ADRD in African American participants from the Rush Alzheimer's Disease Research Center Minority Aging Research Study (MARS) and African American Clinical Core (AACORE). We assessed baseline DCTclock scores in 646 participants (baseline median age = 78.0 ± 6.4, median years of education = 14.0 ± 3.2, 78% female) and found significantly lower baseline DCTclock scores in those who received a dementia diagnosis within 3 years. We also found that 16.4% of participants with a baseline DCTclock score less than 60 were significantly more likely to develop dementia in 5 years vs. those with the highest DCTclock scores (75-100). This research demonstrates the DCTclock's ability to estimate the 5-year risk of developing dementia in an African American population. Early detection of elevated dementia risk using the DCTclock could provide patients, caregivers, and clinicians opportunities to plan and intervene early to improve cognitive health trajectories. Early detection of dementia risk can also enhance participant selection in clinical trials while reducing screening costs.

"VR is the future": perspectives of healthcare professionals on virtual reality as a diagnostic tool for dementia status in primary care

BACKGROUND

Healthcare professionals (HPs) hold critical perspectives on the barriers and facilitating factors for the implementation of virtual reality (VR) dementia diagnosis tools in the clinical setting. This study aims to explore HP perspectives regarding the clinical implementation of dementia diagnosis tools using VR platforms.

METHODS

An exploratory qualitative interview study was carried out between July and September 2022. In-depth semi-structured interviews were conducted with HPs (n = 7) with clinical expertise in dementia diagnoses drawn from medicine, nursing and allied health practices. A hermeneutic phenomenological approach was used to frame the interview data across the dementia diagnosis pathway and application of new technology.

RESULTS

HPs were on average 36.29 years old (SD = 11.56) with 11.85 years of experience (SD = 12.80, range:4-42). Analyses identified three main themes related to the contemporary methods of dementia diagnosis, dementia diagnosis and the medical landscape and HP perspectives on the usefulness and barriers of VR implementation. VR was considered an innovative prospect, with improved ecological validity compared to commonplace, current cognitive assessments. Concerns of time commitments, monetary costs and the validity of the new technology were identified as key barriers to implementation. Overall, implementation of a new diagnostic tool was considered a complex process.

CONCLUSIONS

Our insight into general practice and nursing clinics can be supported to embed and integrate virtual reality platforms in primary care settings. Primary healthcare organizations require more funding and time related resources to produce a context in which VR tools could be implemented in a beneficial manner.

An Exploration of the Memory Performance in Older Adult Hearing Aid Users on the Integrated Digit-in-Noise Test

This study aimed to preliminarily investigate the associations between performance on the integrated Digit-in-Noise Test (iDIN) and performance on measures of general cognition and working memory (WM). The study recruited 81 older adult hearing aid users between 60 and 95 years of age with bilateral moderate to severe hearing loss. The Chinese version of the Montreal Cognitive Assessment Basic (MoCA-BC) was used to screen older adults for mild cognitive impairment. Speech reception thresholds (SRTs) were measured using 2- to 5-digit sequences of the Mandarin iDIN. The differences in SRT between five-digit and two-digit sequences (SRT5-2), and between five-digit and three-digit sequences (SRT5-3), were used as indicators of memory performance. The results were compared to those from the Digit Span Test and Corsi Blocks Tapping Test, which evaluate WM and attention capacity. SRT5-2 and SRT5-3 demonstrated significant correlations with the three cognitive function tests (rs ranging from -.705 to -.528). Furthermore, SRT5-2 and SRT5-3 were significantly higher in participants who failed the MoCA-BC screening compared to those who passed. The findings show associations between performance on the iDIN and performance on memory tests. However, further validation and exploration are needed to fully establish its effectiveness and efficacy.

Results of objective brushing data recorded from a powered toothbrush used by elderly individuals with mild cognitive impairment related to values for oral health

OBJECTIVES

The study aimed to investigate how the objective use of a powered toothbrush in frequency and duration affects plaque index, bleeding on probing, and periodontal pocket depth ≥ 4 mm in elderly individuals with MCI. A second aim was to compare the objective results with the participants' self-estimated brush use.

MATERIALS AND METHODS

Objective brush usage data was extracted from the participants' powered toothbrushes and related to the oral health variables plaque index, bleeding on probing, and periodontal pocket depth ≥ 4 mm. Furthermore, the objective usage data was compared with the participants' self-reported brush usage reported in a questionnaire at baseline and 6- and 12-month examination.

RESULTS

Out of a screened sample of 213 individuals, 170 fulfilled the 12-month visit. The principal findings are that despite the objective values registered for frequency and duration being lower than the recommended and less than the instructed, using powered toothbrushes after instruction and information led to improved values for PI, BOP, and PPD ≥ 4 mm in the group of elderly with MIC.

CONCLUSIONS

Despite lower brush frequency and duration than the generally recommended, using a powered toothbrush improved oral health. The objective brush data recorded from the powered toothbrush correlates poorly with the self-estimated brush use.

CLINICAL RELEVANCE

Using objective brush data can become one of the factors in the collaboration to preserve and improve oral health in older people with mild cognitive impairment.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05941611, retrospectively registered 11/07/2023.

Assessing cognitive decline in the aging brain: lessons from rodent and human studies

As life expectancy continues to increase worldwide, age-related dysfunction will largely impact our societies in the future. Aging is well established to promote the deterioration of cognitive function and is the primary risk factor for the development of prevalent neurological disorders. Even in the absence of dementia, age-related cognitive decline impacts specific types of memories and brain structures in humans and animal models. Despite this, preclinical and clinical studies that investigate age-related changes in brain physiology often use largely different methods, which hinders the translational potential of findings. This review seeks to integrate what is known about age-related changes in the brain with analogue cognitive tests used in humans and rodent studies, ranging from "pen and paper" tests to virtual-reality-based paradigms. Finally, we draw parallels between the behavior paradigms used in research compared to the enrollment into clinical trials that aim to study age-related cognitive decline.

Brain-derived neurotrophic factor gene polymorphism affects cognitive function and neurofilament light chain level in patients with subcortical ischaemic vascular dementia

Objective

To investigate the effects of brain-derived neurotrophic factor (BDNF) gene polymorphism on cognitive function, neuroimaging and blood biological markers in patients with subcortical ischaemic vascular dementia (SIVD).

Methods

A total of 81 patients with SIVD were included. According to their BDNF gene polymorphism, the participants were divided into the Val/Val (n = 26), Val/Met (n = 35), and Met/Met (n = 20) groups. A comprehensive neuropsychological evaluation and multimodal brain MRI scan were performed. MRI markers for small vessel disease were visually rated or quantitatively analysed. Moreover, 52 patients were further evaluated with blood marker assays, including amyloid beta (Aβ), phosphorylated tau at threonine-181 (P-tau181), glial fibrillary acidic protein (GFAP), total tau (T-tau) and neurofilament light chain (NfL).

Results

There were no significant differences in demographics, disease duration or MRI markers of small vessel disease between the three groups. Compared with the Val/Val and Val/Met groups, the Met/Met group showed worse performance in the verbal fluency test and higher levels of plasma NfL.

Conclusion

The rs6265 polymorphism of the BDNF gene is associated with semantic language fluency in patients with SIVD. The Met genotype may be a risk factor for cognitive impairment and neuronal injury.

Virtual Reality for Pulmonary Rehabilitation: Comprehensive Review

BACKGROUND

Pulmonary rehabilitation is a vital component of comprehensive care for patients with respiratory conditions, such as lung cancer, chronic obstructive pulmonary disease, and asthma, and those recovering from respiratory diseases like COVID-19. It aims to enhance patients' functional ability and quality of life, and reduce symptoms, such as stress, anxiety, and chronic pain. Virtual reality is a novel technology that offers new opportunities for customized implementation and self-control of pulmonary rehabilitation through patient engagement.

OBJECTIVE

This review focused on all types of virtual reality technologies (nonimmersive, semi-immersive, and fully immersive) that witnessed significant development and were released in the field of pulmonary rehabilitation, including breathing exercises, biofeedback systems, virtual environments for exercise, and educational models.

METHODS

The review screened 7 electronic libraries from 2010 to 2023. The libraries were ACM Digital Library, Google Scholar, IEEE Xplore, MEDLINE, PubMed, Sage, and ScienceDirect. Thematic analysis was used as an additional methodology to classify our findings based on themes. The themes were virtual reality training, interaction, types of virtual environments, effectiveness, feasibility, design strategies, limitations, and future directions.

RESULTS

A total of 2319 articles were identified, and after a detailed screening process, 32 studies were reviewed. Based on the findings of all the studies that were reviewed (29 with a positive label and 3 with a neutral label), virtual reality can be an effective solution for pulmonary rehabilitation in patients with lung cancer, chronic obstructive pulmonary disease, and asthma, and in individuals and children who are dealing with mental health-related disorders, such as anxiety. The outcomes indicated that virtual reality is a reliable and feasible solution for pulmonary rehabilitation. Interventions can provide immersive experiences to patients and offer tailored and engaging rehabilitation that promotes improved functional outcomes of pulmonary rehabilitation, breathing body awareness, and relaxation breathing techniques.

CONCLUSIONS

The identified studies on virtual reality in pulmonary rehabilitation showed that virtual reality holds great promise for improving the outcomes and experiences of patients. The immersive and interactive nature of virtual reality interventions offers a new dimension to traditional rehabilitation approaches, providing personalized exercises and addressing psychological well-being. However, additional research is needed to establish standardized protocols, identify the most effective strategies, and evaluate long-term benefits. As virtual reality technology continues to advance, it has the potential to revolutionize pulmonary rehabilitation and significantly improve the lives of patients with chronic lung diseases.

The neutrophil-to-lymphocyte ratio is associated with mild cognitive impairment in community-dwelling older women aged over 70 years: a population-based cross-sectional study

Background

The neutrophil-to-lymphocyte ratio (NLR) is a marker of inflammation that can be obtained quickly, conveniently, and cheaply from blood samples. However, there is no research to explore the effects of sex and age on the relationship between the NLR and mild cognitive impairment (MCI) in community-dwelling older adults.

Methods

A total of 3,126 individuals aged over 60 years in Shanghai were recruited for face-to-face interviews, and blood samples were collected. MCI was assessed by the Mini-Mental State Examination (MMSE) and the Instrumental Activities of Daily Living (IADL) scale, and neutrophil count and lymphocyte counts were measured in fasting blood samples. The NLR was calculated by dividing the absolute neutrophil count by the absolute lymphocyte count.

Results

In females, the NLR in the MCI group was significantly higher than that in the cognitively normal group (2.13 ± 0.94 vs. 1.85 ± 0.83, p < 0.001) but not in men. Logistic regression showed that a higher NLR was an independent risk factor for MCI in women [odds ratio (OR) = 1.33; 95% confidence interval (CI) = 1.14-1.55]. In addition, the elevated NLR quartile was associated with an increased risk of MCI, especially in women older than 70 years (p value for trend = 0.012).

Conclusion

Compared with males, female MCI patients had a significantly higher NLR than cognitively normal controls. In addition, elevated NLR was found to be significantly associated with MCI risk in women older than 70 years. Therefore, elderly Chinese women with a higher NLR value may be the target population for effective prevention of MCI.

Influence of CurQfen®-curcumin on cognitive impairment: a randomized, double-blinded, placebo-controlled, 3-arm, 3-sequence comparative study

Background

Although curcumin is a blood-brain-barrier permeable molecule with the ability to bind and segregate β-amyloid plaques and neurofibrillary tangles of hyperphosphorylated tau proteins, its poor oral bioavailability, rapid biotransformation to inactive metabolites, fast elimination from the systemic circulation, and hence the poor neuronal uptake has been limiting its clinical efficacy under neurodegenerative conditions.

Objective

We hypothesized that the highly bioavailable CurQfen-curcumin (CGM), which has been shown to possess significant blood-brain-barrier permeability and brain bioavailability, would ameliorate dementia in neurodegenerative conditions.

Methods

In the present double-blinded placebo-controlled 3-arm 3-sequence comparative study, 48 subjects characterized with moderate dementia due to the onset of Alzheimer's disease were randomized into three groups (N = 16/group) and supplemented with 400 mg × 2/day of either placebo (MCC), unformulated standard curcumin complex with 95% purity (USC), or CGM as a sachet for six months. The relative changes in cognitive and locomotor functions and biochemical markers were compared.

Results

Supplementation with CGM produced significant (P < 0.05) improvement in the Mini-Mental State Examination (MMSE) and the Geriatric Locomotive Function Scale (GLFS) scores in both intra- and inter-group comparison by 2 × 2 repeated measures (RM) ANOVA. Further, analysis of the serum levels of specific biomarkers (BDNF, Aβ42, tau protein, IL-6, and TNF-α) also revealed a significant (P < 0.05) improvement among CGM subjects as compared to placebo and the USC groups.

Conclusion

Supplementation with CGM as sachet was found to offer significant delay in the progress of Alzheimer's disease, as evident from the improvements in locomotive and cognitive functions related to dementia.

Clinical trial registration

http://ctri.nic.in, identifier: CTRI/2018/03/012410.

Disentangling accelerated cognitive decline from the normal aging process and unraveling its genetic components: A neuroimaging-based deep learning approach

Background

The progressive cognitive decline that is an integral component of AD unfolds in tandem with the natural aging process. Neuroimaging features have demonstrated the capacity to distinguish cognitive decline changes stemming from typical brain aging and Alzheimer's disease between different chronological points.

Methods

We developed a deep-learning framework based on dual-loss Siamese ResNet network to extract fine-grained information from the longitudinal structural magnetic resonance imaging (MRI) data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study. We then conducted genome-wide association studies (GWAS) and post-GWAS analyses to reveal the genetic basis of AD-related accelerated cognitive decline.

Results

We used our model to process data from 1,313 individuals, training it on 414 cognitively normal people and predicting cognitive assessment for all participants. In our analysis of accelerated cognitive decline GWAS, we identified two genome-wide significant loci: APOE locus (chromosome 19 p13.32) and rs144614292 (chromosome 11 p15.1). Variant rs144614292 (G>T) has not been reported in previous AD GWA studies. It is within the intronic region of NELL1, which is expressed in neuron and plays a role in controlling cell growth and differentiation. In addition, MUC7 and PROL1/OPRPNon chromosome 4 were significant at the gene level. The cell-type-specific enrichment analysis and functional enrichment of GWAS signals highlighted the microglia and immune-response pathways. Furthermore, we found that the cognitive decline slope GWAS was positively correlated with previous AD GWAS.

Conclusion

Our deep learning model was demonstrated effective on extracting relevant neuroimaging features and predicting individual cognitive decline. We reported a novel variant (rs144614292) within the NELL1 gene. Our approach has the potential to disentangle accelerated cognitive decline from the normal aging process and to determine its related genetic factors, leveraging opportunities for early intervention.

Reduced body cell mass and functions in lower extremities are associated with mild cognitive impairment and Alzheimer's dementia

This study examined the alterations of segmental body composition in individuals with Alzheimer's pathology (AD), including mild cognitive impairment (MCI) and dementia. A multifrequency bioimpedance analysis (BIA) was used to provide segmental water and impedance variables from 365 cognitively normal (CN), 123 MCI due to AD, and 30 AD dementia participants. We compared the BIA variables between the three groups, examined their correlations with neuropsychological screening test scores, and illustrate their 95% confidence RXc graphs. AD dementia participants were older, more depressive, and had worse cognitive abilities than MCI due to AD and CN participants. Although the BIA variables showed weak partial correlations with the cognitive test scores, we found patterns of an increasing water content in lean mass, increasing extra to intracellular water ratio, and decreasing reactance and phase angle in the lower extremities with effect sizes ranging from 0.26 to 0.51 in the groups of MCI and dementia due to AD compared with CN individuals. The RXc graphs upheld the findings with a significant displacement downward and toward the right, dominantly in the lower extremities. Individuals with AD pathology exhibit a reduced body cell mass or cell strength, an abnormal cellular water distribution, and an overhydration status in lean mass, especially in the lower extremities.

Role of comprehensive geriatric assessment in screening for mild cognitive disorders

BACKGROUND

The role of comprehensive geriatric assessment (CGA) in screening for mild cognitive disorders was not known.

AIM

To evaluate the role of CGA in screening for mild cognitive disorders.

METHODS

A total of 100 elderly people who underwent health examinations in our hospital and community between January 2020 and December 2021 were included for analysis. Using Petersen as the diagnostic gold standard, healthy individuals were included in the control group and patients with mild cognitive impairment were assigned to the study group. The correlation between the cognitive function of the patients and their baseline clinical profiles was analyzed. Patients' Montreal Cognitive Assessment (MoCA) and CGA screening results were compared, and the sensitivity and specificity were calculated to assess the screening role of CGA.

RESULTS

CGA assessment yielded higher diagnostic accuracy than MoCA. The results of the multivariate regression analysis showed no correlation of gender, age, body mass index and literacy with cognitive function. Patients with mild cognitive impairment obtained significantly lower MoCA scores than healthy individuals (P < 0.05). In the CGA scale, patients with mild cognitive impairment showed significantly lower Mini-mental State Examination, Miniature Nutritional Assessment and Berg Balance Scale scores, and higher Activity of Daily Living, Instrumental Activities of Daily Living Scale and Frailty Screening Inventory scores than healthy individuals (P < 0.05), whereas the other assessment scales showed no significant differences (P > 0.05). The CGA provides higher diagnostic sensitivity and specificity than the MoCA (P < 0.05).

CONCLUSION

CGA allows accurate identification of mild cognitive impairment with high sensitivity and specificity, facilitating timely and effective intervention, and is thus recommended for clinical use.

Frail patients who fall and their risk on major bleeding and intracranial haemorrhage. Outcomes from the Fall and Syncope Registry

BACKGROUND

Major bleeding, and intracranial bleeding specifically, are severe complications related to the use of anticoagulation. To what extent the risk for major bleeding is elevated among frail older people is not well known because they are underrepresented in the randomized clinical trials (RCTs). This study investigates the risk for major bleeding (MB) and intra cranial haemorrhage (ICH) in frail older people who fall.

METHODS

All patients 65 years and older visiting the Fall and Syncope Clinic, between November 2011 and January 2020, and underwent a MRI of the brain were eligible. Frailty was assessed with a Frailty Index, based on the accumulation of deficits model. Cerebral small vessel disease was described and evaluated as proposed in the position paper of Wardlaw and colleagues in 2013.

RESULTS

479 patients were included in this analysis. Mean follow-up was 7 years per patient (ranging from 1 month to 8 years and 5 months). 368 patients (77%) were frail. A total of 81 patients used oral anticoagulation (OAC). 17 extracranial MB of which 3 were traumatic and 14 gastrointestinal, and 16 ICH occurred. There was a total of 603.4 treatment years with OAC, and 8 MBs occurred among patients on OAC (bleeding rate 1.32 per 100 treatment years), of which 2 ICHs (bleeding rate 0.33 per 100 treatment years). The risk for extracranial MB was increased by the use of antiplatelet agents (APA) (adjusted OR 6.9, CI 95% 1.2-38.3), and by the use of OAC (adjusted OR 9.8, CI 95% 1.7-56.1). The risk for ICH was only heightened by white matter hyperintensities (WMH) (adjusted OR 3.8, CI 95% 1.0-13.4). The use of APA (adjusted OR 0.9, CI 95% 0.3-3.3) or OAC (adjusted OR 0.6, CI 95% 0.1-3.3) did not elevate the risk for ICH.

CONCLUSION

In contrast to common belief, frail patients on OAC with repeated falls show a comparable bleeding rate as in the large RCTs, and the use of OAC did not increase the risk for ICH. However, the number of MBs was low, and of ICHs very low, despite extensive follow-up in this registry.

Initial non-amnestic symptoms relate to faster rate of functional and cognitive decline compared to amnestic symptoms in neuropathologically confirmed dementias

INTRODUCTION

The relationship between initial cognitive symptoms and subsequent rate of clinical decline is important in clinical care and the design of dementia clinical trials.

METHODS

This retrospective longitudinal, autopsy-confirmed, cohort study among 2426 participants in the National Alzheimer's Coordinating Center database included Alzheimer's disease (AD) pathology, n = 1187; Lewy body pathology (LBP), n = 331; and mixed pathology (AD-LBP), n = 904. The predominant initial cognitive symptom was assessed clinically. Linear mixed models evaluated the longitudinal outcome of the Clinical Dementia Rating-Sum of Boxes (CDR-SB) score.

RESULTS

Non-amnestic initial symptoms had a faster rate of decline than amnestic symptoms in all three groups. Language symptoms had a faster rate of decline in all three groups. Executive symptoms had a faster rate of decline than amnestic in AD and AD-LBP. There was a similar trend for visuospatial symptoms in AD-LBP.

DISCUSSION

Initial cognitive symptoms, despite varied underlying pathology, are a predictor of longitudinal functional outcomes among dementias.

HIGHLIGHTS

Initial non-amnestic symptoms had a faster rate of longitudinal cognitive and functional decline on the Clinical Dementia Rating-Sum of Boxes (CDR-SB) scores than amnestic symptoms among Alzheimer's disease, Lewy body pathology, and mixed neuropathology. Given the relative size of CDR-SB changes in Alzheimer's disease clinical trials, clarifying the nature of initial symptoms could be an important variable in ensuring appropriately designed clinical trials.

General anesthesia with S-ketamine improves the early recovery and cognitive function in patients undergoing modified radical mastectomy: a prospective randomized controlled trial

BACKGROUND

Postoperative cognitive dysfunction (POCD) is a common postoperative disorder that is frequently observed after general anesthesia, which seriously threatens the quality of patients' life. Existing studies have demonstrated that S-ketamine plays an important role in improving neuroinflammation. This trial aimed to explore the effects of S-ketamine on quality of recovery and cognitive function in patients following modified radical mastectomy (MRM).

METHODS

Ninety patients aged 45 to 70 years with ASA grades of I or II, who underwent MRM, were selected. Patients were randomly assigned to the S-ketamine or control group. In the S-ketamine group, patients were induced with S-ketamine instead of sufentanil and maintained with S-ketamine and remifentanil. In the control group, patients were induced with sufentanil and maintained with remifentanil. The primary outcome was the Mini-Mental State Examination (MMSE) and Quality of Recovery-15 (QoR-15) score. Secondary outcomes including visual analog scale (VAS) score, cumulative propofol and opioids consumption, post anesthesia care unit (PACU) recovery time, occurrence of remedial analgesia, postoperative nausea and vomiting (PONV), other adverse events, as well as patient satisfaction.

RESULTS

The global QoR-15 scores at postoperative day 1 (POD1) were significantly higher in the S-ketamine group than in the control group (124 [119.5-128.0] vs. 119 [114.0-123.5], P = 0.002), with a median difference of 5 points (95% confidence interval [CI] [-8 to -2]). Similarly, the global QoR-15 scores at postoperative day 2 (POD2) in the S-ketamine group were significantly higher than in the control group (140.0 [133.0-145.0] vs. 132.0 [126.5-141.5], P = 0.004). In addition, among the five subcomponents of the 15-item scale, S-ketamine group had a higher score in terms of physical comfort, pain, and emotional state both at POD1 and POD2. In terms of MMSE score, S-ketamine could promote the recovery of postoperative cognitive function at POD1, but not at POD2. Furthermore, the consumption of opioids, VAS score, and remedial analgesia in the S-ketamine group decreased significantly.

CONCLUSIONS

Collectively, our findings support that general anesthesia with S-ketamine as a potential strategy showed high safety and could not only improve the quality of recovery mainly through improving pain, physical comfort, and emotional state but also promote the recovery of cognitive function on POD1 in patients undergoing MRM.

TRIAL REGISTRATION

The study was registered in the Chinese Clinical Trial Registry (registration No:ChiCTR2200057226, Date of registration: 04/03/2022).

Risk assessment and stratification of mild cognitive impairment among the Chinese elderly: attention to modifiable risk factors

BACKGROUND

The early identification of individuals at risk of mild cognitive impairment (MCI) has major public health implications for Alzheimer's disease prevention.

OBJECTIVE

This study aims to develop and validate a risk assessment tool for MCI with a focus on modifiable factors and a suggested risk stratification strategy.

METHODS

Modifiable risk factors were selected from recent reviews, and risk scores were obtained from the literature or calculated based on the Rothman-Keller model. Simulated data of 10 000 subjects with the exposure rates of the selected factors were generated, and the risk stratifications were determined by the theoretical incidences of MCI. The performance of the tool was verified using cross-sectional and longitudinal datasets from a population-based Chinese elderly cohort.

RESULTS

Nine modifiable risk factors (social isolation, less education, hypertension, hyperlipidaemia, diabetes, smoking, drinking, physical inactivity and depression) were selected for the predictive model. The area under the curve (AUC) was 0.71 in the training set and 0.72 in the validation set for the cross-sectional dataset. The AUCs were 0.70 and 0.64 in the training and validation sets, respectively, for the longitudinal dataset. A combined risk score of 0.95 and 1.86 was used as the threshold to categorise MCI risk as 'low', 'moderate' and 'high'.

CONCLUSION

A risk assessment tool for MCI with appropriate accuracy was developed in this study, and risk stratification thresholds were also suggested. The tool might have significant public health implications for the primary prevention of MCI in elderly individuals in China.

Comparison of DBFS with MoCA and MMSE tools for MCI screening

Mild cognitive impairment (MCI) has been associated with many diseases. The MCI could be a marker for the early diagnosis of certain diseases. Early detection of MCI could be beneficial for restoration of cognitive reserves. One hundred and five subjects were included in the study, underwent the Digital Brain Function Screen (DBFS) test as well as the Montreal Cognitive Assessment (MoCA) test and 73 subjects took the Mini-Mental State Examination (MMSE) test. DBFS test and retest was taken by 16 subjects. The test scores of DBFS tool showed significant positive correlation with MoCA and MMSE test scores. In conclusion, the DBFS tool could be an effective digital tool which can overcome the disadvantages of traditional tools of screening MCI like MoCA and MMSE.

Determinants of Nutritional Risk among Community-Dwelling Older Adults with Social Support

BACKGROUND

It is well established that older adults are at risk for malnutrition due to several social and non-social determinants, namely physiological, psychosocial, dietary and environmental determinants. The progression to malnutrition is often insidious and undetected. Thus, nutritional assessment should consider a complex web of factors that can impact nutritional status (NS). The primary objective of this study was to assess the NS of older adults attending senior centres (SCs) and to identify its predictors.

METHODS

This cross-sectional study enrolled a sample of community-dwelling older adults in Lisbon. NS was assessed using Mini Nutritional Assessment (MNA^®). Malnutrition or malnutrition risk (recategorised into a single group) was predicted using binary logistic regression models, considering those participants classified as having a normal NS as the reference group. Data were collected through face-to-face interviews and anthropometric indices were measured according to Isak procedures.

RESULTS

A sample of 337 older adults, with an average age of 78.4 years old (range 66-99), mostly women (n = 210; 62.3%), were enrolled. Older adults at risk of malnutrition accounted for 40.7% of the sample. Being older (OR = 1.045, CI 95% [1.003-1.089], p = 0.037), having a worse perception of health status (OR = 3.395, CI 95% [1.182-9.746], p = 0.023), having or having had depression (OR = 5.138, CI 95% [2.869-9.201], p < 0.001), and not having or having had respiratory tract problems (OR = 0.477, CI 95% [0.246-0.925], p = 0.028) were independent predictors of malnutrition or malnutrition risk. An intermediate time of SC attendance was associated with a lower probability of malnutrition or risk (OR = 0.367, CI 95% [0.191-0.705], p = 0.003).

CONCLUSIONS

NS among older adults has a multifactorial aetiology, with a strongly social component and is related to health circumstances. Further research is needed to timely identify and understand nutritional risk among this population.

Access to, use of, and experiences with social alarms in home-living people with dementia: results from the LIVE@Home.Path trial

Background

Social alarms are considered an appropriate technology to ensure the safety and independence of older adults, but limited research has been conducted on their actual use. We, therefore, explored the access, experiences, and use of social alarms among home-bound people with dementia and their informal caregivers (dyads).

Methods

From May 2019 to October 2021, the LIVE@Home.Path mixed-method intervention trial collected data from semi-quantitative questionnaires and qualitative interviews conducted among home-dwelling people with dementia and their informal caregivers in Norway. The study focused on data from the final assessment at 24 months.

Results

A total of 278 dyads were included, and 82 participants reached the final assessment. The mean age of the patients was 83 years; 74.6% were female; 50% lived alone; and 58% had their child as a caregiver. A total of 62.2% of subjects had access to a social alarm. Caregivers were more likely to answer that the device was not in use (23.6%) compared to patients (14%). Qualitative data revealed that approximately 50% of the patients were not aware of having such an alarm. Regression analyses assessed that access to a social alarm was associated with increasing age (86-97 years, p = 0.005) and living alone (p < 0.001). Compared to their caregivers, people with dementia were more likely to answer that the device gave them a false sense of security (28% vs. 9.9%), while caregivers were more likely to answer that the social alarm was of no value (31.4% vs.14.0%). The number of social alarms installed increased from 39.5% at baseline to 68% at 24 months. The frequency of unused social alarms increased from 12 months (17.7%) to 24 months (23.5%), and patients were less likely to feel safe during this period (60.8% vs. 70%).

Conclusion

Depending on their living situation, patients and family members experienced the installed social alarm differently. There is a gap between access to and the use of social alarms. The results indicate an urgent need for better routines in municipalities with regard to the provision and follow-up of existing social alarms. To meet the users' changing needs and abilities, passive monitoring may help them adapt to declining cognitive abilities and increase their safety.Clinical Trial Registration: https://ClinicalTrials.gov, NCT04043364.

Speeding up: Discrete mediolateral perturbations increased self-paced walking speed in young and older adults

BACKGROUND

In uncertain environments and with increasing age, humans often walk, slower while taking shorter, quicker, and wider steps, reflective of a cautious gait., Understanding when humans opt to use a cautious gait and the differences in gait, strategies used as people age could be examined with perturbations on a self-paced, treadmill that allows participants to adjust their walking speed. Adding varying degrees, of unpredictability, an inherent element of real-world walking, could also improve, understanding of when specific gait strategies are used RESEARCH QUESTION: We investigated how healthy young and older adults adjust their, gait strategies when responding to perturbations of varying unpredictability. We, hypothesized that more unpredictable perturbations would produce more cautious gait, strategies and be more pronounced in older adults than young adults METHODS: Ten young and ten older adults walked on a self-paced treadmill with, discrete mediolateral treadmill shift perturbations. We changed the shift magnitude, and/or the timing of the perturbations during the gait cycle to vary perturbation, unpredictability. We analyzed walking speed and step kinematics from treadmill and, motion capture data RESULTS: Surprisingly, participants walked faster, not slower, for the conditions with, perturbations. Even more surprising, older adults walked faster overall than young, adults. As expected, participants took faster and wider steps for the most unpredictable, perturbation but also took longer steps, which was not expected. Step kinematic, variability and average step width also increased as perturbation unpredictability, increased, suggesting that the more unpredictable conditions demanded greater, balance control. Additionally, older adults had greater step kinematic variability, highlighted further using detrended step length variability, compared to young adults SIGNIFICANCE: Overall, these findings provide new insights about gait strategies and, suggest that perturbations such as discrete mediolateral treadmill shifts can potentially, be designed to encourage participants to walk faster, if it is beneficial.

Serum brain-derived neurotrophic factor as diagnosis clue for Alzheimer's disease: A cross-sectional observational study in the elderly

Objective

Brain-derived neurotrophic factor (BDNF) has not been validated as a diagnostic marker for Alzheimer's disease (AD). To provide a different perspective, this study aimed to evaluate the relationship between serum levels of mature BDNF (mBDNF) and precursor BDNF (proBDNF) in AD and to investigate whether serum BDNF levels or the ratio of mBDNF levels to proBDNF levels (M/P) could be a valuable biomarker for determining the risk of AD in elderly individuals.

Method

A total of 126 subjects who met the inclusion criteria were assigned to either the AD group (n = 62) or the healthy control group (HC, n = 64) in this cross-sectional observationl study. Serum levels of mBDNF and proBDNF were measured using enzyme immunoassay kits. We analyzed the Mini-Mental State Examination (MMSE) scores from the two groups and examined the associations between AD and BDNF metabolism.

Results

The serum concentration of proBDNF was significantly higher in ADs (4140.937 pg/ml) than in HCs (2606.943 pg/ml; p &lt; 0.01). The MMSE significantly correlated with proBDNF (p &lt; 0.01, r = −0.686) and M/P (p &lt; 0.01, r = 0.595) in all subjects. To determine the risk for AD, the area under the receiver operating characteristic curve was calculated, which was 0.896 (95% confidence interval 0.844–0.949) for proBDNF and 0.901 (95% 0.850–0.953) for proBDNF and M/P combined.

Conclusion

We observed a correlation between low serum proBDNF levels and higher MMSE scores in AD. The most effective diagnostic strategy was the combination of proBDNF and M/P, whereas mBDNF levels performed poorly when we evaluated the predictive model.

Dietary and Environmental Risk Factors in Parkinson's and Alzheimer's Disease: A Semi-Quantitative Pilot Study

Objective

Environmental influence and dietary variations are well-known risk factors for various diseases including neurodegenerative disorders. Preliminary evidence suggests that diet in early-life and living environment might influence the incidence of Parkinson's disease (PD) in later phase of life. There have been limited epidemiologic studies on this aspect especially in India. In this hospital-based case-control study, we intended to identify dietary and environmental risk factors of PD.

Methods

Patients with PD (n = 105), Alzheimer's disease (AD) (n = 53) and healthy individuals (n = 81) were recruited. Dietary intake and environmental exposures were assessed using a validated Food-Frequency and Environmental Hazard Questionnaire. Their demographic details and living environment were also recorded using the same questionnaire.

Results

Pre-morbid consumption of carbohydrate and fat was significantly higher whereas dietary fiber and fruit content was significantly lesser in PD as compared to AD and healthy age-matched controls. Meat and milk intake was the highest among all the food groups in PD patients. Rural living and their habitation near water bodies were significantly more frequent in PD patients.

Conclusion

We found that past intake of carbohydrate, fat, milk, and meat are associated with increased risk of PD. On the other hand, rural living and habitat near water bodies might be associated with incidence and severity of PD. Hence, preventive strategies related to dietary and environmental modulators in PD might be clinically useful in the future.

Exploring and Mapping Screening Tools for Cognitive Impairment and Traumatic Brain Injury in the Homelessness Context: A Scoping Review

Cognitive impairment is common amongst people experiencing homelessness, yet cognitive screening and the collection of history of brain injury rarely features in homelessness service delivery practice. The purpose of this research was to scope and map strategies for screening for the potential presence of cognitive impairment or brain injury amongst people experiencing homelessness and identify instruments that could be administered by homelessness service staff to facilitate referral for formal diagnosis and appropriate support. A search was conducted across five databases, followed by a hand search from relevant systematic reviews. A total of 108 publications were included for analysis. Described in the literature were 151 instruments for measuring cognitive function and 8 instruments screening for history of brain injury. Tools that were described in more than two publications, screening for the potential presence of cognitive impairment or history of brain injury, were included for analysis. Of those regularly described, only three instruments measuring cognitive function and three measuring history of brain injury (all of which focused on traumatic brain injury (TBI)) may be administered by non-specialist assessors. The Trail Making Test (TMT) and the Ohio State University Traumatic Brain Injury Identification Method (OSU TBI-ID) are both potentially viable tools for supporting the identification of a likely cognitive impairment or TBI history in the homelessness service context. Further population-specific research and implementation science research is required to maximise the potential for practice application success.

Affective Out-World Experience via Virtual Reality for Older Adults Living with Mild Cognitive Impairments or Mild Dementia

Older adults with cognitive impairments may face barriers to accessing experiences beyond their physical premises. Previous research has suggested that missing out on emotional experiences may affect mental health and impact cognitive abilities. In recent years, there has been growing research interest in designing non-pharmacological interventions to improve the health-related quality of life of older adults. With virtual reality offering endless opportunities for health support, we must consider how virtual reality can be sensitively designed to provide comfortable, enriching out-world experiences to older adults to enhance their emotional regulation. Thirty older adults living with mild cognitive impairment or mild dementia participated in the study. Affect and emotional behavior were measured. The usability and the sense of presence were also assessed. Finally, we assessed the virtual reality experiences based on physiological responses and eye-tracking data. The results indicated that virtual reality can positively enhance the mental health of this population by eliciting a positive affective state and enhancing their emotional regulation. Overall, this paper raises awareness of the role of virtual reality in emotion elicitation, regulation, and expression and enhances our understanding of the use of virtual reality by older adults living with mild cognitive impairments or mild dementia.

Assessment of clinical features and coexisting geriatric syndromes in newly diagnosed dementia with Lewy bodies: a retrospective study in a tertiary geriatrics setting in Turkey

PURPOSE

Identifying the associated clinical conditions in patients with newly diagnosed dementia with Lewy bodies (DLB) may contribute to the disease management. This study aimed to examine the clinical features and coexisting geriatric syndromes of patients with newly diagnosed DLB.

METHOD

This cross-sectional study included newly diagnosed DLB participants who were admitted to a tertiary geriatric outpatient clinic. Of the 857 patients with dementia, 116 DLB diagnoses were eligible for analysis. The core and supportive clinical features of DLB were recorded. Geriatric syndromes including polypharmacy, depression, insomnia, dependency, a history of delirium, falls, malnutrition, urinary incontinence, functional impairment, and living alone, were assessed and recorded at baseline.

RESULTS

The mean age was 79.0 ± 6.9 years, and 50.9% of the participants were female. The majority (63.8%) had mild dementia, 31.9% had moderate, and 4.3% had severe disease. Cognitive fluctuations (78.4%), visual hallucinations (77.6%), and Parkinsonism (73.3%) were the most common clinical features. Functional impairment (59.5%) and urinary incontinence (59.5%) were the leading geriatric syndromes, followed by polypharmacy (56.9%), depressive symptoms (54.7%), falls (52.6%), insomnia (49.1%), malnutrition (24.3%), and delirium (6.0%). Women had more functional impairment and depressive symptoms than men.

CONCLUSION

Although most patients had mild dementia, three-quarters of the DLB cohort had hallucinations, and nearly two-thirds were functionally impaired. The proportion of other serious health conditions also increased, indicating a high comorbidity and geriatric syndrome burden. Comprehensive geriatric assessment is strongly recommended for DLB patients from the time of diagnosis until death to reduce disability and comorbidities.

THE CLINICAL TRIAL REGISTRATION NUMBER

NCT05052450.

Using Artificial Intelligence to Learn Optimal Regimen Plan for Alzheimer's Disease

Background

Alzheimer's Disease (AD) is a progressive neurological disorder with no specific curative medications. While only a few medications are approved by FDA (i.e., donepezil, galantamine, rivastigmine, and memantine) to relieve symptoms (e.g., cognitive decline), sophisticated clinical skills are crucial to optimize the appropriate regimens given the multiple coexisting comorbidities in this patient population.

Objective

Here, we propose a study to leverage reinforcement learning (RL) to learn the clinicians' decisions for AD patients based on the longitude records from Electronic Health Records (EHR).

Methods

In this study, we withdraw 1,736 patients fulfilling our criteria, from the Alzheimer's Disease Neuroimaging Initiative(ADNI) database. We focused on the two most frequent concomitant diseases, depression, and hypertension, thus resulting in five main cohorts, 1) whole data, 2) AD-only, 3) AD-hypertension, 4) AD-depression, and 5) AD-hypertension-depression. We modeled the treatment learning into an RL problem by defining the three factors (i.e., states, action, and reward) in RL in multiple strategies, where a regression model and a decision tree are developed to generate states, six main medications extracted (i.e., no drugs, cholinesterase inhibitors, memantine, hypertension drugs, a combination of cholinesterase inhibitors and memantine, and supplements or other drugs) are for action, and Mini-Mental State Exam (MMSE) scores are for reward.

Results

Given the proper dataset, the RL model can generate an optimal policy (regimen plan) that outperforms the clinician's treatment regimen. With the smallest data samples, the optimal-policy (i.e., policy iteration and Q-learning) gained a lesser reward than the clinician's policy (mean -2.68 and -2.76 vs . -2.66, respectively), but it gained more reward once the data size increased (mean -3.56 and -2.48 vs . -3.57, respectively).

Conclusions

Our results highlight the potential of using RL to generate the optimal treatment based on the patients' longitude records. Our work can lead the path toward the development of RL-based decision support systems which could facilitate the daily practice to manage Alzheimer's disease with comorbidities.

An app for predicting patient dementia classes using convolutional neural networks (CNN) and artificial neural networks (ANN): Comparison of prediction accuracy in Microsoft Excel

BACKGROUND

Dementia is a progressive disease that worsens over time as cognitive abilities deteriorate. Effective preventive interventions require early detection. However, there are no reports in the literature concerning apps that have been developed and designed to predict patient dementia classes (DCs). This study aimed to develop an app that could predict DC automatically and accurately for patients responding to the clinical dementia rating (CDR) instrument.

METHODS

A CDR was applied to 366 outpatients in a hospital in Taiwan, with assessments on 25 and 49 items endorsed by patients and family members, respectively. The 2 models of convolutional neural networks (CNN) and artificial neural networks (ANN) were applied to examine the prediction accuracy based on 5 classes (i.e., no cognitive decline, very mild, mild, moderate, and severe) in 4 scenarios, consisting of 74 (items) in total, 25 in patients, 49 in family, and a combination strategy to select the best in the aforementioned scenarios using the forest plot. Using CDR scores in patients and their families on both axes, patients were dispersed on a radar plot. An app was developed to predict patient DC.

RESULTS

We found that ANN had higher accuracy rates than CNN with a ratio of 3:1 in the 4 scenarios. The highest accuracy rate (=93.72%) was shown in the combination scenario of ANN. A significant difference was observed between the CNN and ANN in terms of the accuracy rate. An available ANN-based app for predicting DC in patients was successfully developed and demonstrated in this study.

CONCLUSION

On the basis of a combination strategy and a decision rule, a 74-item ANN model with 285 estimated parameters was developed and included. The development of an app that will assist clinicians in predicting DC in clinical settings is required in the near future.

Comparison of Cognitive Functions Between Patients with Alzheimer Disease, Patients with Mild Cognitive Impairment, and Healthy People

Background: There is a growing need for predicting Alzheimer disease (AD) based on emerging neurocognitive dysfunction before the onset of the disease. Objectives: According to neuropathological changes in the mesial temporal lobe (MTL) before the onset of clinical symptoms and the relationship between the function of these structures and cognitive functions (such as visual memory, working memory, and new learning), we aimed to investigate the possibility of these cognitive functions as markers of transition from mild cognitive impairment (MCI) to AD. Methods: In this case-control study, 15 patients with AD, 18 patients with MCI (from memory clinics of Tehran University of Medical Sciences), and 15 healthy people were compared using the 3 subtests of the Cambridge Neuropsychological Test Automated Battery (CANTAB), including spatial working memory (SWM), pattern recognition memory (PRM), and paired-associate learning (PAL). The tests were performed between 9 AM and 12 noon. The scores were compared by a 1-way analysis of variance (ANOVA). Results: The mean ages of AD, MCI, and healthy groups were 68.66, 68.22, and 64.26 years, respectively. In terms of the SWM test, in 2 of 3 variables, there were significant differences between the 3 groups (P = 0.000 and P = 0.001). Regarding the PRM test, there were significant differences between the 3 groups in accuracy and response time (P = 0.000 and P = 0.004, respectively). Regarding PAL, there were significant differences between the 3 groups in all 3 variables (P = 0.000). The Mini-mental State Examination (MMSE) scores were associated with almost all variable scores (P = 0.000). Conclusions: Dysfunction in new learning and recognition memory can be indicators of MCI and its progression to AD, whereas the assessment of SWM can only be used to assess the progression of MCI to AD.

The Costs of Dementia in Europe: An Updated Review and Meta-analysis

BACKGROUND AND OBJECTIVE

The prevalence of dementia is increasing, while new opportunities for diagnosing, treating and possibly preventing Alzheimer's disease and other dementia disorders are placing focus on the need for accurate estimates of costs in dementia. Considerable methodological heterogeneity creates challenges for synthesising the existing literature. This study aimed to estimate the costs for persons with dementia in Europe, disaggregated into cost components and informative patient subgroups.

METHODS

We conducted an updated literature review searching PubMed, Embase and Web of Science for studies published from 2008 to July 2021 reporting empirically based cost estimates for persons with dementia in European countries. We excluded highly selective or otherwise biased reports, and used a random-effects meta-analysis to produce estimates of mean costs of care across five European regions.

RESULTS

Based on 113 studies from 17 European countries, the estimated mean costs for all patients by region were highest in the British Isles (73,712 EUR), followed by the Nordics (43,767 EUR), Southern (35,866 EUR), Western (38,249 EUR), and Eastern Europe and Baltics (7938 EUR). Costs increased with disease severity, and the distribution of costs over informal and formal care followed a North-South gradient with Southern Europe being most reliant on informal care.

CONCLUSIONS

To our knowledge, this study represents the most extensive meta-analysis of the cost for persons with dementia in Europe to date. Though there is considerable heterogeneity across studies, much of this is explained by identifiable factors. Further standardisation of methodology for capturing resource utilisation data may further improve comparability of future studies. The cost estimates presented here may be of value for cost-of-illness studies and economic evaluations of novel diagnostic technologies and therapies for Alzheimer's disease.