This study aimed to describe the clinical journey of patients with different stages of Alzheimer disease (AD). This was a cross-sectional survey of US primary care physicians (PCPs)/specialists and patients using the Adelphi Real World AD Disease Specific Programme™ (December 2022 - September 2023). Patients were stratified by disease severity and data are presented as the mean (SD) or frequencies/percentages. In the overall sample (N = 990), mean time from symptom onset to first evaluation was 31.4 (40.6) weeks and mean time from evaluation to diagnosis was 14.2 (29.0) weeks (mild cognitive impairment due to AD, 12.0 [22.7] weeks; mild AD dementia, 15.7 [31.6] weeks; moderate AD dementia, 14.0 [29.9] weeks; severe AD dementia, 5.1 [9.6] weeks). 74.5% of the overall sample was initially evaluated by their PCP and 13.8% by a neurologist. Patients with AD experience many barriers during the diagnostic journey; however, PCPs and neurologists play key roles in early diagnosis. Alzheimer disease (AD) is a main cause of dementia in older adults. Early diagnosis of AD is key, as it increases opportunities for treatment that may slow cognitive decline. However, underdiagnosis and diagnostic delays are common, particularly in the early stages of the disease. This study aimed to describe the clinical journey of patients with different stages of AD and to describe the diagnostic and monitoring tests used in these patients. This study also aimed to evaluate the role of primary care physicians (PCPs) and specialists in the diagnostic process. This study used survey data from the Adelphi Real World AD Disease Specific Programme™ between December 2022 and September 2023. The survey included data from US PCPs and specialists and their patients. Patient data was separated by disease severity into 4 categories: mild cognitive impairment due to AD (MCI due to AD), mild AD dementia (MAD), moderate AD dementia (MoAD), and severe AD dementia (SevAD). In the overall sample (N = 990), the average time from the beginning of symptoms to the first doctor’s appointment was 31.4 weeks, and the average time from the first doctor’s appointment to diagnosis was 14.2 weeks. The average time from the first doctor’s appointment to diagnosis was 12.0 weeks for patients with MCI due to AD, 15.7 weeks for MAD, 14.0 weeks for MoAD, and 5.1 weeks for SevAD. In the overall sample, 74.5% of patients were first evaluated by their PCP and 13.8% were first evaluated by a neurologist. Blood tests for AD-specific biomarkers were used to diagnose 9.0% of patients. This study found that PCPs and neurologists play an important role in diagnosing AD during early disease stages and that biomarker tests were not frequently used during diagnosis. In sum, patients with AD experience many barriers that may prevent quick diagnosis and potential treatment.
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.
The increasing incidence of Alzheimer's disease (AD) coupled with emerging diagnostics and treatments underscores the need for early detection of AD, yet identifying these individuals remains challenging. This US study sought to examine community-based physician attitudes regarding diagnosis and treatment of early AD (mild cognitive impairment [MCI] due to AD and mild AD). A total of 177 primary care physicians (PCPs) and 147 neurologists recruited through a national physician panel were surveyed about early AD diagnostic and treatment processes, and self-confidence in identifying and managing the condition. Physicians identified patient and family/caregiver involvement as critical in triggering the diagnostic process. Patterns of use of neurocognitive assessments, structural imaging tests, and AD-specific biomarkers varied between PCPs and neurologists. Confidence diagnosing and managing early AD was a concern across specialties, although was greater among PCPs. Programs promoting awareness of early AD symptoms, and emerging technologies and treatments are critical to timely management.
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.
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.
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.
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.
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.
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.
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.
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.
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.
ObjectiveTo assess external counterpulsation (ECP) effects on cognitive and functional decline in early AD.MethodsThis 12-month, multicenter, blinded, randomized, sham-controlled trial enrolled 190 patients with early AD (MCI due to AD or mild AD per NIA-AA clinical criteria). Participants received either full-pressure ECP (150-300 mmHg) or sham (25 mmHg): 3-5 weekly one-hour sessions for 35 treatments, then twice-weekly through six months. Assessments occurred at baseline and weeks 6, 12, 18, 24, 36, and 52. Primary endpoints included ADCS-ADL, ADAS-cog-14, and VADAS-cog.ResultsFull-pressure ECP significantly improved ADCS-ADL scores versus sham (mean change 2.57 vs. -0.49; p=0.036) and VADAS-cog scores (9.95 vs. 5.22; p=0.005) at 12-24 weeks. Benefits persisted through 52 weeks despite treatment cessation at 6 months. No serious device-related adverse events occurred.ConclusionsFull-pressure ECP therapy significantly improved cognition and ADL compared to sham treatment in early AD. ECP represents a novel therapeutic approach warranting further investigation.
This study examined the associations of activities of daily living (ADL) limitations and depressive symptoms with global and domain-specific cognition among older adults with chronic diseases. Data were drawn from the 2020 wave of the China Health and Retirement Longitudinal Study, including 5,112 participants aged ≥60 years. Functional ability and depressive symptoms were assessed using the ADL scale and CES-D-10, respectively. Cognitive function was assessed using CHARLS cognitive measures, including the Telephone Interview of Cognitive Status-10 and other cognition-related items. Spearman correlation and path analyses were performed using AMOS and Stata. ADL limitations were associated with poorer global and domain-specific cognitive function, and depressive symptoms accounted for part of these associations in the path models. The proportion accounted for by the indirect effect ranged from 17.39% for visuospatial ability to 60.27% for delayed recall. These findings suggest that functional status, depressive symptoms, and cognition are closely interrelated in this population.
Comprehensive cost measurement is essential for an effective policy response to societal dementia costs. Using dynamic microsimulation, the Health and Retirement Study, and other national data, we quantified the 2026 cost of dementia in the United States. In 2026, 5.7 million (95% confidence interval [CI] [5.6, 6.0]) US adults aged 51 and older are living with dementia, supported by 5.2 million (95% CI [4.9, 5.5]) care partners. Total costs are $818 billion (B, 95% CI [759, 866]), driven by quality-of-life losses for persons with dementia ($320B, 95% CI [269, 363]) and care partners ($15B 95% CI [6, 25]). Unpaid care ($237B, 95% CI [220, 253]), earnings losses ($23B), and out-of-pocket costs combined with quality-of-life losses account for 80% of costs and are borne by families. Governments cover 70% of healthcare costs ($222B, 95% CI [209, 237]). The costs of dementia fall on families, highlighting limited policy and work supports. Treatment innovation may increase medical costs but reduce caregiver burden and improve quality of life. The costs of dementia in the United States in 2026 are $818 billion. Quality-of-life losses are the largest driver of dementia's total burden. Individuals and families bear over three times the cost versus health systems. Methods enable analysis of treatment, care, and policy innovations on future costs.
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.