RESUMEN
Introduction: Alzheimer's disease and related disorders (ADRD) progressively impair cognitive function, prompting the need for early detection to mitigate its impact. Mild Cognitive Impairment (MCI) may signal an early cognitive decline due to ADRD. Thus, developing an accessible, non-invasive method for detecting MCI is vital for initiating early interventions to prevent severe cognitive deterioration. Methods: This study explores the utility of analyzing gait patterns, a fundamental aspect of human motor behavior, on straight and oval paths for diagnosing MCI. Using a Kinect v.2 camera, we recorded the movements of 25 body joints from 25 individuals with MCI and 30 healthy older adults (HC). Signal processing, descriptive statistical analysis, and machine learning techniques were employed to analyze the skeletal gait data in both walking conditions. Results and discussion: The study demonstrated that both straight and oval walking patterns provide valuable insights for MCI detection, with a notable increase in identifiable gait features in the more complex oval walking test. The Random Forest model excelled among various algorithms, achieving an 85.50% accuracy and an 83.9% F-score in detecting MCI during oval walking tests. This research introduces a cost-effective, Kinect-based method that integrates gait analysis-a key behavioral pattern-with machine learning, offering a practical tool for MCI screening in both clinical and home environments.
RESUMEN
BACKGROUND AND OBJECTIVES: The clinical diagnosis of dementia with Lewy bodies (DLB) depends on identifying significant cognitive decline accompanied by core features of parkinsonism, visual hallucinations, cognitive fluctuations, and REM sleep behavior disorder (RBD). Hyposmia is one of the several supportive features. α-Synuclein seeding amplification assays (αSyn-SAAs) may enhance diagnostic accuracy by detecting pathologic αSyn seeds in CSF. In this study, we examine how different clinical features associate with CSF αSyn-SAA positivity in a large group of clinically diagnosed participants with DLB. METHODS: Cross-sectional and longitudinal CSF samples from the multicentered observational cohort study of the DLB Consortium and similar studies within the Parkinson's Disease Biomarker Program, contributed by academic medical centers in the United States, underwent αSyn-SAA testing. Participants included those clinically diagnosed with DLB and 2 control cohorts. Associations between core DLB features and olfaction with αSyn-SAA positivity were evaluated using logistic regression. RESULTS: CSF samples from 191 participants diagnosed with DLB (mean age 69.9 ± 6.8, 15% female), 50 age-matched and sex-matched clinical control participants, and 49 younger analytical control participants were analyzed. Seventy-two percent (137/191) of participants with DLB had positive αSyn-SAAs vs 4% of the control groups. Among participants with DLB, those who were αSyn-SAA-positive had lower Montreal Cognitive Assessment scores (18.8 ± 5.7 vs 21.2 ± 5.2, p = 0.01), had worse parkinsonism on the Movement Disorders Society Unified Parkinson's Disease Rating Scale part III (33.8 ± 15.1 vs 25.6 ± 16.4, p = 0.001), were more likely to report RBD (114/133 [86%] vs 33/53 [62%], p < 0.0001), and had worse hyposmia on the University of Pennsylvania Smell Identification Test (UPSIT) (94/105 [90%] below 15th percentile vs 14/44 [32%], p < 0.0001). UPSIT percentile had the highest area under the curve (0.87, 95% CI 0.81-0.94) in predicting αSyn-SAA positivity and participants scoring at or below the 15th percentile of age and sex normative values had 18.3 times higher odds (95% CI 7.52-44.6) of having a positive αSyn-SAA test. Among 82 participants with longitudinal CSF samples, 81 (99%) had the same αSyn-SAA result for initial and follow-up specimens. DISCUSSION: A substantial proportion of clinically diagnosed participants with DLB had negative αSyn-SAA results. Hyposmia was the strongest clinical predictor of αSyn-SAA positivity. Hyposmia and αSyn-SAA may have utility in improving the diagnostic assessment of individuals with potential DLB. CLASSIFICATION OF EVIDENCE: This study provided Class III evidence that CSF αSyn-SAA distinguishes patients with clinically diagnosed DLB from normal controls.
Asunto(s)
Enfermedad por Cuerpos de Lewy , alfa-Sinucleína , Humanos , Enfermedad por Cuerpos de Lewy/líquido cefalorraquídeo , Enfermedad por Cuerpos de Lewy/diagnóstico , Femenino , Anciano , Masculino , alfa-Sinucleína/líquido cefalorraquídeo , Persona de Mediana Edad , Estudios Transversales , Estudios Longitudinales , Biomarcadores/líquido cefalorraquídeo , Estudios de Cohortes , Anciano de 80 o más AñosRESUMEN
Background: Detecting cognitive impairment in clinical practice is challenging as most instruments do not perform well in diverse samples of older adults. These same instruments are often used for eligibility into clinical trials making it difficult to recruit minoritized adults into Alzheimer's disease (AD) studies. Cognivue Clarity® is an FDA-cleared computerized 10-minute cognitive screening platform using adaptive psychophysics to detect cognitive impairment. Objective: Test the ability of Cognivue Clarity to measure cognitive performance in a diverse community sample compared with the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Methods: This study enrolled 452 participants across 6 US study sites and completed both Cognivue Clarity device and RBANS. Psychometric properties and exploratory factor analysis of Cognivue Clarity were explored and comparisons against RBANS across different age, sex, education, and ethnoracial groups were conducted. Results: Participants had a mean age of 47.9±16.1 years (range: 18-85), 63.6% were female, 45.9% had ≤12 years of education, 31.2% were African American and 9.2% were Hispanic. Cognivue Clarity had strong internal consistency, test-retest reliability and minimal practice effects. A 4-factor structure (Memory, Attention, Visuomotor, and Discrimination) had excellent goodness-of-fit. Normalizing age effects improved performance. Race and education effects were similar to those seen with RBANS. Cognivue Clarity had strong correlations with RBANS. Conclusions: Our study supports the use of Cognivue Clarity as an easy-to-use, brief, and valid cognitive assessment that measures cognitive performance. In the correct clinical setting, Cognivue Clarity may identify individuals with likely cognitive impairment who could be candidates for AD research studies.
Asunto(s)
Disfunción Cognitiva , Pruebas Neuropsicológicas , Psicometría , Humanos , Femenino , Masculino , Psicometría/métodos , Anciano , Persona de Mediana Edad , Adulto , Anciano de 80 o más Años , Pruebas Neuropsicológicas/normas , Pruebas Neuropsicológicas/estadística & datos numéricos , Disfunción Cognitiva/diagnóstico , Disfunción Cognitiva/psicología , Adulto Joven , Adolescente , Reproducibilidad de los Resultados , Valores de ReferenciaRESUMEN
Background: Diagnosing Dementia with Lewy Bodies (DLB) remains a challenge in clinical practice. The use of 123I-ioflupane (DaTscan™) SPECT imaging, which detects reduced dopamine transporter (DAT) uptake-a key biomarker in DLB diagnosis-could improve diagnostic accuracy. However, DAT imaging is underutilized despite its potential, contributing to delays and suboptimal patient management. Methods: This review evaluates DLB diagnostic practices and challenges faced within the U.S. by synthesizing information from current literature, consensus guidelines, expert opinions, and recent updates on DaTscan FDA filings. It contrasts DAT SPECT with alternative biomarkers, provides recommendations for when DAT SPECT imaging may be indicated and discusses the potential of emerging biomarkers in enhancing diagnostic approaches. Results: The radiopharmaceutical 123I-ioflupane for SPECT imaging was initially approved in Europe (2000) and later in the US (2011) for Parkinsonism/Essential Tremor. Its application was extended in 2022 to include the diagnosis of DLB. DaTscan's diagnostic efficacy for DLB, with its sensitivity, specificity, and predictive values, confirms its clinical utility. However, US implementation faces challenges such as insurance barriers, costs, access issues, and regional availability disparities. Conclusion: 123I-ioflupane SPECT Imaging is indicated for DLB diagnosis and differential diagnosis of Alzheimer's Disease, particularly in uncertain cases. Addressing diagnostic obstacles and enhancing physician-patient education could improve and expedite DLB diagnosis. Collaborative efforts among neurologists, geriatric psychiatrists, psychologists, and memory clinic staff are key to increasing diagnostic accuracy and care in DLB management.
RESUMEN
Ongoing assessment of patients with Alzheimer's disease (AD) in postapproval studies is important for mapping disease progression and evaluating real-world treatment effectiveness and safety. However, interpreting outcomes in the real world is challenging owing to variation in data collected across centers and specialties and greater heterogeneity of patients compared with trial participants. Here, we share considerations for observational postapproval studies designed to collect harmonized longitudinal data from individuals with mild cognitive impairment or mild dementia stage of disease who receive therapies targeting the underlying pathological processes of AD in routine practice. This paper considers key study design parameters, including proposed aims and objectives, study populations, approaches to data collection, and measures of cognition, functional abilities, neuropsychiatric status, quality of life, health economics, safety, and drug utilization. Postapproval studies that capture these considerations will be important to provide standardized data on AD treatment effectiveness and safety in real-world settings.
Asunto(s)
Enfermedad de Alzheimer , Humanos , Enfermedad de Alzheimer/terapia , Disfunción Cognitiva , Proyectos de Investigación , Calidad de Vida , Estudios Observacionales como Asunto , Progresión de la EnfermedadRESUMEN
Accurate balance assessment is important in healthcare for identifying and managing conditions affecting stability and coordination. It plays a key role in preventing falls, understanding movement disorders, and designing appropriate therapeutic interventions across various age groups and medical conditions. However, traditional balance assessment methods often suffer from subjectivity, lack of comprehensive balance assessments and remote assessment capabilities, and reliance on specialized equipment and expert analysis. In response to these challenges, our study introduces an innovative approach for estimating scores on the Modified Clinical Test of Sensory Interaction on Balance (m-CTSIB). Utilizing wearable sensors and advanced machine learning algorithms, we offer an objective, accessible, and efficient method for balance assessment. We collected comprehensive movement data from 34 participants under four different sensory conditions using an array of inertial measurement unit (IMU) sensors coupled with a specialized system to evaluate ground truth m-CTSIB balance scores for our analysis. This data was then preprocessed, and an extensive array of features was extracted for analysis. To estimate the m-CTSIB scores, we applied Multiple Linear Regression (MLR), Support Vector Regression (SVR), and XGBOOST algorithms. Our subject-wise Leave-One-Out and 5-Fold cross-validation analysis demonstrated high accuracy and a strong correlation with ground truth balance scores, validating the effectiveness and reliability of our approach. Key insights were gained regarding the significance of specific movements, feature selection, and sensor placement in balance estimation. Notably, the XGBOOST model, utilizing the lumbar sensor data, achieved outstanding results in both methods, with Leave-One-Out cross-validation showing a correlation of 0.96 and a Mean Absolute Error (MAE) of 0.23 and 5-fold cross-validation showing comparable results with a correlation of 0.92 and an MAE of 0.23, confirming the model's consistent performance. This finding underlines the potential of our method to revolutionize balance assessment practices, particularly in settings where traditional methods are impractical or inaccessible.
RESUMEN
Background: Few studies have investigated associations between perceived social determinants of health (SDOH) and Alzheimer's disease and related dementia (ADRD) biomarkers or between SDOH and resilience against ADRD. Objective: To examine associations between perceived and objective SDOH and ADRD-related outcomes. Methods: We used cross-sectional data on≥50-year-olds without dementia in the Healthy Brain Initiative (nâ=â162). Questionnaires captured trust in neighbors and indices of perceived neighborhood greenspace access, time spent in neighborhood greenspaces, and interpersonal discrimination. Residential addresses were linked to 2021 Area Deprivation Index scores. The Vulnerability Index (VI) is based on 12 dementia risk factors (e.g., age, race/ethnicity, diabetes) and Resilience Index (RI) is based on 6 protective factors (e.g., diet, mindfulness, physical activity). Cognitive measured included number symbol coding task and Montreal Cognitive Assessment. Biomarkers included Aß42/40 and pTau-217/npTau-217, hippocampal and white matter hyperintensity volume, lipoprotein A, and high-sensitivity c-reactive protein. Results: Perceived greater access to greenspaces (estimateâ=â2.83, 95% CIâ=â1.40-4.26) and greater time in neighborhood greenspaces were associated with greater RI scores (estimateâ=â2.30, 95% CIâ=â1.24-3.35). Reporting greater discrimination (estimateâ=â0.10, 95% CIâ=â0.04-0.16) and living in higher deprivation neighborhoods were associated with greater VI scores (estimateâ=â0.017, 95% CIâ=â0.003-0.032). Greater discrimination was associated with greater white matter hyperintensity volume (estimateâ=â0.27, 95% CIâ=â0.04-0.51). Conclusions: Perceived greenspace access and time spent in greenspaces were associated with resilience against ADRD, and interpersonal discrimination was associated with vulnerability to ADRD. Future work needs to validate perceived SDOH measures, examine associations in racially/ethnic diverse populations, and investigate longitudinal associations between SDOH and ADRD-related biomarkers.
RESUMEN
Background and Objectives: Dementia with Lewy bodies (DLB) is a common degenerative dementia, but research on caregiver experiences in late stages is lacking. This study aimed to investigate the caregiving experience in moderate-advanced DLB to identify opportunities for improving care and support. Methods: Dyads of individuals with moderate-advanced DLB and their primary informal caregivers were recruited from specialty clinics, advocacy organizations, and research registries. The study collected demographics, disease-related measures, and measures of the caregiver experience relating to caregiver support, burden, grief, self-efficacy, depression, quality of life, and coping. Spearman correlation coefficients and Wilcoxon rank-sum tests evaluated the relationships of caregiver measures with patient and caregiver variables with adjustments for multiple testing. Results: Caregivers (n = 143) were mostly women (83.5%) and spouses (84.7%) (mean age 68 years; range 37-85). Almost 40% reported high burden and/or depression. Caregiver measures correlated with fluctuation and behavioral symptom severity, sleepiness, and autonomic symptoms of the person with DLB. Higher burden correlated with worse caregiver quality of life, higher depression, and grief. Greater self-efficacy, social support, and resilience correlated with lower caregiver burden. The most frequently reported caregiver concerns were being unable to plan for the future, having to put the needs of the person with DLB ahead of the caregiver's own needs, and worry that the person with DLB would become too dependent on the caregiver, but many additional concerns were endorsed. Caregivers were generally satisfied with medical team support. The lowest reported satisfaction related to information regarding disease progression and how well medical teams shared information with each other. Discussion: Various patient-related and caregiver-related factors influence caregiver experiences in moderate-advanced DLB. Clinicians can target caregiver needs by providing support resources and DLB education and treating bothersome patient symptoms. Future research should investigate what interventions can modify and improve caregiver experiences in advanced DLB and identify therapeutics for patient symptoms currently without adequate treatments (e.g., fluctuations, daytime sleepiness). Trial Registration Information: NCT04829656.
RESUMEN
Test Background: Alzheimer's disease (AD) is characterized by progressive cognitive decline, including impairments in speech production and fluency. Mild cognitive impairment (MCI), a prodrome of AD, has also been linked with changes in speech behavior but to a more subtle degree. OBJECTIVE: This study aimed to investigate whether speech behavior immediately following both filled and unfilled pauses (post-pause speech behavior) differs between individuals with MCI and healthy controls (HCs), and how these differences are influenced by the cognitive demands of various speech tasks. METHODS: Transcribed speech samples were analyzed from both groups across different tasks, including immediate and delayed narrative recall, picture descriptions, and free responses. Key metrics including lexical and syntactic complexity, lexical frequency and diversity, and part of speech usage, both overall and post-pause, were examined. RESULTS: Significant differences in pause usage were observed between groups, with a higher incidence and longer latencies following these pauses in the MCI group. Lexical frequency following filled pauses was higher among MCI participants in the free response task but not in other tasks, potentially due to the relative cognitive load of the tasks. The immediate recall task was most useful at differentiating between groups. Predictive analyses utilizing random forest classifiers demonstrated high specificity in using speech behavior metrics to differentiate between MCI and HCs. CONCLUSIONS: Speech behavior following pauses differs between MCI participants and healthy controls, with these differences being influenced by the cognitive demands of the speech tasks. These post-pause speech metrics can be easily integrated into existing speech analysis paradigms.
RESUMEN
Background: Mild cognitive impairment (MCI) can be an early sign of Alzheimer's disease and other types of dementia detectable through gait analysis. Curve walking, which demands greater cognitive and motor skills, may be more sensitive in MCI detection than straight walking. However, few studies have compared gait performance in older adults with and without MCI in these conditions. Objective: To compare the capability of curve and straight walking tests for the detection of MCI among older adults. Methods: We employed a Kinect v.2 camera to record the gait of 55 older adults (30 healthy controls, 25 with MCI) during single-task straight and curve walking tests. We examined 50 gait markers and conducted statistical analyses to compare groups and conditions. The trail was approved with protocol No. IR.SEMUMS.REC.1398.237 by the ethics committee of Semnan University of Medical Sciences in Iran. Results: Older adults with MCI exhibited more compromised gait performance, particularly during curve walking. Curve walking outperformed straight walking in MCI detection, with several gait markers showing significant differences between healthy controls and MCI patients. These markers encompass average velocity, cadence, temporal markers (e.g., gait cycle subphase durations), spatial markers (e.g., foot position changes during gait subphases), and spatiotemporal markers (e.g., step and stride velocities). Conclusions: Our study suggests curve walking as a more informative and challenging test for MCI detection among older adults, facilitating early diagnosis using non-invasive, cost-effective tools like the Kinect v.2 camera, complementing cognitive assessments in early diagnosis, and tracking MCI progression to dementia.
RESUMEN
Background: Lifestyle factors are linked to differences in brain aging and risk for Alzheimer's disease, underscored by concepts like 'cognitive reserve' and 'brain maintenance'. The Resilience Index (RI), a composite of 6 factors (cognitive reserve, physical and cognitive activities, social engagement, diet, and mindfulness) provides such a holistic measure. Objective: This study aims to examine the association of RI scores with cognitive function and assess the mediating role of cortical atrophy. Methods: Baseline data from 113 participants (aged 45+, 68% female) from the Healthy Brain Initiative were included. Life course resilience was estimated with the RI, cognitive performance with Cognivue®, and brain health using a machine learning derived Cortical Atrophy Score (CAS). Mediation analysis probed the relationship between RI, cognitive outcomes, and cortical atrophy. Results: In age and sex adjusted models, the RI was significantly associated with CAS (ß=â-0.25, pâ=â0.006) and Cognivue® scores (ß=â0.32, pâ<â0.001). The RI-Cognivue® association was partially mediated by CAS (ß=â0.07; 95% CI [0.02, 0.14]). Conclusions: Findings revealed that the collective effect of early and late-life lifestyle resilience factors on cognition are partially explained by their association with less brain atrophy. These findings underscore the value of comprehensive lifestyle assessments in understanding the risk and progression of cognitive decline and Alzheimer's disease in an aging population.
Asunto(s)
Enfermedad de Alzheimer , Disfunción Cognitiva , Resiliencia Psicológica , Humanos , Femenino , Anciano , Masculino , Enfermedad de Alzheimer/patología , Imagen por Resonancia Magnética , Pruebas Neuropsicológicas , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Cognición , Disfunción Cognitiva/psicología , Atrofia/patologíaRESUMEN
INTRODUCTION: Little is known regarding quality of life (QoL) in dementia with Lewy bodies (DLB), particularly in advanced stages. METHODS: Dyads of individuals with moderate-advanced DLB and their primary caregivers were recruited from specialty clinics, advocacy organizations, and research registries. The study collected demographics, disease-related measures, and measures of patient/caregiver experiences. RESULTS: The Quality of Life in Alzheimer's Disease (QoL-AD) was completed by the person with DLB and the caregiver (proxy) in 61 dyads; 85 dyads had only a proxy-completed QoL-AD. Patient- and proxy-reported scores were moderately correlated (r = 0.57, P < 0.0001). Worse patient-reported QoL correlated with daytime sleepiness, autonomic symptom burden, and behavioral symptoms. Proxy ratings correlated with dementia severity, daytime sleepiness, behavioral symptoms, dependence in activities of daily living, and caregiver experience measures. DISCUSSION: Patient- and proxy-reported quality of life (QoL) should be assessed separately in advanced DLB. Some symptoms associated with QoL have available therapeutic options. Research is needed regarding strategies to optimally improve QoL in DLB. HIGHLIGHTS: Patient and proxy quality of life (QoL) ratings had moderate correlation in advanced dementia with Lewy bodies. Daytime sleepiness affected patient- and proxy-reported QoL. Behavioral symptoms affected patient- and proxy-reported QoL. Autonomic symptom burden affected patient-reported QoL. Dementia severity, dependence, and caregiver experiences affected proxy ratings.
Asunto(s)
Enfermedad de Alzheimer , Trastornos de Somnolencia Excesiva , Enfermedad por Cuerpos de Lewy , Humanos , Calidad de Vida , Enfermedad por Cuerpos de Lewy/diagnóstico , Actividades Cotidianas , Enfermedad de Alzheimer/diagnóstico , CuidadoresRESUMEN
Despite its high prevalence among dementias, Lewy body dementia (LBD) remains poorly understood with a limited, albeit growing, evidence base. The public-health burden that LBD imposes is worsened by overlapping pathologies, which contribute to misdiagnosis, and lack of treatments. For this report, we gathered and analyzed public-domain information on advocacy, funding, research outputs, and the therapeutic pipeline to identify gaps in each of these key elements. To further understand the current gaps, we also conducted interviews with leading experts in regulatory/governmental agencies, LBD advocacy, academic research, and biopharmaceutical research, as well as with funding sources. We identified wide gaps across the entire landscape, the most critical being in research. Many of the experts participated in a workshop to discuss the prioritization of research areas with a view to accelerating therapeutic development and improving patient care. This white paper outlines the opportunities for bridging the major LBD gaps and creates the framework for collaboration in that endeavor. HIGHLIGHTS: A group representing academia, government, industry, and consulting expertise was convened to discuss current progress in Dementia with Lewy Body care and research. Consideration of expert opinion,natural language processing of the literature as well as publicly available data bases, and Delphi inspired discussion led to a proposed consensus document of priorities for the field.
Asunto(s)
Enfermedad por Cuerpos de Lewy , Humanos , Enfermedad por Cuerpos de Lewy/diagnóstico , Enfermedad por Cuerpos de Lewy/terapiaRESUMEN
BACKGROUND: Existing measures of scam susceptibility lack ecological validity and situational variability. Evidence suggests that all adults may be susceptible to scams, though a comprehensive fraud victimization theory remains to be explored. OBJECTIVE: To identify cognitive and sociodemographic variables that differentiate individuals with high scam susceptibility from those less susceptible. This article describes the development and feasibility of the Assessment of Situational Judgment questionnaire (ASJ), a brief tool designed to detect scam susceptibility. METHODS: The 17-item ASJ was developed using a combination of existing scams reported by the Florida Division of Consumer Services and legitimate scenarios. Participants were presented with scam and legitimate scenarios and queried regarding their willingness to engage. Response options were offered with instructions on a 7-point Likert scale (extremely unlikely to extremely likely). Pilot data from a development sample provided the foundation for the final version of the ASJ. RESULTS: The final version of the ASJ was administered to 183 online participants. The Scam factor (8 items) explained 50.6% of the variance. The Legit factor (9 items) reported on a 7-point Likert scale explaining 10.6% of the variance. A Scam to Legit ratio provides a proxy for overall scam susceptibility. Cut-off scores of 24 on the Scam factor, 47 on the Legit factor, and 0.62 on the ratio optimize measures of scam susceptibility. CONCLUSIONS: The ASJ is a brief, ecologically valid measure of scam susceptibility. There is a need for a sensitive and specific tool to detect scam susceptibility in clinical, community, and financial settings.
Asunto(s)
Víctimas de Crimen , Juicio , Humanos , Fraude , Encuestas y Cuestionarios , Susceptibilidad a Enfermedades , Víctimas de Crimen/psicologíaRESUMEN
INTRODUCTION: The National Institute on Aging - Alzheimer's Association (NIA-AA) ATN research framework proposes to use biomarkers for amyloid (A), tau (T), and neurodegeneration (N) to stage individuals with AD pathological features and track changes longitudinally. The overall aim was to utilize this framework to characterize pre-mortem ATN status longitudinally in a clinically diagnosed cohort of dementia with Lewy bodies (DLB) and to correlate it with the post mortem diagnosis. METHODS: The cohort was subtyped by cerebrospinal fluid (CSF) ATN category. A subcohort had longitudinal data, and a subgroup was neuropathologically evaluated. RESULTS: We observed a significant difference in Aß42/40 after 12 months in the A+T- group. Post mortem neuropathologic analyses indicated that most of the p-Tau 181 positive (T+) cases also had a high Braak stage. DISCUSSION: This suggests that DLB patients who are A+ but T- may need to be monitored to determine whether they remain A+ or ever progress to T positivity. HIGHLIGHTS: Some A+T- DLB subjects transition from A+ to negative after 12-months. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Clinically diagnosed DLB with LBP-AD (A+T+) maintain their positivity. Monitoring of the A+T- sub-type of DLB may be necessary.
Asunto(s)
Enfermedad de Alzheimer , Enfermedad por Cuerpos de Lewy , Humanos , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/líquido cefalorraquídeo , Enfermedad por Cuerpos de Lewy/diagnóstico , Enfermedad por Cuerpos de Lewy/líquido cefalorraquídeo , Péptidos beta-Amiloides/líquido cefalorraquídeo , Proteínas tau/líquido cefalorraquídeo , Biomarcadores/líquido cefalorraquídeo , Fragmentos de Péptidos/líquido cefalorraquídeoRESUMEN
OBJECTIVES: Racially and ethnically diverse populations have recently contributed to the majority of rural and small-town growth. Consequently, the disproportionately high risk and prevalence of Alzheimer's disease and related dementias (ADRD) among rural and minoritized older residents will likely increase. To address this threat, we tested the hypotheses that (1) a faith-based, resident-led approach would increase basic ADRD knowledge and diagnosis, and (2) older age, female gender, lower educational levels, and more years lived rural would predict number of referrals, new dementia diagnoses, and treatment. METHODS: An adaptation of Schoenberg's Faith Moves Mountains model, previously successful in detection and management of other chronic illnesses in rural settings, guided this community-based participatory research. Local faith community members were trained as research assistants to recruit, administer surveys, conduct brief memory assessments, teach brain health strategies, and follow-up with residents. Outreaches were offered virtually during the pandemic, then in-person monthly at rotating church sites, and repeated â¼1 year later. RESULTS: This rural sample was racially and ethnically diverse (74.5% non-White), with 28% reporting eight or less years of formal education. Findings included that referrals and years lived rural were significant and positive predictors of new ADRD treatments [(b = 3.74, χ2(1, n = 235) = 13.01, p < 0.001); (b = 0.02, χ2(1, n = 235 = 3.93, p = 0.048)], respectively, regardless of participant characteristics. CONCLUSION: Resident-led action research in rural, diverse, faith communities is a successful approach to increasing ADRD disease knowledge, detection, diagnosis, and treatment.
Asunto(s)
Enfermedad de Alzheimer , Investigación Participativa Basada en la Comunidad , Conocimientos, Actitudes y Práctica en Salud , Población Rural , Anciano , Anciano de 80 o más Años , Femenino , Humanos , Masculino , Persona de Mediana Edad , Enfermedad de Alzheimer/diagnóstico , Enfermedad de Alzheimer/etnología , Etnicidad/estadística & datos numéricos , Conocimientos, Actitudes y Práctica en Salud/etnología , Población Rural/estadística & datos numéricos , Grupos Raciales/estadística & datos numéricosRESUMEN
Background and Objectives: Many individuals with dementia and their families report not receiving a dementia diagnosis. Previously published standards for delivering a dementia diagnosis are now more than 10 years old and were developed without patient and caregiver input. The objective of this study was to identify best practices for delivering a diagnosis of dementia using existing literature, involvement of diverse stakeholders, and consensus building through a formal modified Delphi approach. Methods: We convened a multi-stakeholder working group including a patient, caregivers, Alzheimer's Association staff, and clinicians from diverse backgrounds. The panel used the American Academy of Neurology process for recommendation development, consisting of a half-day workshop and 3 rounds of anonymous modified Delphi voting to achieve consensus. Results: The working group convened from May 2022 through January 2023. The group chose to focus statements on a limited number of best practices that can be applied across clinic types. Seven best practice statements achieved consensus after a maximum of 3 rounds of voting. These included the following: (1) Clinicians must show compassion and empathy when delivering a diagnosis of dementia (level A). During dementia diagnosis disclosure, clinicians should (2) ask regarding diagnosis preferences, (3) instill realistic hope, (4) provide practical strategies, (5) provide education and connections to high-quality resources, (6) connect caregivers to support resources, and (7) provide written summaries of the diagnoses, plan, and relevant resources (each level B). Discussion: Clinicians need to customize discussion of a dementia diagnosis for individual patients and their caregivers. These 7 best practices provide a diagnosis communication framework that can be implemented across varied clinical settings. Additional strategies, such as using optimal general communication approaches, are also important for dementia diagnosis discussions. Thoughtful application of these best practices is particularly important when caring for individuals from underrepresented communities. Further improving communication regarding dementia diagnoses will require health system changes (e.g., for sufficient time), improved access to specialty dementia care, and clinician training for delivering difficult diagnoses. More research is needed to identify culturally sensitive approaches to discussing dementia diagnoses.
RESUMEN
BACKGROUND: Identifying individuals with mild cognitive impairment (MCI) who are likely to progress to Alzheimer's disease and related dementia disorders (ADRD) would facilitate the development of individualized prevention plans. We investigated the association between MCI and comorbidities of ADRD. We examined the predictive potential of these comorbidities for MCI risk determination using a machine learning algorithm. METHODS: Using a retrospective matched case-control design, 5185 MCI and 15,555 non-MCI individuals aged ≥50 years were identified from MarketScan databases. Predictive models included ADRD comorbidities, age, and sex. RESULTS: Associations between 25 ADRD comorbidities and MCI were significant but weakened with increasing age groups. The odds ratios (MCI vs non-MCI) in 50-64, 65-79, and ≥ 80 years, respectively, for depression (4.4, 3.1, 2.9) and stroke/transient ischemic attack (6.4, 3.0, 2.1). The predictive potential decreased with older age groups, with ROC-AUCs 0.75, 0.70, and 0.66 respectively. Certain comorbidities were age-specific predictors. CONCLUSIONS: The comorbidity burden of MCI relative to non-MCI is age-dependent. A model based on comorbidities alone predicted an MCI diagnosis with reasonable accuracy.
Asunto(s)
Enfermedad de Alzheimer , Disfunción Cognitiva , Humanos , Anciano , Estudios Retrospectivos , Sensibilidad y Especificidad , Progresión de la Enfermedad , Enfermedad de Alzheimer/diagnóstico , Disfunción Cognitiva/epidemiología , Disfunción Cognitiva/diagnóstico , Comorbilidad , Factores de EdadRESUMEN
Background: The Health Brain Initiative (HBI), established by University of Miami's Comprehensive Center for Brain Health (CCBH), follows racially/ethnically diverse older adults without dementia living in South Florida. With dementia prevention and brain health promotion as an overarching goal, HBI will advance scientific knowledge by developing novel assessments and non-invasive biomarkers of Alzheimer's disease and related dementias (ADRD), examining additive effects of sociodemographic, lifestyle, neurological and biobehavioral measures, and employing innovative, methodologically advanced modeling methods to characterize ADRD risk and resilience factors and transition of brain aging. Methods: HBI is a longitudinal, observational cohort study that will follow 500 deeply-phenotyped participants annually to collect, analyze, and store clinical, cognitive, behavioral, functional, genetic, and neuroimaging data and biospecimens. Participants are ≥50 years old; have no, subjective, or mild cognitive impairment; have a study partner; and are eligible to undergo magnetic resonance imaging (MRI). Recruitment is community-based including advertisements, word-of-mouth, community events, and physician referrals. At baseline, following informed consent, participants complete detailed web-based surveys (e.g., demographics, health history, risk and resilience factors), followed by two half-day visits which include neurological exams, cognitive and functional assessments, an overnight sleep study, and biospecimen collection. Structural and functional MRI is completed by all participants and a subset also consent to amyloid PET imaging. Annual follow-up visits repeat the same data and biospecimen collection as baseline, except that MRIs are conducted every other year after baseline. Ethics and expected impact: HBI has been approved by the University of Miami Miller School of Medicine Institutional Review Board. Participants provide informed consent at baseline and are re-consented as needed with protocol changes. Data collected by HBI will lead to breakthroughs in developing new diagnostics and therapeutics, create comprehensive diagnostic evaluations, and provide the evidence base for precision medicine approaches to dementia prevention with individualized treatment plans.