搜索结果：American journal of Alzheimer's disease and other dementias

Blood-based biomarkers offer a widely available, scalable, and noninvasive method to study neurodegeneration. However, the association between blood-based biomarkers of neurodegeneration and long-term risk of mortality, as well as dementia-specific mortality in a racially diverse cohort, remains understudied. The goal of this study was to determine whether baseline biomarkers of neurodegeneration are associated with long-term risk of all-cause and dementia-specific mortality in a biracial cohort. The REasons for Geographic and Racial Differences in Stroke cohort study enrolled 30,239 Black and White participants across the continental United States from 2003 to 2007, with ongoing follow-up. Plasma neurofilament light chain (NfL), total tau, glial fibrillary acidic protein (GFAP), and ubiquitin carboxy-terminal hydrolase L1 (UCH-L1) were measured in baseline plasma from a random sample of participants. All-cause mortality, dementia-specific mortality, cardiovascular-specific mortality, and other causes of death were adjudicated and classified using medical records, the Social Security Death Index, and the National Death Index. Cause-specific Cox regression models accounting for competing risks were used to calculate hazard ratios (HRs) of outcomes for each biomarker separately. A total of 917 participants had a mean baseline age of 67.4 years (SD 12.1), 49.4% were female, and 48.6% self-identified as Black. With a mean follow-up of 11.1 (SD 5.7) years, 51.0% (477/935) of participants died and 9.2% experienced dementia-specific mortality (86/935). No associations were observed for total tau. In fully adjusted models for other biomarkers, HRs of all-cause mortality per standard deviation increments were 1.93 (95% CI 1.48-2.52) for GFAP, 1.90 (95% CI 1.55-2.32) for NfL, and 1.23 (95% CI 1.09-1.37) for UCH-L1. Furthermore, GFAP (HR 5.66, 95% CI 2.91-11.00) and NfL (HR 2.72, 95% CI 1.57-4.71) were associated with dementia-specific mortality in fully adjusted models. GFAP (HR 2.06, 95% CI 1.22-3.49) and NfL (HR 2.16, 95% CI 1.66-2.81) were also associated with cardiovascular-specific mortality in fully adjusted models. Plasma biomarkers of neurodegeneration, particularly GFAP and NfL, were associated with increased risk of all-cause, dementia-specific, and cardiovascular-specific mortality in a biracial cohort. These associations should be considered when assessing links between these biomarkers and other outcomes, as well as when used in clinical practice.

Caring for a family member living with dementia is costly. A major contributor to care demands, and therefore to the costs, are the behavioral symptoms of dementia. Here, we examine the feasibility of ascertaining costs related to caregiving from weekly web-based surveys collected during a telehealth-based behavioral intervention study-Support via Technology: Living and Learning with Advancing Alzheimer Disease. This study aims to determine the feasibility and acceptability of using a web-based weekly survey to capture real-time data on out-of-pocket caregiving expenses and time commitments associated with dementia care. To examine relationships between behavioral symptoms, care partner reactivity, burden, and out-of-pocket dementia care costs. Feasibility was measured by accrual, retention, and data completion by participating care partners. Behavioral symptoms, care partner reactivity, and burden were collected before and after the intervention from 13 care partners. Weekly web-based surveys queried Support via Technology: Living and Learning with Advancing Alzheimer Disease care partners about their out-of-pocket costs associated with care-related activities. The surveys included questions on out-of-pocket costs care partners incurred from hospitalizations and emergency department use, primary care provider visits, use of paid in-home care or respite services, use of prescription medications, and use of over-the-counter medications. The surveys also queried the amount of time care partners devoted to these specific care-related activities. Out-of-pocket costs of dementia care were collected via a web-based weekly survey for up to 18 months. In-home assistance was the most frequently reported type of out-of-pocket care expense and the costliest. care partners who paid for in-home assistance or respite reported more behavioral and psychological symptoms of dementia behaviors, higher reactivity, and higher burden than those who did not. This novel web-based weekly survey-based approach offers lessons for designing and implementing future cost-focused studies and care partner-supportive telehealth-based interventions for Alzheimer disease and related dementias (ADRD). The results correspond with the existing understanding of ADRD in that high family-related out-of-pocket costs are a typical part of the caregiving experience, and those costs likely increase with dementia severity. The results may also offer potential insights to health systems and policy makers as they seek to implement telehealth-based and related interventions that seek to better support people living with ADRD and their family care partners. ClinicalTrials.gov NCT04335110; https://clinicaltrials.gov/ct2/show/NCT04335110.

We aimed to explore the value and interpretability of a multimodal deep learning model integrating optical coherence tomography angiography (OCTA) and electronystagmography (ENG) for the early screening of Alzheimer's disease (AD) and mild cognitive impairment (MCI). A total of 250 subjects were retrospectively recruited. OCTA images, ENG signals and neurocognitive scores were collected from all subjects. The model had an area under curve of 0.85 for the independent validation cohort, with the sensitivity and specificity of 0.73 and 0.90 at the optimal cut-off of receiver operating characteristic curve, respectively. According to Gradient-weighted Class Activation Mapping analysis, the model focused on regions with reduced microvascular density. SHapley Additive exPlanations analysis revealed that saccade accuracy (left eye), saccade latency (right eye) and smooth pursuit gain (left eye) contributed the most to the model. The multimodal model effectively improves early, non-invasive screening of AD/MCI with good interpretability.

Religiosity and spirituality (R/S) encompass organizational activity, private practice, and intrinsic beliefs, which may relate differently to cognitive and mental health outcomes in older adults. This study identified latent R/S profiles among South Korean older adults with mild cognitive impairment (MCI) and Alzheimer's disease (AD), and examined differences in cognitive function, psychological well-being, and depressive symptoms. Latent profile analysis using Duke University Religion Index indicators was conducted with 518 patients (MCI: n = 224; AD: n = 294). In MCI, three classes that differed in well-being and verbal fluency were identified; they showed no differences in depressive symptoms or other cognitive domains. In AD, four classes were identified that differed in the Short Blessed Test and Word List Recall; in these, well-being, depression, and other cognitive outcomes did not differ across classes. These findings underscore the relevance of diverse R/S patterns in individualized care for older adults with neurocognitive disorders.

Subarachnoid hemorrhage (SAH) has been reported to cause glial scarring within a short timeframe. Due to the high mortality rate of SAH, there is limited research on its long-term effects and relation to neurodegenerative disorders. This report aims to investigate a combination of healed SAH and Alzheimer's Disease (AD) pathology. A 90-year-old female cadaver, in the anatomy laboratory, was found to have an irregular surgical scar in the right frontoparietal bone. Upon dissection, the right frontal lobe was discovered to be atrophic with a concavity. Histopathology exhibited significant gliosis and corpora amylacea (CA). The cause of death was AD, and past medical history revealed an aneurysmal SAH during childbirth 60 years ago. CA and gliosis are common findings in aging, ischemia, and AD. These findings contribute to the knowledge of the long-term effects of SAH and necessitate further research on the pathogenesis of AD in relation to cerebral ischemia.

Objective: Alzheimer's disease (AD) continues to be a major challenge because handling high-dimensional data is time-consuming and expensive due to its complexity. A large feature space often increases computational costs and reduces model interpretability. This study addresses this problem by evaluating and comparing multiple feature selection techniques to identify the most informative biomarkers for AD diagnosis.Methods: Our study used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) to implement and test three feature selection approaches, visualization-based, filter-based, and wrapper-based, within a Naive Bayes (NB) classification framework.Results: Based on the results of the analysis, the wrapper method achieved 96.77% classification accuracy, outperforming both visualization and filter methods with 86.19 and 91.87%, respectively. Interestingly, even when over 92.5% of the original features were removed the classifier still performed well, indicating that only a small set of features is necessary to ensure reliable diagnosis.Discussion: This study illustrates that strategically selecting features improves diagnostic accuracy while reducing computational burden, providing a more efficient framework for machine learning applications in Alzheimer's disease research.

Social and structural determinants of health (SSDoH) have been linked to racial disparities in Alzheimer's disease and related dementias (ADRD). Research has established that living in an environment with greater economic stability (ES) or healthcare access (HCA) is associated with better baseline cognition, but the interactive effects between these distinct SSDoH on cognition over time have not been studied. Therefore, the present study examined the independent and interactive effects of ES and HCA on 10-year change in cognitive functioning within a large sample of racially diverse community-dwelling older adults. Participants included 701 Black/African American and 1804 White older adults from the Advanced Cognitive Training for Independent and Vital Elderly study. Multilevel mixed effects models were used to assess associations between ES and HCA factors on individual-level memory and reasoning trajectories. Results revealed there was no significant ES × HCA interaction on longitudinal cognitive trajectories across the whole sample or within race-stratified groups, but there was a significant interaction on memory level. Higher ES levels were independently associated with slower age-related memory declines among Black/African American older adults. In contrast, higher ES and HCA levels were both independently associated with faster age-related reasoning declines among White participants. Results demonstrated that ES and HCA exerted synergistic effects on memory level across ages in the whole sample. Differential associations between SSDoH and cognitive outcomes across racial groups suggest that improving access to economic resources within Black/African American communities may reduce racial disparities in ADRD.

This review examines the application of olfactory testing in the early stages of mild cognitive impairment (MCI) associated with Alzheimer's disease (AD), highlighting its potential and challenges in early screening and intervention. Olfactory function is typically divided into three domains: odor identification, odor discrimination, and odor threshold. Among these, odor identification and discrimination are closely linked to higher cognitive processes and exhibit significant impairment in patients with AD and MCI. Moreover, the anatomical and functional characteristics of the olfactory system make it a promising target for the early detection of neurodegenerative disorders. This review also outlines various olfactory assessment tools and evaluates their clinical utility. Future research should aim to enhance the accuracy and cultural adaptability of olfactory tests and integrate them with multimodal diagnostic approaches to advance early detection and intervention strategies for AD.

Alzheimer's disease (AD) is the most common cause of dementia. Epileptic seizures or epileptic activity have been detected in AD, and people with epilepsy have a higher risk of dementia compared to the general population. This suggests that seizures or epileptic activity might often coexist with AD. It is increasingly evident that epileptic activity or seizures are common but often overlooked comorbidities of AD. However, the causal relationship between seizures, epileptic activity and cognitive decline remains uncertain. Experimental data show that amyloid-β (Aβ) and Tau protein can cause neuronal hyperexcitability and has epileptogenic effects. Neural network hyperexcitation regulates the ratio of Aβ isoforms and is linked to the initiation of AD, indicating a shared mechanism. Clinical studies suggest that cognitive impairment accelerates in AD patients with seizures or epileptic activity. This review discusses the relationship between epileptic seizures and AD, the impact of epileptic activity in AD, and potential treatments.

Triggering receptor expressed on myeloid cells 2 (TREM2) is upregulated in activated microglia and may be related to cognitive decline in patients with Alzheimer's disease (AD). There is conflicting evidence regarding the association of peripheral TREM2 mRNA expression/soluble TREM2 (the extracellular domain of TREM2) with cognitive function/neuroinflammation in patients with AD. Herein, we studied the TREM2 and TREM2alt mRNA expression and their association with the cognitive performance in subjects with mild dementia due to AD and healthy controls. In a subgroup of patients with AD, magnetic resonance spectroscopy was used to measure the myo-inositol level in the posterior cingulate cortex, a surrogate marker for neuroinflammation. The results showed that increased TREM2 and TREM2alt mRNA expression is associated with AD pathogenesis at the mild dementia stage, thereby serving as a potential biomarker for early symptomatic stage of AD. TREM2 may exert protective effects on both cognition and central neuroinflammation.

Handwriting is a preferred identifier in detecting Alzheimer's disease that enables diagnosis about people. The aim of this study is to evaluate the handwriting and make the early detection and diagnosis of Alzheimer's disease with the highest possible prediction rates. In this regard, 9 machine learning algorithms were used. Seven feature selection methods were used to determine the most effective features for Alzheimer's disease prediction to eliminate unnecessary ones and increase model prediction performance. The models were trained and tested on the DARWIN dataset with both train - test split and cross-validation methods. According to the results, it has been evaluated that the highest performance criterion values are generally achieved when the SHAP is used as the feature selection method. According to the results, the appropriate model that achieved the highest performance values was determined as the hybrid SHAP-Support Vector Machine model with 0.9623 accuracy, 0.9643 precision, 0.9630 recall and 0.9636 F1-Score.

Multimodal non-pharmacological interventions (MNPI) have been determined as effective in delaying cognitive deterioration. The effectiveness of timing of such interventions in elderly is less discussed. We compared the different effectiveness of MNPI in cognitive preservation in elderly subjects with and without dementia. We enrolled volunteer the elderly subjects. Subjects were classified as dementia group and non-dementia group by instrument of ascertainment of dementia 8. All were assigned to attend 3 hours of MNPI (physical fitness training, Chinese capillary, and Chinese drawings and paintings) twice a week over a 16-week period. Neuropsychiatric tests, including Mini-Mental State Examination (MMSE), Cognitive Assessment Screening Instrument (CASI), clinical dementia rating (CDR), and neuropsychiatric inventory (NPI), were administered before and 1 year after MNPI. We demonstrated the changes of cognition and behavioral and psychological symptoms of dementia (BPSD) before and after MNPI. We compared the different effectiveness of cognition preservation between two groups. In total, there were 43 participants in our study, including 18 with non-dementia and 25 with dementia. The non-dementia group had a significantly higher proportion of cognitive preservation in remote memory (100.0% vs 68.0%, P = .007), orientation (94.4% vs 48.0%, P = .001), drawing (94.4% vs 64.0%, P = .021) and language (77.8% vs 48.0%, P = .049) than the dementia group. The highest proportion of preserved cognition after MNPI was remote memory (100%), followed by orientation (94.4%) and drawing (94.4%) in the non-dementia group. The highest proportion of preserved cognition after MNPI was attention (72%) followed by remote memory (68%), recent memory (64%) and drawing (64%) in the dementia group. Overall, their improved rate in behavioral and psychological symptoms was 55.6%. Our study concluded the benefits of early MNPI in cognition preservation in the elderly, especially in the field of remote memory, orientation, drawing and language.

Neuropsychological test batteries, which accurately and comprehensively assess cognitive functions, are a crucial approach in the early detection of and interventions for cognitive impairments. However, these tests have yet to gain wide clinical application in China owing to their complexity and time-consuming nature. This study aimed to develop the Computerized Neurocognitive Battery for Chinese-Speaking participants (CNBC), an autorun and autoscoring cognitive assessment tool to provide efficient and accurate cognitive evaluations for Chinese-Speaking individuals. The CNBC was developed through collaboration between clinical neurologists and software engineers. Qualified volunteers were recruited to complete CNBC and traditional neurocognitive batteries. The reliability and validity of the CNBC were evaluated by analyzing the correlations between the measurements obtained from the computerized and the paper-based assessment and those between software-based scoring and manual scoring. The CNBC included 4 subtests and an autorun version. Eighty-six volunteers aged 51-82 years with 7-22 years of education were included. Significant correlations (0.256-0.666) were observed between paired measures associated with attention, executive function, and episodic memory from the CNBC and the traditional paper-based neurocognitive batteries. This suggests a strong construct validity of the CNBC in assessing these cognitive domains. Furthermore, the correlation coefficients between manual scoring and system scoring ranged from 0.904-1.0, indicating excellent inter-rater reliability for the CNBC. A novel CNBC equipped with automated testing and scoring features was developed in this study. The preliminary results confirm its strong reliability and validity, indicating its promising potential for clinical utilization.

The staff working at day-care centers and nursing homes are in a key frontline for early detection of older people living with dementia, however, whether the staff were well prepared and if they were appropriately trained were still little known. A cross-sectional survey was conducted and the validated questionnaires exploring the awareness of dementia care, in terms of knowledge, attitude and preventive practice domain, were given to the staff working at day-care centers and nursing homes in Macao. 272 samples were approached and scores of knowledge was 76.23 ± 19.62, attitude was 80.05 ± 8.92 and preventive practice was 75.59 ± 13.88, among which knowledge and preventive practice were positively related to attitude, and knowledge, attitude and preventive practice were negatively related to age. Health care assistants' knowledge were less than social workers, managers, health professionals and clerk. Attitude of health care assistants were less positive than social workers and health professionals. Health care assistants and older staff had less knowledge and less positive attitude. Trainings to improve knowledge, attitude and preventive practice amongst health care assistants and older staff were recommended strongly.

Several risk factors contribute to the development of Alzheimer's disease (AD), including genetics, metabolic health, cardiovascular history, and diet. It has been observed that women appear to face a higher risk of developing AD. Among the various hypotheses surrounding the gender disparity in AD, one pertains to the potential neuroprotective properties of estrogen. Compared to men, women are believed to be more susceptible to neuropathology due to the significant decline in circulating estrogen levels following menopause. Studies have shown, however, that estrogen replacement therapies in post-menopausal women do not consistently reduce the risk of AD. While menopause and estrogen levels are potential factors in the elevated incidence rates of AD among women, this review highlights the possible roles estrogen has in other pathways that may also contribute to the sex disparity observed in AD such as olfaction, sleep, and glymphatic functionality.

Understanding the clinical utility of patient-reported outcome measures is critical for using these measures in research and clinical practice. Therefore, the purpose of this analysis was to establish the psychometric properties of three TBI-CareQOL measures in caregivers of people living with Alzheimer's disease or Alzheimer's disease-related dementias (ADRD): Caregiver Strain, Caregiver-Specific Anxiety, and Feeling Trapped. One-hundred-and-ninety-seven caregivers of individuals living with ADRD (n=197) completed three TBI-CareQOL measures, three additional measures to establish convergent and discriminant validity (NIH Toolbox Perceived Stress, Dementia Management Strategies Scale, PROMIS Pain Intensity), and the Dementia Severity Rating Scale to establish known groups validity. Internal consistency and test-retest reliability of the TBI-CareQOL measures were supported (alphas >.70). The TBI-CareQOL measures were also free of floor and ceiling effects. Convergent, discriminant, and known groups validity were also supported. Taken together, findings support the clinical utility of the TBI-CareQOL measures for caregivers of people living with ADRD.

The study aims to identify psychological symptoms (depression and anxiety) and their relationship to the quality of life among dementia patients' caregivers, and whether there are differences in the level of each of them due to the gender variable. The study follows the correlational approach, with a sample of 174 dementia patients' caregivers. To pursue the analysis, the study uses 3 measurement tools: anxiety, depression, and quality of life. The results show that the level of depression, anxiety, and quality of life among dementia patients' caregivers is moderate. It also finds that there is a positive relationship between anxiety and depression, and there is a negative relationship between quality of life and anxiety and depression. There are no differences in the level of depression and anxiety due to gender, as the study finds female caregivers to have a higher level of quality of life.

Timely detection of dementia is crucial for reducing its health and societal burden. Standard tools such as the Mini-Mental State Examination (MMSE) and Cognitive Abilities Screening Instrument (CASI), although widely used, are limited by time and resource demands. This study developed and validated a machine learning-based screening tool using the Six-Question Dementia Screening Test (6Q-DS), a brief interview of six items. Data from 533 older adults at a neurology clinic in Taiwan (331 with dementia, 202 without) were analyzed with eXtreme Gradient Boosting. The 6Q-DS achieved an AUC of 0.936, sensitivity 0.879, specificity 0.951, and accuracy 0.907 for dementia vs non-dementia. For identifying very mild dementia vs non-dementia, the AUC was 0.874, with a sensitivity of 0.818, specificity of 0.805, and accuracy of 0.810. Comparable to MMSE and CASI, the 6Q-DS provides a practical, rapid, and user-friendly tool for dementia screening.

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.