American journal of Alzheimer's disease and other dementias最新文献

Objective: To improve the identification of cognitive impairment by distinguishing normal cognition (NC), mild cognitive impairment (MCI), and Alzheimer's disease (AD). Methods: A recursive partitioning tree model was developed using ARMADA data and the NIH Toolbox, a multidimensional health assessment tool. It incorporated demographic and clinical assessment variables to predict NC, MCI, and AD. Model performance was evaluated using AUC, precision, recall, and F1 score. Robustness was tested through 5-fold cross-validation, sensitivity, scenario, and subgroup analyses. Results: The model achieved macro-AUC and micro-AUC scores of 0.92 and 0.91 (training) and 0.89 and 0.86 (testing). Key predictors included the Picture Sequence Memory Test and List Sorting Working Memory Test. Cross-validation yielded 70.22% accuracy and a Kappa of 0.52. Conclusion: Machine learning effectively uses a small set of assessments to distinguish NC, MCI, and AD, offering a valuable tool to support clinical decision-making. Future research should validate this model across diverse populations.

White matter hyperintensity (WMH) is associated with cognitive impairment. In this study, 79 patients with WMH from hospital 1 were randomly divided into a training set (62 patients) and an internal validation set (17 patients). In addition, 29 WMH patients from hospital 2 were used as an external validation set. Cognitive status was determined based on neuropsychological assessment results. A deep learning convolutional neural network of VB-Nets was used to automatically identify and segment whole-brain subregions and WMH. The PyRadiomics package in Python was used to automatically extract radiomic features from the WMH and bilateral hippocampi. Delong tests revealed that the random forest model based on combined features had the best performance for the detection of cognitive impairment in WMH patients, with an AUC of 0.900 in the external validation set. Our results provide clinical doctors with a reliable tool for the early diagnosis of cognitive impairment in WMH patients.

Narrow definitions of family can constrain survey items about obligations regarding who should care for older adults. Current measurement often does not account for the increased prevalence of diverse family forms and support received among older adults. We draw on six focus groups (N = 33) of family or friends caring for older adults with trouble remembering, memory issues, or dementia to explore definitions of family, caregiving, and responsibility. Although many caregivers immediately default to traditional definitions, the breadth of "family" seen as responsible and actual care networks are often broader. In many cases, caregivers considered friends and other non-kin as family because they provided care. Furthermore, both care and obligations are shaped by family dynamics and the older adult's memory loss. Results suggest that survey measures should capture a wider range of relationship ties and dynamics to better understand family, caregiving obligations, and the tensions between them.

Foreign-born people living with cognitive impairment (PLwCI) and their family caregivers may have distinct caregiving networks compared to their U.S.-born counterparts. Data is drawn from the 2022 wave of the National Health and Aging Trends Study. Descriptive statistics and mean difference tests were run by native and foreign-born PLwCI. Linear and logistic regressions were run controlling for foreign-born PLwCI demographics with categorized time in the U.S. as the predictor of network characteristics. Foreign-born PLwCI networks were more likely to have a daughter caregiver and engage in household task-sharing, but less likely to have a spouse and non-family caregiver. In adjusted regressions, residing in the U.S. for less than 30 years was associated with greater odds of having a daughter and generalist in network, and greater task-sharing in household and self-care/mobility domains, relative to those residing over 50 years. Results underscore the importance of acculturation in shaping care networks among PLwCI.

Alzheimer's disease (AD) presents a pressing global health challenge, with amyloid-β (Aβ) accumulation in the brain being a hallmark feature. While monoclonal antibodies targeting Aβ have shown cognitive benefits, safety concerns remain. Here, we introduce the Amytrapper catheter, a novel extracorporeal device developed by Recombinant Technologies to trap circulating Aβ using a retro-inverso peptide conjugated to polyethylene glycol. Through in vivo experiments using a rat model of AD, we demonstrate significant reductions in blood Aβ levels and behavioral improvements following Amytrapper catheter treatment. This innovative approach holds promise as a disease-modifying therapy for AD, offering a complementary strategy to existing treatments and advocating for further clinical development.

Using LGBTQ+ Social Networks, Aging, and Policy Study Wave 3 data (N = 982), this study examines how caregiving for individuals with mild cognitive impairment, Alzheimer's disease, and related dementias (MCI/ADRD) impacts everyday stressors, discrimination, and health outcomes among LGBTQ+ older adults in the Southern United States. Using chi-square tests, Fisher's exact tests, and logistic regression models, we assessed associations of caregiver role with stress and health outcomes. We then conducted moderation analyses to test interactions between caregiver role and LGBTQ+ minority stress. LGBTQ+ caregivers of individuals with MCI/ADRD were 3 times more likely to experience proximal minority stress (P < 0.05), twice as likely to report suicidal ideation (P < 0.1), and more likely to report cognitive problems (P < 0.05) and high blood pressure (P < 0.05) than non-caregivers. Interaction effects suggest that minority stress may exacerbate mental health problems among MCI/ADRD caregivers. Findings underscore the need for targeted supports and interventions for LGBTQ+ older adult dementia caregivers.

A growing body of literature has examined the impact of neighborhood characteristics on Alzheimer's disease (AD) dementia, yet the spatial variability and relative importance of the most influential factors remain underexplored. We compiled various widely recognized factors to examine spatial heterogeneity and associations with AD dementia prevalence via geographically weighted random forest (GWRF) approach. The GWRF outperformed conventional models with an out-of-bag R² of 74.8% in predicting AD dementia prevalence and the lowest error (MAE = 0.34, RMSE = 0.45). Key findings showed that mobile homes were the most influential factor in 19.9% of U.S. counties, followed by NDVI (17.4%), physical inactivity (12.9%), households with no vehicle (11.3%), and particulate matter (10.4%), while other primary factors affecting <10% of U.S. counties. Findings highlight the need for county-specific interventions tailored to local risk factors. Policies should prioritize increasing affordable housing stability, expanding green spaces, improving transportation access, promoting physical activity, and reducing air pollution exposure.

Parkinson's disease (PD) is characterized by degeneration of dopaminergic neurons in the substantia nigra (SN), leading to motor impairments, while hippocampal dysfunction contributes to memory deficits. Botulinum neurotoxin (BoNT), a therapeutic modulator of acetylcholine (ACh) release, its cognitive effects remain underexplored. We investigated the effect of BoNT on spatial learning, memory, microglia and hippocampal neurogenesis in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model of PD. Behavioral tests, including the open field, novel object recognition, and Morris water maze, demonstrated significant improvements in locomotion, learning, and memory with BoNT treatment. BoNT increased the number of doublecortin (DCX)-positive immature neurons and percentage of bromodeoxyuridine (BrdU)/neuronal nuclei (NeuN) double-positive cells, while the reduced number of microglia was evident in the hippocampal dentate gyrus (DG). Additionally, histological analyses revealed BoNT-mediated protection of pyramidal neurons in hippocampal cornu ammonis (CA)-1 and CA3 regions. These findings suggest that BoNT mitigates memory deficits by promoting neurogenesis in experimental PD.

Dementia affects over 55 million people worldwide, with more than 11 million informal caregivers providing care. Caregivers experience physical, psychological, and social stresses, making it crucial to understand their caregiving experience. This study assessed whether the caregivers' perceived choice to provide care and recognition of dementia symptoms influenced their caregiving experiences. A secondary cross-sectional analysis was conducted using data from the National Alliance for Caregiving, including 927 caregivers. Caregiving experience was measured on a 5-point Likert scale. Chi-square tests and ordinal logistic regression were used. Caregivers who perceived they had a choice to provide care were significantly more likely to report positive experiences (ARR = 1.39, P ≤ .001). Recognition of dementia symptoms was not significantly associated with caregiving experience. However, the combination of perceived choice and recognition of dementia symptoms, particularly from one event, was associated with the most positive caregiving experiences. Findings suggest the need for caregiver choice-support and dementia education programs.

Background: The role of parity in predicting dementia risk in women is debated. This study examines how birth rate affects global dementia incidence.

Methods: Country-specific data on birth rate and dementia incidence rate were analyzed using bivariate analysis, partial correlation, and multiple linear regression. Confounding factors such as aging, affluence, genetic predisposition (I_bs), and urbanization were considered.

Results: Pearson's r and nonparametric analyzes showed a significant inverse correlation between birth rate and dementia incidence. This relationship remained significant after controlling for aging, affluence, I_bs, and urbanization. Multiple linear regression identified birth rate as a significant predictor of dementia incidence, and as the strongest predictor. Affluence and urbanization were not significant predictors. The correlation was stronger in developing countries.

Conclusions: Lower birth rate is an independent risk factor for dementia, particularly in developed countries. These findings highlight the importance of considering birth rate in dementia studies.