Strength together: examining risk and protective factors associated with dementia and cognitive impairment in Aboriginal and Torres Strait Islander peoples through harmonisation of landmark studies.

BACKGROUND: Rates of dementia for Aboriginal and Torres Strait Islander peoples are three to five times greater compared to non-Indigenous Australians, with earlier age of onset. However, the risk and protective factors that drive these higher rates vary across existing cohort studies, with minimal findings on the role of vascular risk factors beyond stroke. Harmonisation of data across studies may offer greater insights through enhanced diversity and strengthened statistical capabilities. This study aims to combine three landmark cohort studies of Aboriginal and Torres Strait Islander participants to better understand the determinants of cognitive health and dementia. METHODS/DESIGN: Three cohort studies - the Kimberley Healthy Adults Project (KHAP, N = 363), Koori Growing Old Well Study (KGOWS, N = 336) and Torres Strait Dementia Prevalence Study (TSDPS, N = 274) - share a similar research methodology with demographic, medical history, psychosocial factors, cognitive tests and consensus clinical diagnoses of cognitive impairment and dementia. Associations between risk and protective factors of interest and the presence of dementia and/or cognitive impairment diagnoses will be evaluated by univariable and multivariable logistic regression in a harmonised cross-sectional cohort of 898 participants. Factors associated with incident dementia and/or cognitive impairment will be assessed in a subset of KHAP (n = 189) and KGOWS participants (n = 165) who were available in longitudinal follow-up, after exclusion of those with baseline dementia or cognitive impairment. Analyses in relation to outcome measure of death or dementia will be conducted to account for the competing risk of death. Logistic regression will be used to evaluate the association between the individual components of the 16-component Kimberley Indigenous Cognitive Assessment (KICA) tool and the presence of dementia and cognitive impairment determined by independent consensus diagnoses. Multivariable binary logistic regression will be used to adjust for the effect of confounding variables. Results will be reported as odds ratios (OR) with 95% confidence intervals (95% CI). DISCUSSION: Greater understanding of risk and protective factors of dementia and cognitive impairment relevant to Aboriginal and Torres Strait Islander peoples may improve approaches across the life course to delay cognitive decline and reduce dementia risk.

Community screening for dementia among older adults in China: a machine learning-based strategy.

BACKGROUND: Dementia is a leading cause of disability in people older than 65 years worldwide. However, diagnosing dementia in its earliest symptomatic stages remains challenging. This study combined specific questions from the AD8 scale with comprehensive health-related characteristics, and used machine learning (ML) to construct diagnostic models of cognitive impairment (CI). METHODS: The study was based on the Shenzhen Healthy Ageing Research (SHARE) project, and we recruited 823 participants aged 65 years and older, who completed a comprehensive health assessment and cognitive function assessments. Permutation importance was used to select features. Five ML models using BalanceCascade were applied to predict CI: a support vector machine (SVM), multilayer perceptron (MLP), AdaBoost, gradient boosting decision tree (GBDT), and logistic regression (LR). An AD8 score ≥ 2 was used to define CI as a baseline. SHapley Additive exPlanations (SHAP) values were used to interpret the results of ML models. RESULTS: The first and sixth items of AD8, platelets, waist circumference, body mass index, carcinoembryonic antigens, age, serum uric acid, white blood cells, abnormal electrocardiogram, heart rate, and sex were selected as predictive features. Compared to the baseline (AUC = 0.65), the MLP showed the highest performance (AUC: 0.83 ± 0.04), followed by AdaBoost (AUC: 0.80 ± 0.04), SVM (AUC: 0.78 ± 0.04), GBDT (0.76 ± 0.04). Furthermore, the accuracy, sensitivity and specificity of four ML models were higher than the baseline. SHAP summary plots based on MLP showed the most influential feature on model decision for positive CI prediction was female sex, followed by older age and lower waist circumference. CONCLUSIONS: The diagnostic models of CI applying ML, especially the MLP, were substantially more effective than the traditional AD8 scale with a score of ≥ 2 points. Our findings may provide new ideas for community dementia screening and to promote such screening while minimizing medical and health resources.

Peripheral GFAP and NfL as early biomarkers for dementia: longitudinal insights from the UK Biobank.

BACKGROUND: Peripheral glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are sensitive markers of neuroinflammation and neuronal damage. Previous studies with highly selected participants have shown that peripheral GFAP and NfL levels are elevated in the pre-clinical phase of Alzheimer's disease (AD) and dementia. However, the predictive value of GFAP and NfL for dementia requires more evidence from population-based cohorts. METHODS: This was a prospective cohort study to evaluate UK Biobank participants enrolled from 2006 to 2010 using plasma GFAP and NfL measurements measured by Olink Target Platform and prospectively followed up for dementia diagnosis. Primary outcome was the risk of clinical diagnosed dementia. Secondary outcomes were cognition. Linear regression was used to assess the associations between peripheral GFAP and NfL with cognition. Cox proportional hazard models with cross-validations were used to estimate associations between elevated GFAP and NfL with risk of dementia. All models were adjusted for covariates. RESULTS: A subsample of 48,542 participants in the UK Biobank with peripheral GFAP and NfL measurements were evaluated. With an average follow-up of 13.18 ± 2.42 years, 1312 new all-cause dementia cases were identified. Peripheral GFAP and NfL increased up to 15 years before dementia diagnosis was made. After strictly adjusting for confounders, increment in NfL was found to be associated with decreased numeric memory and prolonged reaction time. A greater annualized rate of change in GFAP was significantly associated with faster global cognitive decline. Elevation of GFAP (hazard ratio (HR) ranges from 2.25 to 3.15) and NfL (HR ranges from 1.98 to 4.23) increased the risk for several types of dementia. GFAP and NfL significantly improved the predictive values for dementia using previous models (area under the curve (AUC) ranges from 0.80 to 0.89, C-index ranges from 0.86 to 0.91). The AD genetic risk score and number of APOE*E4 alleles strongly correlated with GFAP and NfL levels. CONCLUSIONS: These results suggest that peripheral GFAP and NfL are potential biomarkers for the early diagnosis of dementia. In addition, anti-inflammatory therapies in the initial stages of dementia may have potential benefits.

A Combined Index Using the Mini-Mental State Examination and Lawton Index to Discriminate Between Clinical Dementia Rating Scores of 0.5 and 1: A Development and Validation Study.

Objective: To develop a combined index using cognitive function and instrumental activities of daily living (IADL) to discriminate between Clinical Dementia Rating (CDR) scores of 0.5 and 1 in the clinical setting, and to investigate its optimal cutoff values and internal and external validities.Methods: We included outpatients aged 65-89 years with CDR scores of 0.5 or 1. The optimal cutoff values and internal validity were verified using Japanese memory clinic-based datasets between September 2010 and October 2021 [National Center for Geriatrics and Gerontology (NCGG) datasets]. Cognitive function and IADL were assessed using the Mini-Mental State Examination (MMSE) and Lawton Index (LI), respectively. The optimal cutoff values were defined using the Youden Index. To verify internal validity, sensitivity and specificity were calculated using stratified 5-fold cross-validation. To verify external validity, sensitivity and specificity of the optimal cutoff values were assessed in the Organized Registration for the Assessment of dementia on Nationwide General consortium toward Effective treatment (ORANGE) Registry dataset between July 2015 and March 2022, which has multicenter clinical data.Results: A total of 800 (mean age, 77.53 years; men, 50.1%) and 1494 (mean age, 77.97 years; men, 43.3%) participants comprised the NCGG and ORANGE Registry datasets, respectively. The optimum cutoff values for men and women were determined as MMSE < 25 and LI < 5 and MMSE < 25 and LI < 8, respectively; such a combined index showed good discriminative performance in internal (sensitivity/specificity: men, 92.50/73.52; women, 88.57/65.65) and external validities (men, 81.43/77.62; women, 77.64/74.67).Conclusion: The index developed is useful in discriminating between CDR scores of 0.5 and 1 and should be applicable to various settings, such as memory clinics and clinical research.

[Aspiration pneumonia and dementia in nursing homes: to anticipate emergency.] / Pneumonie d'aspiration en EMS et démence : anticiper l'urgence.

The care of a nursing home resident suffering from dementia and aspiration pneumonia (AP) is generally initiated by the family doctor (FD) in collaboration with the nursing home professionals. This is a holistic emergency medicine whose occurrence should be the subject of advance care planning, an AP being rarely isolated, and its risk factors are known. AP - the probable cause of half of deaths of demented individuals in nursing homes - requires essentially non-hospital care. It calls on the scientific, relational, collaborative, and ethical skills of the family doctor. This review aims to contextualize the emergency management skills of the FD in the living environment of the nursing home. The management of uncertainty linked to a probabilistic diagnosis is highlighted and care commensurate with life expectancy is provided.

La prise en soins d'un résident d'un établissement médicosocial (EMS) souffrant de démence et de pneumonie d'aspiration (PA) est en général initiée par le médecin de famille (MF) en collaboration avec les professionnels du lieu de vie de la personne. Il s'agit d'une médecine d'urgence holistique qui devrait faire l'objet d'un plan de soins anticipés, la PA étant rarement isolée et ses facteurs de risque étant connus. La PA est la cause probable de la moitié des décès de personnes démentes en EMS. Elle ne devrait en principe pas nécessiter d'hospitalisation. La PA fait appel à des compétences scientifiques, relationnelles, collaboratives et éthiques du MF. Dans cet article de revue, nous contextualisons les compétences de gestion de l'urgence du MF dans un EMS. Nous discutons également de la gestion de l'incertitude en lien avec un diagnostic probabiliste et proposons des soins en adéquation avec l'espérance de vie.

Diagnostic accuracy of cognitive screening tools validated for older adults in Iran: a systematic review and meta-analysis.

BACKGROUND: This systematic review aims to comprehensively assess the diagnostic accuracy of cognitive screening tools validated for older adults in Iran, providing evidence-based recommendations for clinicians and researchers. METHODS: A comprehensive search in March 2023 across Web of Science, PubMed, Scopus, ScienceDirect, SID, IranMedex, and IranDoc, enhanced by hand-searching references and Google Scholar, identified cross-sectional studies on cognitive screening in Iranian seniors. We assessed diagnostic accuracy, cognitive domains, and test strengths and weaknesses. A bivariate random-effects meta-analysis provided summary estimates and 95% confidence intervals, illustrated in forest plots. RESULTS: Our review, derived from an initial screening of 38 articles, focused on 17 studies involving 14 cognitive screening tools and participant counts from 60 to 350, mostly from specialized clinics. The MMSE was the only tool examined in at least three studies, prompting a meta-analysis revealing its sensitivity at 0.89 and specificity at 0.77 for dementia detection, albeit amidst significant heterogeneity (I^2 > 80%). ACE-III demonstrated the highest diagnostic accuracy for MCI and dementia, while MoCA's performance was deemed adequate for MCI and excellent for dementia. High bias risk in studies limits interpretation. CONCLUSION: This review identifies key cognitive tools for dementia and MCI in Iranian older adults, tailored to educational levels for use in primary and specialized care. It emphasizes the need for further validation to enhance diagnostic precision across diverse settings, within a concise framework prioritizing brevity and accuracy for clinical applicability.

Post-diagnostic support for persons with young-onset dementia - a retrospective analysis based on data from the Swedish dementia registry SveDem.

BACKGROUND: Approximately 3.9 million persons worldwide have young-onset dementia. Symptoms related to young-onset dementia present distinct challenges related to finances, employment, and family. To provide tailored support, it is important to gain knowledge about the formal support available for persons with young-onset dementia. Therefore, this paper aims to describe formal support for persons with young-onset dementia in Sweden and the factors influencing this support. METHODS: This retrospective study used data on persons under 65 years of age (n = 284) from The Swedish Registry for Cognitive/Dementia Disorders (SveDem) between 2021 and 2022. SveDem was established to monitor the quality of dementia care in Sweden. Characteristics of participants were obtained, including age, sex, dementia diagnosis, MMSE, medications, accommodation, and care setting. Descriptive statistics and logistic regression were used to test for associations between participant characteristics and post-diagnostic support. RESULTS: Information and educational support were usually offered to the person with young-onset dementia (90.1%) and their family (78.9%). Approximately half of the sample were offered contact with a dementia nurse (49.3%), counsellor (51.4%), or needs assessor (47.9%). A minority (28.5%) were offered cognitive aids. Six regression models were conducted based on participant characteristics to predict the likelihood that persons were offered support. Support was not predicted by age, sex, children at home, accommodation, or medications. Lower MMSE scores (p < .05) and home help (p < .05) were significantly associated with offer of a needs assessor. Living together was a significant predictor (p < .01) for information and educational support offered to the family. Care setting significantly predicted (p < .01) an offer of information and educational support for the person and family members, as well as contact with a counsellor. CONCLUSION: This study indicates potential formal support shortages for persons with young-onset dementia in some areas of dementia care. Despite equal support across most characteristics, disparities based on care setting highlight the importance of specialised dementia care. Pre-diagnostic support is minimal, indicating challenges for persons with young-onset dementia to access these services before diagnosis. While our study has identified areas in need of improvement, we recommend further research to understand the changing support needs of those with young-onset dementia.

Unsupervised multimodal modeling of cognitive and brain health trajectories for early dementia prediction.

Predicting the course of neurodegenerative disorders early has potential to greatly improve clinical management and patient outcomes. A key challenge for early prediction in real-world clinical settings is the lack of labeled data (i.e., clinical diagnosis). In contrast to supervised classification approaches that require labeled data, we propose an unsupervised multimodal trajectory modeling (MTM) approach based on a mixture of state space models that captures changes in longitudinal data (i.e., trajectories) and stratifies individuals without using clinical diagnosis for model training. MTM learns the relationship between states comprising expensive, invasive biomarkers (ß-amyloid, grey matter density) and readily obtainable cognitive observations. MTM training on trajectories stratifies individuals into clinically meaningful clusters more reliably than MTM training on baseline data alone and is robust to missing data (i.e., cognitive data alone or single assessments). Extracting an individualized cognitive health index (i.e., MTM-derived cluster membership index) allows us to predict progression to AD more precisely than standard clinical assessments (i.e., cognitive tests or MRI scans alone). Importantly, MTM generalizes successfully from research cohort to real-world clinical data from memory clinic patients with missing data, enhancing the clinical utility of our approach. Thus, our multimodal trajectory modeling approach provides a cost-effective and non-invasive tool for early dementia prediction without labeled data (i.e., clinical diagnosis) with strong potential for translation to clinical practice.

Prevalence and Determinants of Diagnosed Dementia: A Registry Linkage Study Linking Diagnosis of Dementia in the Population-Based HUNT Study to Registry Diagnosis of Dementia in Primary Care and Hospitals in Norway.

Background: A timely diagnosis of dementia can be beneficial for providing good support, treatment, and care, but the diagnostic rate remains unknown and is probably low. Objective: To determine the dementia diagnostic rate and to describe factors associated with diagnosed dementia. Methods: This registry linkage study linked information on research-based study diagnoses of all-cause dementia and subtypes of dementias, Alzheimer's disease, and related dementias, in 1,525 participants from a cross-sectional population-based study (HUNT4 70+) to dementia registry diagnoses in both primary-care and hospital registries. Factors associated with dementia were analyzed with multiple logistic regression. Results: Among those with research-based dementia study diagnoses in HUNT4 70+, 35.6% had a dementia registry diagnosis in the health registries. The diagnostic rate in registry diagnoses was 19.8% among home-dwellers and 66.0% among nursing home residents. Of those with a study diagnosis of Alzheimer's disease, 35.8% (95% confidence interval (CI) 32.6-39.0) had a registry diagnosis; for those with a study diagnosis of vascular dementia, the rate was 25.8% (95% CI 19.2-33.3) and for Lewy body dementias and frontotemporal dementia, the diagnosis rate was 63.0% (95% CI 48.7-75.7) and 60.0% (95% CI 43.3-75.1), respectively. Factors associated with having a registry diagnosis included dementia in the family, not being in the youngest or oldest age group, higher education, more severe cognitive decline, and greater need for help with activities of daily living. Conclusions: Undiagnosed dementia is common, as only one-third of those with dementia are diagnosed. Diagnoses appear to be made at a late stage of dementia.

Care trajectories around a first dementia diagnosis in patients with serious mental illness.

AIM: To develop a typology of care trajectories (CTs) 1 year before and after a first dementia diagnosis in individuals aged ≥65 years, with prevalent schizophrenia or bipolar disorder. METHODS: This was a longitudinal, retrospective cohort study using health administrative data (1996-2016) from Quebec (Canada). We selected patients aged ≥65 years with an incident diagnosis of dementia between 1 January 2014 and 31 December 2016, and a diagnosis of schizophrenia and/or or bipolar disorder. A CT typology was generated by a multidimensional state sequence analysis based on the "6 W" model of CTs. Three dimensions were considered: the care setting ("where"), the reason for consultation ("why") and the specialty of care providers ("which"). RESULTS: In total, 3868 patients were categorized into seven distinct types of CTs, with varying patterns of healthcare use and comorbidities. Healthcare use differed in terms of intensity, but also in its distribution around the diagnosis. For instance, whereas one group showed low healthcare use, healthcare use abruptly increased or decreased after the diagnosis in other groups, or was equally distributed. Other significant differences between CTs included mortality rates and use of long-term care after the diagnosis. Most patients (67%) received their first dementia diagnosis during hospitalization. CONCLUSIONS: Our innovative approach provides a unique insight into the complex healthcare patterns of people living with serious mental illness and dementia, and provides an avenue to support data-driven decision-making by highlighting fragility areas in allocating care resources. Geriatr Gerontol Int 2024; 24: 577-586.

High plasma homocysteine levels predict the progression from mild cognitive impairment to dementia.

High levels of blood homocysteine (HCy), a well-known cardiovascular risk factor and promoter of oxidative stress, have been associated with the incidence of cognitive impairment and dementia. Nonetheless, contrasting data are still present on its involvement in the progression from Mild Cognitive Impairment (MCI) to overt dementia. In this study we aimed to observe whether blood HCy level are associated with the evolution from MCI, divided into amnestic MCI (aMCI) and non-amnestic MCI (naMCI), to dementia. Blood HCy was measured in 311 MCI subjects (aMCI: 64%, naMCI: 36%) followed-up for a median of 33 months (range 10-155 months). At follow-up, 137 individuals converted to dementia (naMCI, n = 34; aMCI, n = 103). Based on HCy distribution, subjects in the highest tertile had a greater risk to convert to dementia compared to tertile I (Hazard Ratio (95% confidence interval): 2.25 (1.05-4.86); p = 0.04). aMCI subjects did not show increased risk to convert to dementia with increasing HCy concentration, but was significant in naMCI (p = 0.04). We observed a non-significant increase in the risk of progression to dementia from naMCI/low HCy (reference group, HCy cutoff value = 16 µmol/L) to naMCI/high HCy, but it was significant from aMCI/low HCy (HR: 2.73; 95%CI: 1.06-7.0; p:0.03), to aMCI/high HCy (HR: 3.24; 95%CI: 1.17-8.47; p:0.02). Our results suggest that HCy levels are associated with the progression from MCI to dementia. This association seems significant only for the naMCI group, indirectly supporting the notion that hyperhomocysteinemia damages the nervous system through its role as a vascular risk factor.

Predicting patients with dementia most at risk of needing psychiatric in-patient or enhanced community care using routinely collected clinical data: retrospective multi-site cohort study.

BACKGROUND: Dementia is a common and progressive condition whose prevalence is growing worldwide. It is challenging for healthcare systems to provide continuity in clinical services for all patients from diagnosis to death. AIMS: To test whether individuals who are most likely to need enhanced care later in the disease course can be identified at the point of diagnosis, thus allowing the targeted intervention. METHOD: We used clinical information collected routinely in de-identified electronic patient records from two UK National Health Service (NHS) trusts to identify at diagnosis which individuals were at increased risk of needing enhanced care (psychiatric in-patient or intensive (crisis) community care). RESULTS: We examined the records of a total of 25 326 patients with dementia. A minority (16% in the Cambridgeshire trust and 2.4% in the London trust) needed enhanced care. Patients who needed enhanced care differed from those who did not in age, cognitive test scores and Health of the Nation Outcome Scale scores. Logistic regression discriminated risk, with an area under the receiver operating characteristic curve (AUROC) of up to 0.78 after 1 year and 0.74 after 4 years. We were able to confirm the validity of the approach in two trusts that differed widely in the populations they serve. CONCLUSIONS: It is possible to identify, at the time of diagnosis of dementia, individuals most likely to need enhanced care later in the disease course. This permits the development of targeted clinical interventions for this high-risk group.

Using AI-Based Technologies to Help Nurses Detect Behavioral Disorders: Narrative Literature Review.

BACKGROUND: The behavioral and psychological symptoms of dementia (BPSD) are common among people with dementia and have multiple negative consequences. Artificial intelligence-based technologies (AITs) have the potential to help nurses in the early prodromal detection of BPSD. Despite significant recent interest in the topic and the increasing number of available appropriate devices, little information is available on using AITs to help nurses striving to detect BPSD early. OBJECTIVE: The aim of this study is to identify the number and characteristics of existing publications on introducing AITs to support nursing interventions to detect and manage BPSD early. METHODS: A literature review of publications in the PubMed database referring to AITs and dementia was conducted in September 2023. A detailed analysis sought to identify the characteristics of these publications. The results were reported using a narrative approach. RESULTS: A total of 25 publications from 14 countries were identified, with most describing prospective observational studies. We identified three categories of publications on using AITs and they are (1) predicting behaviors and the stages and progression of dementia, (2) screening and assessing clinical symptoms, and (3) managing dementia and BPSD. Most of the publications referred to managing dementia and BPSD. CONCLUSIONS: Despite growing interest, most AITs currently in use are designed to support psychosocial approaches to treating and caring for existing clinical signs of BPSD. AITs thus remain undertested and underused for the early and real-time detection of BPSD. They could, nevertheless, provide nurses with accurate, reliable systems for assessing, monitoring, planning, and supporting safe therapeutic interventions.

Cognitive Impairment in the Primary Care Clinic.

Cognitive impairment is a common problem in the geriatric population and is characterized by variable symptoms of memory difficulties, executive dysfunction, language or visuospatial problems, and behavioral changes. It is imperative that primary care clinicians recognize and differentiate the variable symptoms associated with cognitive impairment from changes attributable to normal aging or secondary to other medical conditions. A thorough evaluation for potentially reversible causes of dementia is required before diagnosis with a neurodegenerative dementia. Other abnormal neurologic findings, rapid progression, or early age of onset are red flags that merit referral to neurology for more specialized evaluation and treatment.

Non-linear relationship between serum cholesterol levels and cognitive change among older people in the preclinical and prodromal stages of dementia: a retrospective longitudinal study in Taiwan.

BACKGROUND: Adverse effects of rigorously lowering low-density lipoprotein cholesterol on cognition have been reported; therefore, we aimed to study the contribution of serum cholesterol in cognitive decline in older people with or without dementia. METHODS: Cognitive function was assessed by the Cognitive Abilities Screening Instrument (CASI). We investigated associations between serum cholesterol with cognitive decline using multiple regressions controlling for the effects of demographics, vascular risk factors, and treatments. RESULTS: Most associations between cholesterol and CASI scores could be explained by non-linear and inverted U-shaped relationships (R2 = 0.003-0.006, p < 0.016, Sidákcorrection). The relationships were most evident between changes in cholesterol and CASI scores in older people at the preclinical or prodromal stages of dementia (R2 = 0.02-0.064, p values < 0.016). There were no differences in level of changes in CASI scores between individuals in 1st decile and 10th decile groups of changes in cholesterol (p = 0.266-0.972). However, individuals in the 1st decile of triglyceride changes and with stable and normal cognitive functions showed significant improvement in CASI scores compared to those in the 10th decile (t(202) = 2.275, p values < 0.05). CONCLUSION: These findings could implicate that rigorously lowering cholesterol may not be suitable for the prevention of cognitive decline among older people, especially among individuals in preclinical or prodromal stages of dementia.

Alzheimer's Disease and Related Dementias in Muslim Women: Recommendations for Culturally Sensitive Care.

Alzheimer's disease and related dementias (ADRD) present significant challenges including cognitive and functional loss, behavioral disruption, emotional distress, and significant financial burden. These stressors are amplified in minority groups, who experience higher rates of ADRD but less frequent and later diagnosis. There is therefore a critical need to identify tangible approaches to culturally informed dementia assessment and care for patients from diverse communities. Muslim patients and particularly Muslim women are among the populations most understudied in the ADRD space. Muslim patients may hold unique religious, spiritual, and cultural beliefs and practices that can impact care-seeking for dementia symptoms, diagnostic accuracy, and treatment uptake. This paper outlines culturally informed approaches to assessing and treating Muslim women and families at each stage of ADRD care, though many recommendations extend to the broader Muslim community and others of diverse racial-ethnic backgrounds. We provide concrete suggestions for building rapport within and leveraging common family structures, respecting principles of modesty and privacy for all women including those who observe hijab or niqab, and communicating dementia diagnosis and care in the context of spiritual and ethical beliefs. While not intended as a comprehensive and prescriptive guide, this review provides important points of consideration and discussion with patients of Muslim backgrounds.

A multimodal machine learning model for predicting dementia conversion in Alzheimer's disease.

Alzheimer's disease (AD) accounts for 60-70% of the population with dementia. Mild cognitive impairment (MCI) is a diagnostic entity defined as an intermediate stage between subjective cognitive decline and dementia, and about 10-15% of people annually convert to AD. We aimed to investigate the most robust model and modality combination by combining multi-modality image features based on demographic characteristics in six machine learning models. A total of 196 subjects were enrolled from four hospitals and the Alzheimer's Disease Neuroimaging Initiative dataset. During the four-year follow-up period, 47 (24%) patients progressed from MCI to AD. Volumes of the regions of interest, white matter hyperintensity, and regional Standardized Uptake Value Ratio (SUVR) were analyzed using T1, T2-weighted-Fluid-Attenuated Inversion Recovery (T2-FLAIR) MRIs, and amyloid PET (αPET), along with automatically provided hippocampal occupancy scores (HOC) and Fazekas scales. As a result of testing the robustness of the model, the GBM model was the most stable, and in modality combination, model performance was further improved in the absence of T2-FLAIR image features. Our study predicts the probability of AD conversion in MCI patients, which is expected to be useful information for clinician's early diagnosis and treatment plan design.

Prevalence and risk factors for dementia and mild cognitive impairment among older people in Southeast China: a community-based study.

BACKGROUND: With the aging population, the number of individuals with dementia in China is increasing rapidly. This community-based study aimed to investigate the prevalence and risk factors for dementia and mild cognitive impairment (MCI) among older adults in China. METHODS: In this study, 20,070 individuals aged ≥ 65 were recruited between January 1, 2022, and February 1, 2023, from ten communities in Xiamen City, China. We collected data on age, sex, level of education, and medical history, as well as global cognition and functional status. The prevalence of dementia and MCI was examined, and the risk factors for different groups were assessed. RESULTS: The overall prevalence of dementia and MCI was approximately 5.4% (95% confidence interval [CI], 5.1-5.7) and 7.7% (95% CI, 7.4-8.1), respectively. The results also indicated that dementia and MCI share similar risk factors, including older age, female sex, hypertension, and diabetes mellitus. Compared with individuals with no formal education, those with > 6 years of education had an odds ratio for MCI of 1.83 (95% CI, 1.49-2.25). We also found that only 5.5% of the positive participants chose to be referred to the hospital for further diagnosis and treatment during follow-up visits. CONCLUSIONS: This study estimated the prevalence and risk factors for dementia and MCI among individuals aged ≥ 65 years in Southeast China. These findings are crucial for preventing and managing dementia and MCI in China.

Diagnostic and Prognostic Value of Plasma GFAP in Sporadic Creutzfeldt-Jakob Disease in the Clinical Setting of Rapidly Progressive Dementia.

The diagnostic and prognostic value of plasma glial fibrillary acidic protein (pl-GFAP) in sporadic Creutzfeldt-Jakob disease (sCJD) has never been assessed in the clinical setting of rapidly progressive dementia (RPD). Using commercially available immunoassays, we assayed the plasma levels of GFAP, tau (pl-tau), and neurofilament light chain (pl-NfL) and the CSF total tau (t-tau), 14-3-3, NfL, phospho-tau181 (p-tau), and amyloid-beta isoforms 42 (Aß42) and 40 (Aß40) in sCJD (n = 132) and non-prion RPD (np-RPD) (n = 94) patients, and healthy controls (HC) (n = 54). We also measured the CSF GFAP in 67 sCJD patients. Pl-GFAP was significantly elevated in the sCJD compared to the np-RPD and HC groups and affected by the sCJD subtype. Its diagnostic accuracy (area under the curve (AUC) 0.760) in discriminating sCJD from np-RPD was higher than the plasma and CSF NfL (AUCs of 0.596 and 0.663) but inferior to the 14-3-3, t-tau, and pl-tau (AUCs of 0.875, 0.918, and 0.805). Pl-GFAP showed no association with sCJD survival after adjusting for known prognostic factors. Additionally, pl-GFAP levels were associated with 14-3-3, pl-tau, and pl-NfL but not with CSF GFAP, Aß42/Aß40, and p-tau. The diagnostic and prognostic value of pl-GFAP is inferior to established neurodegeneration biomarkers. Nonetheless, pl-GFAP noninvasively detects neuroinflammation and neurodegeneration in sCJD, warranting potential applications in disease monitoring.