Timely Diagnosis for Alzheimer's Disease: A Literature Review on Benefits and Challenges

Validation of Different Dementia Code-Based Definitions in a Population-Based Study of Rheumatoid Arthritis

OBJECTIVE

Rheumatoid arthritis (RA) has been associated with an elevated dementia risk. This study aimed to examine how different diagnostic dementia definitions perform in patients with RA compared to individuals without RA.

METHODS

The study population included 2050 individuals (1025 with RA) from a retrospective, population-based cohort in southern Minnesota and compared the performance of 3 code-based dementia diagnostic algorithms with medical record review diagnosis of dementia. For the overall comparison, each patient's complete medical history was used, with no time frames. Sensitivity analyses were performed using 1-, 2-, and 5-year windows around the date that dementia was identified in the medical record (reference standard).

RESULTS

Algorithms performed very similarly in persons with and without RA. The algorithms generally had high specificity, negative predictive values, and accuracy, regardless of the time window studied (> 88%). Sensitivity and positive predictive values varied depending on the algorithm and the time window. Sensitivity values ranged 56.5-95.9%, and positive predictive values ranged 55.2-83.1%. Performance measures declined with more restrictive time windows.

CONCLUSION

Routinely collected electronic health record (EHR) data were used to define code-based dementia diagnostic algorithms with good performance (vs diagnosis by medical record review). These results can inform future studies that use retrospective databases, especially in the same or a similar EHR infrastructure, to identify dementia in individuals with RA.

Exploring challenges and innovation in memory assessment services in England and Wales - a national survey and case study approach

BACKGROUND

To explore the design, delivery models and identify good and innovative practices in Memory Assessment Services (MAS) in England and Wales.

METHODS

A two-stage service evaluation comprising (1) on-line survey of MAS providers to identify features of the commissioning models, service design, delivery, and challenges alongside examples of good/innovative practice; (2) qualitative case studies using video/telephone interviews with key staff and people who had used the service.

RESULTS

The 49 respondents to the survey reported a shift in delivery of MAS post COVID and identified key areas for improvement, including a need for specialist staff, support for MCI and rarer dementias, and capacity for post diagnostic support. The 15 case studies illustrated good practice and innovation focusing on post diagnostic support, equity of access, working with external services/service location, MCI and rarer dementia and involving specialist staff.

CONCLUSIONS

The evaluation speaks to the importance of (re)evaluation of services to identify local need and the importance of commissioning based on local need and innovative approaches that my sit outside of 'typical' MAS pathways.

Documentation of shared decision-making in diagnostic testing for dementia in Dutch general practice: A retrospective study in electronic patient records

OBJECTIVE

To explore (1) documentation of shared decision-making (SDM) in diagnostic testing for dementia in electronic patient records (EPR) in general practice and (2) study whether documentation of SDM is related to specific patient characteristics.

METHODS

In this retrospective observational study, EPRs of 228 patients in three Dutch general practices were explored for the documentation of SDM elements using Elwyn's model (team talk, option talk, decision talk). Patient characteristics (gender, age, comorbidities, chronic polypharmacy, the number of consultations on memory complaints) and decision outcome (wait-and-see, GP diagnostics, referral) were also extracted.

RESULTS

In EPRs of most patients (62.6 %), at least one SDM element was documented. Most often this concerned team talk (61.6 %). Considerably less often option talk (4.3 %) and decision talk (12.8 %) were documented. SDM elements were more frequently documented in patients with lower comorbidity scores and patients with a relatively high number of consultations. Decision talk was more frequently documented in referred patients.

CONCLUSION

Patients' and significant others' needs, goals, and wishes on diagnostic testing for dementia are often documented in EPRs.

PRACTICE IMPLICATIONS

Limited documentation of option and decision talk stresses the need for future SDM interventions to facilitate timely dementia diagnosis.

Control Beliefs after a Diagnosis of Alzheimer's Disease and Related Dementias: The Need to Foster Resilience

Objectives: Positive adaptation, like higher control beliefs, following a disability diagnosis is important to buffer against excess disability; however, no study has examined how the recent diagnosis of Alzheimer's disease and related dementias (ADRD) impacts control beliefs. The current study addresses this gap in the literature. Method: We use data from the 2012-2016 waves of the Health and Retirement Study. Propensity score weighting was used to address the systematic selection of an ADRD diagnosis to understand how control beliefs (perceived constraints and mastery) are impacted two years following a diagnosis. Results: A new diagnosis of ADRD was associated with a lower mastery score two years later, regardless of baseline functional ability (b = -0.652, p < .001). No associations were noted between a new ADRD diagnosis and perceived constraints. Conclusions: Our results suggest that a recent diagnosis of ADRD has negative implications for mastery, which may facilitate excess disability.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations

Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. We employ an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compare this model with APOE and polygenic risk score models across genetic ancestry groups (Hispanic Latino American sample: 610 patients with 126 cases; African American sample: 440 patients with 84 cases; East Asian American sample: 673 patients with 75 cases), using electronic health records from UCLA Health for discovery and the All of Us cohort for validation. Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 31-84% (Wilcoxon signed-rank test p-value <0.05) and the area-under-the-receiver-operating characteristic by 11-17% (DeLong test p-value <0.05) compared to the APOE and the polygenic risk score models. We identify shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. Our study highlights the benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

Barriers to Timely Dementia Diagnosis in Older Latinos With Limited English Proficiency: An Integrative Review

INTRODUCTION

Timely diagnosis is critical for persons with Alzheimer's disease and related dementias (ADRD) to ensure they receive adequate services; however, timely diagnosis may be prevented by a person's English language skills. The purpose of this integrative review was to understand how limited English proficiency (LEP) impacts older Latino's ability to access a timely ADRD diagnosis.

METHODS

Whittemore and Knafl's methodological approach guided the review. Searches in five databases yielded 12 articles for inclusion.

RESULTS

Lack of culturally congruent health care systems, health care providers, and knowledge of ADRD resulted in delays in obtaining a timely ADRD diagnosis among older Latinos with LEP.

DISCUSSION

Latinos with LEP and risk for ADRD benefit from language assistance and support in navigating the health care system. Nurses must be advocates, even when a language barrier is present, and recognize that interpreters are not a single source solution.

Correlates of missed or late versus timely diagnosis of dementia in healthcare settings

INTRODUCTION

There is limited evidence about factors related to the timeliness of dementia diagnosis in healthcare settings.

METHODS

In five prospective cohorts at Rush Alzheimer's Disease Center, we identified participants with incident dementia based on annual assessments and examined the timing of healthcare diagnoses in Medicare claims. We assessed sociodemographic, health, and psychosocial correlates of timely diagnosis.

RESULTS

Of 710 participants, 385 (or 54%) received a timely claims diagnosis within 3 years prior to or 1 year following dementia onset. In logistic regressions accounting for demographics, we found Black participants (odds ratio [OR] = 2.15, 95% confidence interval [CI]: 1.21 to 3.82) and those with better cognition at dementia onset (OR = 1.48, 95% CI: 1.10 to 1.98) were at higher odds of experiencing a diagnostic delay, whereas participants with higher income (OR = 0.89, 95% CI: 0.81 to 0.97) and more comorbidities (OR = 0.94, 95% CI: 0.89 to 0.98) had lower odds.

DISCUSSION

We identified characteristics of individuals who may miss the optimal window for dementia treatment and support.

HIGHLIGHTS

We compared the timing of healthcare diagnosis relative to the timing of incident dementia based on rigorous annual evaluation. Older Black adults with lower income, higher cognitive function, and fewer comorbidities were less likely to be diagnosed in a timely manner by the healthcare system.

Dementia Specialty Care Clinicians' Perspectives on Their Role in the Dementia Diagnostic Process and Diagnostic Disclosure

BACKGROUND

Delivering a diagnosis of Alzheimer's disease and related dementias (ADRD) can be challenging not just for patients and families, but also for clinicians. Our objective was to understand dementia specialty care clinicians' perspectives on their role in diagnosis and diagnostic disclosure in dementia.

METHODS

Qualitative interviews with clinicians from a specialty tertiary dementia care center focused on practices, challenges, and opportunities addressing patient and caregiver needs in dementia. Data was analyzed by an interdisciplinary team using thematic analysis.

RESULTS

The 16 participants included behavioral neurologists, social workers, neuropsychologists, and nurses. Themes included the value of providing an accurate diagnosis, the timing and challenges of delivering a diagnosis, the central focus on diagnosis alongside the need for more education on care management, and the role of the interdisciplinary team.

DISCUSSION

We identified areas for improvement and strengths that can be built upon or adapted to other settings, including providing clinicians in specialty and primary care settings more guidance and support when diagnostic challenges arise, strengthening interdisciplinary teamwork, and making dementia diagnosis and care more accessible.

Facilitators and barriers of help-seeking for persons with dementia in Asia-findings from a qualitative study of informal caregivers

Background and aim

The deterioration in cognition of persons with dementia (PWD) makes their caregivers key players in their help-seeking process. This study aimed to identify the facilitators and barriers of help-seeking for persons with dementia in Asia from the perspective of their informal caregivers.

Methods

A qualitative methodology was adopted in the current study. Twenty-nine informal caregivers of PWD in Singapore were interviewed between April 2019 and December 2020. All interviews were audio-recorded and transcribed verbatim for the analysis.

Results

The transcripts were analyzed using inductive thematic analysis. The results revealed four major themes with 12 sub-themes, including (1) Barriers to diagnosis-seeking (i.e., lack of knowledge and awareness of dementia, emotional denial, resistance from PWD, and delays in the healthcare system); (2) Facilitators of diagnosis-seeking (i.e., synergy between awareness of dementia and an active diagnosis-seeking intention and incidental diagnosis resulting from seeking treatment for comorbid conditions); (3) Barriers to treatment-seeking (i.e., challenges from PWD and disease, challenges faced by caregivers when seeking treatment for PWD, and challenges imposed by the COVID-19 pandemic); (4) Facilitators of treatment-seeking (i.e., caregivers' capabilities of handling PWD, cooperation/compliance from PWD, and an integrated care plan for PWD).

Conclusion

The findings highlight the importance of raising public awareness, enabling health professionals to tailor psychosocial interventions better, and improving community support through dementia awareness and education.

The features analysis of hemoglobin expression on visual information transmission pathway in early stage of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder characterized primarily by cognitive impairment. The motivation of this paper is to explore the impact of the visual information transmission pathway (V-H pathway) on AD, and the following feature were observed: Hemoglobin expression on the V-H pathway becomes dysregulated as AD occurs so as to the pathway becomes dysfunctional. According to the feature, the following conclusion was proposed: As AD occurs, abnormal tau proteins penetrate bloodstream and arrive at the brain regions of the pathway. Then the tau proteins or other toxic substances attack hemoglobin molecules. Under the attack, hemoglobin expression becomes more dysregulated. The dysfunction of V-H pathway has an impact on early symptoms of AD, such as spatial recognition disorder and face recognition disorder.

"There has to be more caring": patient and care partner experiences of the disclosure of amyloid-β PET scan results

OBJECTIVES

To explore patient and care partner experiences of receiving an amyloid scan result, with a focus on how clinician disclosure practices influenced patient and care partner emotional responses to the scan result and/or diagnosis.

METHODS

Semi-structured interviews with 38 people with mild cognitive impairment or dementia and 62 care partners who experienced the disclosure of results from an amyloid PET scan as part of the CARE-IDEAS study. We used thematic analysis to analyze interview transcripts.

RESULTS

We identified four aspects of the disclosure process that could influence patient and care partner emotional experiences of the scan result/diagnosis: (1) mode of delivery, (2) presence of a care partner, (3) clarity of the scan result explanation, and (4) discussion of post-scan treatment and support options.

CONCLUSIONS

Emotional experiences of an amyloid scan result can vary depending on how results are communicated. These findings support previous efforts to develop standard disclosure protocols. Scan results should be delivered in person with the care partner present. Clinicians should give a clear explanation of the result and its implications in an empathetic manner. Options for treatment and support should be discussed for all patients.

AI for the prediction of early stages of Alzheimer's disease from neuroimaging biomarkers - A narrative review of a growing field

OBJECTIVES

The objectives of this narrative review are to summarize the current state of AI applications in neuroimaging for early Alzheimer's disease (AD) prediction and to highlight the potential of AI techniques in improving early AD diagnosis, prognosis, and management.

METHODS

We conducted a narrative review of studies using AI techniques applied to neuroimaging data for early AD prediction. We examined single-modality studies using structural MRI and PET imaging, as well as multi-modality studies integrating multiple neuroimaging techniques and biomarkers. Furthermore, they reviewed longitudinal studies that model AD progression and identify individuals at risk of rapid decline.

RESULTS

Single-modality studies using structural MRI and PET imaging have demonstrated high accuracy in classifying AD and predicting progression from mild cognitive impairment (MCI) to AD. Multi-modality studies, integrating multiple neuroimaging techniques and biomarkers, have shown improved performance and robustness compared to single-modality approaches. Longitudinal studies have highlighted the value of AI in modeling AD progression and identifying individuals at risk of rapid decline. However, challenges remain in data standardization, model interpretability, generalizability, clinical integration, and ethical considerations.

CONCLUSION

AI techniques applied to neuroimaging data have the potential to improve early AD diagnosis, prognosis, and management. Addressing challenges related to data standardization, model interpretability, generalizability, clinical integration, and ethical considerations is crucial for realizing the full potential of AI in AD research and clinical practice. Collaborative efforts among researchers, clinicians, and regulatory agencies are needed to develop reliable, robust, and ethical AI tools that can benefit AD patients and society.

Neuropsychological Assessment for Early Detection and Diagnosis of Dementia: Current Knowledge and New Insights

Dementia remains an underdiagnosed syndrome, and there is a need to improve the early detection of cognitive decline. This narrative review examines the role of neuropsychological assessment in the characterization of cognitive changes associated with dementia syndrome at different states. The first section describes the early indicators of cognitive decline and the major barriers to their identification. Further, the optimal cognitive screening conditions and the most widely accepted tests are described. The second section analyzes the main differences in cognitive performance between Alzheimer's disease and other subtypes of dementia. Finally, the current challenges of neuropsychological assessment in aging/dementia and future approaches are discussed. Essentially, we find that current research is beginning to uncover early cognitive changes that precede dementia, while continuing to improve and refine the differential diagnosis of neurodegenerative disorders that cause dementia. However, neuropsychology faces several barriers, including the cultural diversity of the populations, a limited implementation in public health systems, and the adaptation to technological advances. Nowadays, neuropsychological assessment plays a fundamental role in characterizing cognitive decline in the different stages of dementia, but more efforts are needed to develop harmonized procedures that facilitate its use in different clinical contexts and research protocols.

Reliability and Validity of a Tablet-Based Neuropsychological Test (the Hellocog) for Screening Dementia

OBJECTIVE

To address the gap in timely diagnosis of dementia due to limited screening tools, we investigated the validity and reliability of the Hellocog, computerized neuropsychological test based on tablets for screening dementia. The higher the probability score on the Hellocog, the higher the likelihood of dementia.

METHODS

This study included 100 patients with dementia and 100 individuals with normal cognition who were aged 60 years or older and free of other major psychiatric, neurological, or medical conditions. They administered the Hellocog on a tablet under the supervision of a neuropsychologist. To determine test-retest reliability, 20 took the Hellocog again after 4 weeks. Diagnostic performance was assessed using the receiver operator characteristics (ROC) analysis.

RESULTS

The Hellocog showed adequate internal consistency (Cronbach's alpha=0.69) and good test-retest reliability (intraclass correlation coefficient=0.86, p<0.001). Participants with dementia scored higher on the Hellocog than those with normal cognition (p<0.001), confirming its high criterion validity. Strong correlations with the Mini-Mental Status Examination (MMSE) score and the total score of the Consortium to Establish a Registry for Alzheimer's Disease Neuropsychological Assessment Battery (CERAD-TS) highlight the concurrent validity of the Hellocog. The area under the ROC curve for dementia of the Hellocog was excellent (0.971) and comparable to that of the MMSE and CERAD-TS. The sensitivity and specificity for dementia were 0.945 and 0.872%, respectively, which were slightly better than those of the MMSE and CERAD-TS.

CONCLUSION

Hellocog stands out as a valid and reliable tool for self-administered dementia screening, with promise for improving early detection of dementia.

Cognitive trajectories preluding the onset of different dementia entities: a descriptive longitudinal study using the NACC database

OBJECTIVE

To describe the 10-year preclinical cognitive trajectories of older, non-demented individuals towards the onset of the four most prevalent types of dementia, i.e., Alzheimer's disease(AD), Lewy body(LBD), vascular(VD) and frontotemporal dementia(FTD).

METHODS

Our analysis focused on data from older (≥ 60years) NACC (National Alzheimer's Coordinating Center) participants. Four distinct presymptomatic dementia groups (AD-LBD-VD-FTD) and a comparison group of cognitively unimpaired(CU) participants were formed. Comprehensive cognitive assessments involving verbal episodic memory, semantic verbal fluency, confrontation naming, mental processing speed - attention and executive function - cognitive flexibility were conducted at baseline and on an approximately yearly basis. Descriptive analyses (adjusted general linear models) were performed to determine and compare the yearly cognitive scores of each group throughout the follow-up. Exploratory analyses were conducted to estimate the rates of cognitive decline.

RESULTS

There were 3343 participants who developed AD, 247 LBD, 108 FTD, 155 VD and 3398 composed the CU group. Participants with AD performed worse on episodic memory than those with VD and LBD for about 3 to 4 years prior to dementia onset (the FTD group documented an intermediate course). Presymptomatic verbal fluency and confrontation naming trajectories differentiated quite well between the FTD group and the remaining dementia entities. Participants with incident LBD and VD performed worse than those with AD on executive functions and mental processing speed-attention since about 5 years prior to the onset of dementia, and worse than those with FTD more proximally to the diagnosis of the disorder.

CONCLUSIONS

Heterogeneous cognitive trajectories characterize the presymptomatic courses of the most prevalent dementia entities.

Isolation and Characterization of Cell-Free DNA from Cerebral Organoids

Early detection of neurological conditions is critical for timely diagnosis and treatment. Identifying cellular-level changes is essential for implementing therapeutic interventions prior to symptomatic disease onset. However, monitoring brain tissue directly through biopsies is invasive and poses a high risk. Bodily fluids such as blood or cerebrospinal fluid contain information in many forms, including proteins and nucleic acids. In particular, cell-free DNA (cfDNA) has potential as a versatile neurological biomarker. Yet, our knowledge of cfDNA released by brain tissue and how cfDNA changes in response to deleterious events within the brain is incomplete. Mapping changes in cfDNA to specific cellular events is difficult in vivo, wherein many tissues contribute to circulating cfDNA. Organoids are tractable systems for examining specific changes consistently in a human background. However, few studies have investigated cfDNA released from organoids. Here, we examined cfDNA isolated from cerebral organoids. We found that cerebral organoids release quantities of cfDNA sufficient for downstream analysis with droplet-digital PCR and whole-genome sequencing. Further, gene ontology analysis of genes aligning with sequenced cfDNA fragments revealed associations with terms related to neurodevelopment and autism spectrum disorder. We conclude that cerebral organoids hold promise as tools for the discovery of cfDNA biomarkers related to neurodevelopmental and neurological disorders.

Genetic-based patient stratification in Alzheimer's disease

Alzheimer's disease (AD) shows a high pathological and symptomatological heterogeneity. To study this heterogeneity, we have developed a patient stratification technique based on one of the most significant risk factors for the development of AD: genetics. We addressed this challenge by including network biology concepts, mapping genetic variants data into a brain-specific protein-protein interaction (PPI) network, and obtaining individualized PPI scores that we then used as input for a clustering technique. We then phenotyped each obtained cluster regarding genetics, sociodemographics, biomarkers, fluorodeoxyglucose-positron emission tomography (FDG-PET) imaging, and neurocognitive assessments. We found three clusters defined mainly by genetic variants found in MAPT, APP, and APOE, considering known variants associated with AD and other neurodegenerative disease genetic architectures. Profiling of these clusters revealed minimal variation in AD symptoms and pathology, suggesting different biological mechanisms may activate the neurodegeneration and pathobiological patterns behind AD and result in similar clinical and pathological presentations, even a shared disease diagnosis. Lastly, our research highlighted MAPT, APP, and APOE as key genes where these genetic distinctions manifest, suggesting them as potential targets for personalized drug development strategies to address each AD subgroup individually.

Moving forward with dementia: an explorative cross-country qualitative study into post-diagnostic experiences

OBJECTIVES

This explorative cross-country qualitative study aims to describe experiences of receiving a dementia diagnosis and experiences of support following a diagnosis in Australia, Canada, the Netherlands and Poland.

METHOD

Qualitative study using projective techniques during online focus groups, online and telephone interviews with people with dementia and caregivers.

RESULTS

Twenty-three people with dementia and 53 caregivers participated. Qualitative content analysis revealed five themes; (1) 'Coming to terms with dementia' helped people deal with complex emotions to move forward. (3) 'The social network as a source of support' and (4) 'The challenges and realities of formal support' and impacted 'Coming to terms with dementia'. (2) 'Navigating life with dementia as a caregiver' highlights caregiver burden and was impacted by (4) 'The challenges and realities of formal support'. People were (5) 'Self-caring and preparing for tomorrow' as they focused on maintaining current health whilst planning the future. Despite differences in healthcare and post-diagnostic support systems, there were more similarities across countries than differences.

CONCLUSION

Across countries, formal support and support from friends and family are crucial for people with dementia and caregivers to come to terms with dementia and maintain carer wellbeing to ultimately live well with dementia.

A qualitative study of informal caregiver perceptions of the benefits of an early dementia diagnosis

BACKGROUND

Current and former dementia policies in the United Kingdom (UK) recommend diagnosing dementia early, or as close to the onset of symptoms as possible. Informal caregivers play an important role in initiating the diagnostic process and providing support to people living with dementia. Therefore, this study aimed to explore caregiver perceptions of the benefits of an early diagnosis.

METHODS

We conducted semi-structured interviews with 12 current and former informal caregivers to people with dementia in the UK in 2020. We analysed the interviews using thematic analysis.

RESULTS

Benefits of an early diagnosis included: (1) protecting the person with dementia from financial or physical harm, (2) timely decision-making, and (3) access to services and treatments following a diagnosis. We identified three conditions necessary for the benefits of an early diagnosis to be felt: (1) adequate prognostic information, (2) someone to advocate on behalf of the person with dementia, and (3) a willingness to seek and accept the diagnosis.

CONCLUSIONS

In this study, we identified how diagnosing dementia close to the onset of symptoms could be beneficial and the conditions necessary for these benefits to be felt. The findings highlight the importance of an early diagnosis for enabling people with dementia and caregivers to make practical arrangements and to access services. Further research is needed to build on the findings of this study by exploring the perspectives of people with dementia and by including a larger, more diverse sample of caregivers.

Agmatine as a novel intervention for Alzheimer's disease: Pathological insights and cognitive benefits

Alzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and a significant societal burden. Despite extensive research and efforts of the multidisciplinary scientific community, to date, there is no cure for this debilitating disease. Moreover, the existing pharmacotherapy for AD only provides symptomatic support and does not modify the course of the illness or halt the disease progression. This is a significant limitation as the underlying pathology of the disease continues to progress leading to the deterioration of cognitive functions over time. In this milieu, there is a growing need for the development of new and more efficacious treatments for AD. Agmatine, a naturally occurring molecule derived from L-arginine, has emerged as a potential therapeutic agent for AD. Besides this, agmatine has been shown to modulate amyloid beta (Aβ) production, aggregation, and clearance, key processes implicated in AD pathogenesis. It also exerts neuroprotective effects, modulates neurotransmitter systems, enhances synaptic plasticity, and stimulates neurogenesis. Furthermore, preclinical and clinical studies have provided evidence supporting the cognition-enhancing effects of agmatine in AD. Therefore, this review article explores the promising role of agmatine in AD pathology and cognitive function. However, several limitations and challenges exist, including the need for large-scale clinical trials, optimal dosing, and treatment duration. Future research should focus on mechanistic investigations, biomarker studies, and personalized medicine approaches to fully understand and optimize the therapeutic potential of agmatine. Augmenting the use of agmatine may offer a novel approach to address the unmet medical need in AD and provide cognitive enhancement and disease modification for individuals affected by this disease.

Actual Clinical Practice Assessment: A Rapid and Easy-to-Use Tool for Evaluating Cognitive Decline Equivalent to Dementia

Background Screening tests reveal the early signs of cognitive decline, enabling better self-care and preparation for the future. We developed and evaluated the accuracy of a rapid (20 s) and easy-to-use tool called ONSEI, assessing the cognitive decline equivalent to dementia in actual clinical practice by correlating clinical diagnoses with the ONSEI classification. Methods In this retrospective observational study, data were collected from individuals who visited three neurosurgical clinics in neighboring prefectures of Tokyo, Japan. ONSEI analysis was performed using a smartphone or tablet. The tool adopts a machine-learning algorithm using the speaker's age, time-orientation task score, and acoustic features of spoken responses to that task. Significant differences in accuracy, sensitivity, and specificity were evaluated by Fisher's exact test. Results The overall classification accuracy of ONSEI was 98.1% (p<0.001). The sensitivity and specificity were 97.3% (p<0.001) and 98.5% (p<0.001), respectively. The proportion of correct classifications was consistent across different age groups. Conclusion ONSEI showed high classification accuracy for dementia in cognitively normal individuals in actual clinical practice, regardless of the facility at which the tests were conducted or the age of the participants. Thus, ONSEI can be useful for dementia screening and self-care.

Toolkit to Examine Lifelike Language (TELL): An app to capture speech and language markers of neurodegeneration

Automated speech and language analysis (ASLA) is a promising approach for capturing early markers of neurodegenerative diseases. However, its potential remains underexploited in research and translational settings, partly due to the lack of a unified tool for data collection, encryption, processing, download, and visualization. Here we introduce the Toolkit to Examine Lifelike Language (TELL) v.1.0.0, a web-based app designed to bridge such a gap. First, we outline general aspects of its development. Second, we list the steps to access and use the app. Third, we specify its data collection protocol, including a linguistic profile survey and 11 audio recording tasks. Fourth, we describe the outputs the app generates for researchers (downloadable files) and for clinicians (real-time metrics). Fifth, we survey published findings obtained through its tasks and metrics. Sixth, we refer to TELL's current limitations and prospects for expansion. Overall, with its current and planned features, TELL aims to facilitate ASLA for research and clinical aims in the neurodegeneration arena. A demo version can be accessed here:  https://demo.sci.tellapp.org/ .

Immigration and access to dementia diagnostics and treatment: A nationwide study in Sweden

•Compared to Swedish-born people, foreign-born people were less likely to receive dementia diagnostic tests.•Being born in Africa or Europe was associated with lower chance of receiving cholinesterase inhibitors.•Asian-born people had higher chance of receiving cholinesterase inhibitors, but were less likely to receive memantine.•Disparities existed in dementia diagnostics and treatment between Swedish-born and foreign-born people, but were not consistent after adjusting for MMSE scores.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations

BACKGROUND

Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited.

METHODS

We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation.

RESULTS

Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOEand the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge.

CONCLUSIONS

Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

Improving genetic risk modeling of dementia from real-world data in underrepresented populations

BACKGROUND

Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited.

METHODS

We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation.

RESULTS

Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOE and the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge.

CONCLUSIONS

Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.

New horizons in the diagnosis and management of Alzheimer's Disease in older adults

Alzheimer's Disease (ad) is the most common cause of dementia, and in addition to cognitive decline, it directly contributes to physical frailty, falls, incontinence, institutionalisation and polypharmacy in older adults. Increasing availability of clinically validated biomarkers including cerebrospinal fluid and positron emission tomography to assess both amyloid and tau pathology has led to a reconceptualisation of ad as a clinical-biological diagnosis, rather than one based purely on clinical phenotype. However, co-pathology is frequent in older adults which influence the accuracy of biomarker interpretation. Importantly, some older adults with positive amyloid or tau pathological biomarkers may never experience cognitive impairment or dementia. These strides towards achieving an accurate clinical-biological diagnosis are occurring alongside recent positive phase 3 trial results reporting statistically significant effects of anti-amyloid Disease-Modifying Therapies (DMTs) on disease severity in early ad. However, the real-world clinical benefit of these DMTs is not clear and concerns remain regarding how trial results will translate to real-world clinical populations, potential adverse effects (including amyloid-related imaging abnormalities), which can be severe and healthcare systems readiness to afford and deliver potential DMTs to appropriate populations. Here, we review recent advances in both clinical-biological diagnostic classification and future treatment in older adults living with ad. Advocating for access to both more accurate clinical-biological diagnosis and potential DMTs must be done so in a holistic and gerontologically attuned fashion, with geriatricians advocating for enhanced multi-component and multi-disciplinary care for all older adults with ad. This includes those across the ad severity spectrum including older adults potentially ineligible for emerging DMTs.

Ratiometric Fluorescent Probe Promotes Trans-differentiation of Human Mesenchymal Stem Cells to Neurons

Development of multifunctional theranostics is challenging and crucial for deciphering complex biological phenomena and subsequently treating critical disease. In particular, development of theranostics for traumatic brain injury (TBI) and understanding its repair mechanism are challenging and highly complex areas of research. Recently, there have been interesting pieces of research work demonstrated that a small molecule-based neuroregenerative approach using stem cells has potential for future therapeutic lead development for TBI. However, these works demonstrated the application of a mixture of multiple molecules as a "chemical cocktail", which may have serious toxic effects in the differentiated cells. Therefore, development of a single-molecule-based potential differentiating agent for human mesenchymal stem cells (hMSCs) into functional neurons is vital for the upcoming neuro-regenerative therapeutics. This lead could be further extraploted for the design of theranostics for TBI. In this study, we have developed a multifunctional single-molecule-based fluorescent probe, which can image the transdifferentiated neurons as well as promote the differentiation process. We demonstrated a promising class of fluorescent probes (CP-4) that can be employed to convert hMSCs into neurons in the presence of fibroblast growth factor (FGF). This fluorescent probe was used in cellular imaging as its fluorescence intensity remained unaltered for up to 7 days of trans-differentiation. We envision that this imaging probe can have an important application in the study of neuropathological and neurodegenerative studies.

Knowledge, attitudes and self-confidence with skills required for providing dementia care in physicians at primary healthcare settings in Vietnam

BACKGROUND

Dementia is a global public health priority. The World Health Organization adopted a Global Action Plan on Dementia, with dementia awareness a priority. This study examined the knowledge, attitudes, and self-confidence with skills required for providing dementia care among primary health care providers in Vietnam.

METHODS

A cross-sectional study was conducted with 405 primary health care providers who worked at commune health stations and district health centers in eight provinces across Vietnam.

RESULTS

The results showed that primary health care providers had poor knowledge and little confidence but more positive attitudes toward dementia care and management.

CONCLUSIONS

The results suggest the training needs for building capacity amongst primary health care providers, which will be critical as Vietnam's population ages.

Estimating dementia risk in an African American population using the DCTclock

The prevalence of Alzheimer's disease (AD) and related dementias (ADRD) is increasing. African Americans are twice as likely to develop dementia than other ethnic populations. Traditional cognitive screening solutions lack the sensitivity to independently identify individuals at risk for cognitive decline. The DCTclock is a 3-min AI-enabled adaptation of the well-established clock drawing test. The DCTclock can estimate dementia risk for both general cognitive impairment and the presence of AD pathology. Here we performed a retrospective analysis to assess the performance of the DCTclock to estimate future conversion to ADRD in African American participants from the Rush Alzheimer's Disease Research Center Minority Aging Research Study (MARS) and African American Clinical Core (AACORE). We assessed baseline DCTclock scores in 646 participants (baseline median age = 78.0 ± 6.4, median years of education = 14.0 ± 3.2, 78% female) and found significantly lower baseline DCTclock scores in those who received a dementia diagnosis within 3 years. We also found that 16.4% of participants with a baseline DCTclock score less than 60 were significantly more likely to develop dementia in 5 years vs. those with the highest DCTclock scores (75-100). This research demonstrates the DCTclock's ability to estimate the 5-year risk of developing dementia in an African American population. Early detection of elevated dementia risk using the DCTclock could provide patients, caregivers, and clinicians opportunities to plan and intervene early to improve cognitive health trajectories. Early detection of dementia risk can also enhance participant selection in clinical trials while reducing screening costs.

Economic Impact of Progression from Mild Cognitive Impairment to Alzheimer Disease in the United States

BACKGROUND

Limited evidence exists on the economic burden of individuals who progress from mild cognitive impairment (MCI) to Alzheimer disease and related dementia disorders (ADRD).

OBJECTIVES

To assess the all-cause health care resource utilization and costs for individuals who develop ADRD following an MCI diagnosis compared to those with stable MCI.

DESIGN

This was a retrospective cohort study from January 01, 2014, to December 31, 2019.

SETTING

The Merative MarketScan Commercial and Medicare Databases were used.

PARTICIPANTS

Individuals were included if they: (1) were aged 50 years or older; (2) had ≥1 claim with an MCI diagnosis based on the International Classification of Diseases, Ninth Revision (ICD-9) code of 331.83 or the Tenth Revision (ICD-10) code of G31.84; and had continuous enrollment. Individuals were excluded if they had a diagnosis of Parkinson's disease or ADRD or prescription of ADRD medication.

MEASUREMENTS

Outcomes included all-cause utilization and costs per patient per year in the first 12 months following MCI diagnosis, in total and by care setting: inpatient admissions, emergency department (ED) visits, outpatient visits, and pharmacy claims.

RESULTS

Out of the total of 5185 included individuals, 1962 (37.8%) progressed to ADRD (MCI-to-ADRD subgroup) and 3223 (62.2%) did not (Stable MCI subgroup). Adjusted all-cause utilization was higher for all care settings in the MCI-to-ADRD subgroup compared with the Stable MCI subgroup. Adjusted all-cause mean total costs ($34 599 vs $24 541; mean ratio [MR], 1.41 [95% CI, 1.31-1.51]; P<.001), inpatient costs ($47 463 vs $38 004; MR, 1.25 [95% CI, 1.08-1.44]; P=.002), ED costs ($4875 vs $3863; MR, 1.26 [95% CI, 1.11-1.43]; P<.001), and outpatient costs ($16 652 vs $13 015; MR, 1.28 [95% CI, 1.20-1.37]; P<.001) were all significantly higher for the MCI-to-ADRD subgroup compared with the Stable MCI subgroup.

CONCLUSIONS

Individuals who progressed from MCI to ADRD had significantly higher health care costs than individuals with stable MCI. Early identification of MCI and delaying its progression is important to improve patient and economic outcomes.

Explainable machine learning for predicting conversion to neurological disease: Results from 52,939 medical records

Objective

This study assesses the application of interpretable machine learning modeling using electronic medical record data for the prediction of conversion to neurological disease.

Methods

A retrospective dataset of Cleveland Clinic patients diagnosed with Alzheimer's disease, amyotrophic lateral sclerosis, multiple sclerosis, or Parkinson's disease, and matched controls based on age, sex, race, and ethnicity was compiled. Individualized risk prediction models were created using eXtreme Gradient Boosting for each neurological disease at four timepoints in patient history. The prediction models were assessed for transparency and fairness.

Results

At timepoints 0-months, 12-months, 24-months, and 60-months prior to diagnosis, Alzheimer's disease models achieved the area under the receiver operating characteristic curve on a holdout test dataset of 0.794, 0.742, 0.709, and 0.645; amyotrophic lateral sclerosis of 0.883, 0.710, 0.658, and 0.620; multiple sclerosis of 0.922, 0.877, 0.849, and 0.781; and Parkinson's disease of 0.809, 0.738, 0.700, and 0.651, respectively.

Conclusions

The results demonstrate that electronic medical records contain latent information that can be used for risk stratification for neurological disorders. In particular, patient-reported outcomes, sleep assessments, falls data, additional disease diagnoses, and longitudinal changes in patient health, such as weight change, are important predictors.

Tanshinone IIA, the key compound in Salvia miltiorrhiza, improves cognitive impairment by upregulating Aβ-degrading enzymes in APP/PS1 mice

In Alzheimer's disease (AD), amyloid-beta (Aβ) plays a crucial role in pathogenesis. Clearing Aβ from the brain is considered as a key therapeutic strategy. Previous studies indicated that Salvia miltiorrhiza (Danshen) could protect against AD. However, the main anti-AD components in Danshen and their specific mechanisms are not clear. In this study, pharmacological network analysis indicated that Tanshinone IIA (Tan IIA) was identified as the key active compound in Danshen contributing to protect against AD. Then, APP/PS1 double transgenic mice were employed to examine the neuroprotective effect of Tan IIA. APP/PS1 mice (age, 6 months) were administered (10 and 20 mg/kg) for 8 weeks. Tan IIA improved learning and anxiety behaviors in APP/PS1 mice. Furthermore, Tan IIA reduced oxidative stress, inhibited neuronal apoptosis, improved cholinergic nervous system and decreased endoplasmic reticulum stress in the brain of APP/PS1 mice. Moreover, Tan IIA treatment reduced the level of Aβ. Molecular docking result showed that Tan IIA might block AD by upregulating Aβ-degrading enzymes. Western blot results confirmed that the expressions of insulin degrading enzymes (IDE) and neprilysin (NEP) were significantly increased after Tan IIA treatment, which demonstrated that Tan IIA improved AD by increasing Aβ-degrading enzymes.

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

Background

A timely diagnosis of dementia can be beneficial for providing good support, treatment, and care, but the diagnostic rate remains unknown and is probably low.

Objective

To determine the dementia diagnostic rate and to describe factors associated with diagnosed dementia.

Methods

This registry linkage study linked information on research-based study diagnoses of all-cause dementia and subtypes of dementias, Alzheimer's disease, and related dementias, in 1,525 participants from a cross-sectional population-based study (HUNT4 70+) to dementia registry diagnoses in both primary-care and hospital registries. Factors associated with dementia were analyzed with multiple logistic regression.

Results

Among those with research-based dementia study diagnoses in HUNT4 70+, 35.6% had a dementia registry diagnosis in the health registries. The diagnostic rate in registry diagnoses was 19.8% among home-dwellers and 66.0% among nursing home residents. Of those with a study diagnosis of Alzheimer's disease, 35.8% (95% confidence interval (CI) 32.6-39.0) had a registry diagnosis; for those with a study diagnosis of vascular dementia, the rate was 25.8% (95% CI 19.2-33.3) and for Lewy body dementias and frontotemporal dementia, the diagnosis rate was 63.0% (95% CI 48.7-75.7) and 60.0% (95% CI 43.3-75.1), respectively. Factors associated with having a registry diagnosis included dementia in the family, not being in the youngest or oldest age group, higher education, more severe cognitive decline, and greater need for help with activities of daily living.

Conclusions

Undiagnosed dementia is common, as only one-third of those with dementia are diagnosed. Diagnoses appear to be made at a late stage of dementia.

Protocol for the Tallaght University Hospital Institute for Memory and Cognition-Biobank for Research in Ageing and Neurodegeneration

INTRODUCTION

Alzheimer's disease and other dementias affect >50 million individuals globally and are characterised by broad clinical and biological heterogeneity. Cohort and biobank studies have played a critical role in advancing the understanding of disease pathophysiology and in identifying novel diagnostic and treatment approaches. However, further discovery and validation cohorts are required to clarify the real-world utility of new biomarkers, facilitate research into the development of novel therapies and advance our understanding of the clinical heterogeneity and pathobiology of neurodegenerative diseases.

METHODS AND ANALYSIS

The Tallaght University Hospital Institute for Memory and Cognition Biobank for Research in Ageing and Neurodegeneration (TIMC-BRAiN) will recruit 1000 individuals over 5 years. Participants, who are undergoing diagnostic workup in the TIMC Memory Assessment and Support Service (TIMC-MASS), will opt to donate clinical data and biological samples to a biobank. All participants will complete a detailed clinical, neuropsychological and dementia severity assessment (including Addenbrooke's Cognitive Assessment, Repeatable Battery for Assessment of Neuropsychological Status, Clinical Dementia Rating Scale). Participants undergoing venepuncture/lumbar puncture as part of the clinical workup will be offered the opportunity to donate additional blood (serum/plasma/whole blood) and cerebrospinal fluid samples for longitudinal storage in the TIMC-BRAiN biobank. Participants are followed at 18-month intervals for repeat clinical and cognitive assessments. Anonymised clinical data and biological samples will be stored securely in a central repository and used to facilitate future studies concerned with advancing the diagnosis and treatment of neurodegenerative diseases.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the St. James's Hospital/Tallaght University Hospital Joint Research Ethics Committee (Project ID: 2159), which operates in compliance with the European Communities (Clinical Trials on Medicinal Products for Human Use) Regulations 2004 and ICH Good Clinical Practice Guidelines. Findings using TIMC-BRAiN will be published in a timely and open-access fashion.

Health System Change for Alzheimer's Disease-Modifying Therapies in Canada: Beginning the Discussion

Alzheimer's disease (AD) is a neurodegenerative disorder that accounts for 60%-70% of patients with dementia, and it is estimated that over one million Canadians will be living with dementia by 2030. Disease-modifying therapies (DMTs) targeting the underlying pathophysiology of AD are currently in development. Several models have demonstrated that the potential arrival of Alzheimer's DMTs will most likely overwhelm the already-constrained Canadian healthcare system. Canada does not have a strategy to address the extensive requirements of using DMTs, including providing an early diagnosis of AD, confirming DMT eligibility via amyloid biomarkers, and conducting ongoing treatment monitoring. Thus, a multidisciplinary group of experts involved in AD care in Canada gathered to review (1) the current barriers to diagnosis and management of AD; (2) how existing clinic models, including those used in multiple sclerosis (MS), could be applied to address key barriers in AD; and (3) how to design and implement optimal care pathways in the future. The actions outlined in this review will help clinicians and healthcare systems improve readiness to integrate the use of disease-modifying therapies in Alzheimer's disease, if such therapies are approved in Canada.

Healthcare utilization prior to a diagnosis of young-onset Alzheimer's disease: a nationwide nested case-control study

OBJECTIVE

Our aim was to identify changes in healthcare utilization prior to a young-onset Alzheimer's disease diagnosis.

METHODS

In a retrospective incidence density matched nested case-control study using national health registers, we examined healthcare utilization for those diagnosed with young-onset Alzheimer's disease in Danish memory clinics during 2016-2018 compared with age- and sex-matched controls. Negative binomial regression analysis produced contact rate ratios.

RESULTS

The study included 1082 young-onset Alzheimer's disease patients and 3246 controls. In the year preceding diagnosis, we found increased contact rate ratios for all types of contacts except physiotherapy. Contact rate ratios for contacts with a general practitioner were significantly increased also > 1-5 and > 5-10 years before diagnosis. The highest contact rate ratios were for psychiatric emergency contacts (8.69, 95% CI 4.29-17.62) ≤ 1 year before diagnosis.

INTERPRETATION

Results demonstrate that young-onset Alzheimer's disease patients have increased healthcare utilization from 5 to 10 years prior to diagnosis. Awareness of specific alterations in health-seeking behaviour may help healthcare professionals provide timely diagnoses.

The electronic health record Risk of Alzheimer's and Dementia Assessment Rule (eRADAR) Brain Health Trial: Protocol for an embedded, pragmatic clinical trial of a low-cost dementia detection algorithm

BACKGROUND

About half of people living with dementia have not received a diagnosis, delaying access to treatment, education, and support. We previously developed a tool, eRADAR, which uses information in the electronic health record (EHR) to identify patients who may have undiagnosed dementia. This paper provides the protocol for an embedded, pragmatic clinical trial (ePCT) implementing eRADAR in two healthcare systems to determine whether an intervention using eRADAR increases dementia diagnosis rates and to examine the benefits and harms experienced by patients and other stakeholders.

METHODS

We will conduct an ePCT within an integrated healthcare system and replicate it in an urban academic medical center. At primary care clinics serving about 27,000 patients age 65 and above, we will randomize primary care providers (PCPs) to have their patients with high eRADAR scores receive targeted outreach (intervention) or usual care. Intervention patients will be offered a "brain health" assessment visit with a clinical research interventionist mirroring existing roles within the healthcare systems. The interventionist will make follow-up recommendations to PCPs and offer support to newly-diagnosed patients. Patients with high eRADAR scores in both study arms will be followed to identify new diagnoses of dementia in the EHR (primary outcome). Secondary outcomes include healthcare utilization from the EHR and patient, family member and clinician satisfaction assessed through surveys and interviews.

CONCLUSION

If this pragmatic trial is successful, the eRADAR tool and intervention could be adopted by other healthcare systems, potentially improving dementia detection, patient care and quality of life.

Delivery of Neuropsychological Interventions for Adult and Older Adult Clinical Populations: An Australian Expert Working Group Clinical Guidance Paper

Delivery of neuropsychological interventions addressing the cognitive, psychological, and behavioural consequences of brain conditions is increasingly recognised as an important, if not essential, skill set for clinical neuropsychologists. It has the potential to add substantial value and impact to our role across clinical settings. However, there are numerous approaches to neuropsychological intervention, requiring different sets of skills, and with varying levels of supporting evidence across different diagnostic groups. This clinical guidance paper provides an overview of considerations and recommendations to help guide selection, delivery, and implementation of neuropsychological interventions for adults and older adults. We aimed to provide a useful source of information and guidance for clinicians, health service managers, policy-makers, educators, and researchers regarding the value and impact of such interventions. Considerations and recommendations were developed by an expert working group of neuropsychologists in Australia, based on relevant evidence and consensus opinion in consultation with members of a national clinical neuropsychology body. While the considerations and recommendations sit within the Australian context, many have international relevance. We include (i) principles important for neuropsychological intervention delivery (e.g. being based on biopsychosocial case formulation and person-centred goals); (ii) a description of clinical competencies important for effective intervention delivery; (iii) a summary of relevant evidence in three key cohorts: acquired brain injury, psychiatric disorders, and older adults, focusing on interventions with sound evidence for improving activity and participation outcomes; (iv) an overview of considerations for sustainable implementation of neuropsychological interventions as 'core business'; and finally, (v) a call to action.

Using a dual-stream attention neural network to characterize mild cognitive impairment based on retinal images

Mild cognitive impairment (MCI) is a critical transitional stage between normal cognition and dementia, for which early detection is crucial for timely intervention. Retinal imaging has been shown as a promising potential biomarker for MCI. This study aimed to develop a dual-stream attention neural network to classify individuals with MCI based on multi-modal retinal images. Our approach incorporated a cross-modality fusion technique, a variable scale dense residual model, and a multi-classifier mechanism within the dual-stream network. The model utilized a residual module to extract image features and employed a multi-level feature aggregation method to capture complex context information. Self-attention and cross-attention modules were utilized at each convolutional layer to fuse features from optical coherence tomography (OCT) and fundus modalities, resulting in multiple output losses. The neural network was applied to classify individuals with MCI, Alzheimer's disease, and control participants with normal cognition. Through fine-tuning the pre-trained model, we classified community-dwelling participants into two groups based on cognitive impairment test scores. To identify retinal imaging biomarkers associated with accurate prediction, we used the Gradient-weighted Class Activation Mapping technique. The proposed method achieved high precision rates of 84.96% and 80.90% in classifying MCI and positive test scores for cognitive impairment, respectively. Notably, changes in the optic nerve head on fundus photographs or OCT images among patients with MCI were not used to discriminate patients from the control group. These findings demonstrate the potential of our approach in identifying individuals with MCI and emphasize the significance of retinal imaging for early detection of cognitive impairment.

Documentation of cognitive impairment screening amongst older hospitalised Australians: a prospective clinical record audit

BACKGROUND

Failure to detect cognitive impairment (CI) in hospitalised older inpatients has serious medical and legal implications, including for the implementation of care planning. This mixed methods study aimed to determine amongst hospital in-patients aged ≥ 65 years: (1) Rates of documentation of screening for CI, including the factors associated with completion of screening; (2) Rates of undocumented CI amongst patients who had not received screening during their admission; (3) Healthcare provider practices and barriers related to CI screening.

METHODS

A mixed methods study incorporating a clinical audit and interviews with healthcare providers was conducted at one Australian public hospital. Patients were eligible for inclusion if they were aged 65 years and older and were admitted to a participating ward for a minimum of 48 h. Patient characteristics, whether CI screening had been documented, were extracted using a template. Patients who had not been screened for CI completed the Montreal Cognitive Assessment (MoCA) to determine cognitive status. Interviews were conducted with healthcare providers to understand practices and barriers to screening for CI.

RESULTS

Of the 165 patients included, 34.5% (n = 57) had screening for CI documented for their current admission. Patients aged > 85 years and those with two or more admissions had greater odds of having CI screening documented. Among patients without CI screening documented, 72% (n = 78) were identified as cognitively impaired. While healthcare providers agreed CI screening was beneficial, they identified lack of time and poor knowledge as barriers to undertaking screening.

CONCLUSIONS

CI is frequently unrecognised in the hospital setting which is a missed opportunity for the provision of appropriate care. Future research should identify feasible and effective strategies to increase implementation of CI screening in hospitals.

Developing cognitive workload and performance evaluation models using functional brain network analysis

Cognition, defined as the ability to learn, remember, sustain attention, make decisions, and solve problems, is essential in daily activities and in learning new skills. The purpose of this study was to develop cognitive workload and performance evaluation models using features that were extracted from Electroencephalogram (EEG) data through functional brain network and spectral analyses. The EEG data were recorded from 124 brain areas of 26 healthy participants conducting two cognitive tasks on a robot simulator. The functional brain network and Power Spectral Density features were extracted from EEG data using coherence and spectral analyses, respectively. Participants reported their perceived cognitive workload using the SURG-TLX questionnaire after each exercise, and the simulator generated actual performance scores. The extracted features, actual performance scores, and subjectively assessed cognitive workload values were used to develop linear models for evaluating performance and cognitive workload. Furthermore, the Pearson correlation was used to find the correlation between participants' age, performance, and cognitive workload. The findings demonstrated that combined EEG features retrieved from spectral analysis and functional brain networks can be used to evaluate cognitive workload and performance. The cognitive workload in conducting only Matchboard level 3, which is more challenging than Matchboard level 2, was correlated with age (0.54, p-value = 0.01). This finding may suggest playing more challenging computer games are more helpful in identifying changes in cognitive workload caused by aging. The findings could open the door for a new era of objective evaluation and monitoring of cognitive workload and performance.

Health economic analysis of the integrated cognitive assessment tool to aid dementia diagnosis in the United Kingdom

Objectives

The aim of this study was to develop a comprehensive economic evaluation of the integrated cognitive assessment (ICA) tool compared with standard cognitive tests when used for dementia screening in primary care and for initial patient triage in memory clinics.

Methods

ICA was compared with standard of care comprising a mixture of cognitive assessment tools over a lifetime horizon and employing the UK health and social care perspective. The model combined a decision tree to capture the initial outcomes of the cognitive testing with a Markov structure that estimated long-term outcomes of people with dementia. Quality of life outcomes were quantified using quality-adjusted life years (QALYs), and the economic benefits were assessed using net monetary benefit (NMB). Both costs and QALYs were discounted at 3.5% per annum and cost-effectiveness was assessed using a threshold of £20,000 per QALY gained.

Results

ICA dominated standard cognitive assessment tools in both the primary care and memory clinic settings. Introduction of the ICA tool was estimated to result in a lifetime cost saving of approximately £123 and £226 per person in primary care and memory clinics, respectively. QALY gains associated with early diagnosis were modest (0.0016 in primary care and 0.0027 in memory clinic). The net monetary benefit (NMB) of ICA introduction was estimated at £154 in primary care and £281 in the memory clinic settings.

Conclusion

Introduction of ICA as a tool to screen primary care patients for dementia and perform initial triage in memory clinics could be cost saving to the UK public health and social care payer.

Normative Data for a Neuropsychological Test Battery in the French Aging Population: 20-Year Follow-Up From the "PROgnostic OF Cardiovascular and Cerebrovascular Events" Study

OBJECTIVE

The study aimed to present relevant norms for the evaluation of pathological aging in the French population over a 20-year period, utilizing the "PROgnostic OF cardiovascular and cerebrovascular events" test and questionnaire.

METHODS

Three neuropsychological evaluations were administered over 20 years with 929 participants at the first cognitive evaluation (62-69 years old), 631 at the second (71-78 years old), and 293 at the third (81-88 years old). The tests and questionnaires were administered in the following order: McNair's Cognitive Complaints Questionnaire, Depression Questionnaire of Pichot, Mini Mental State Examination, Free and Cued Selective Reminding test, Benton Visual Retention Test, Digit-Symbol Substitution Test of the WAIS-III, Trail Making Test, Stroop Test, Verbal Fluency, and the Similarities subtest of the WAIS-III.

RESULTS

Normative data were presented at three time points of the repeated evaluation over 20 years (62-69 years, 71-78 years, and 81-88 years) and four educational levels (no diploma, primary school certificate, certificate of professional aptitude, and baccalaureate and above). The data showed a significant effect of educational level in all neuropsychological tests regardless of age. Gender primarily affected memory, Stroop scores, and Similarities scores.

CONCLUSION

This study highlights the importance of educational level and gender in the evaluation of the memory and executive function of elderly persons. Furthermore, the presented norms consider the self-report cognitive complaints and depression symptoms over a long period of life.

Paving the Way for Predicting the Progression of Cognitive Decline: The Potential Role of Machine Learning Algorithms in the Clinical Management of Neurodegenerative Disorders

Alzheimer's disease (AD) is the most common form of neurodegenerative disorder. The prodromal phase of AD is mild cognitive impairment (MCI). The capacity to predict the transitional phase from MCI to AD represents a challenge for the scientific community. The adoption of artificial intelligence (AI) is useful for diagnostic, predictive analysis starting from the clinical epidemiology of neurodegenerative disorders. We propose a Machine Learning Model (MLM) where the algorithms were trained on a set of neuropsychological, neurophysiological, and clinical data to predict the diagnosis of cognitive decline in both MCI and AD patients.

METHODS

We built a dataset with clinical and neuropsychological data of 4848 patients, of which 2156 had a diagnosis of AD, and 2684 of MCI, for the Machine Learning Model, and 60 patients were enrolled for the test dataset. We trained an ML algorithm using RoboMate software based on the training dataset, and then calculated its accuracy using the test dataset.

RESULTS

The Receiver Operating Characteristic (ROC) analysis revealed that diagnostic accuracy was 86%, with an appropriate cutoff value of 1.5; sensitivity was 72%; and specificity reached a value of 91% for clinical data prediction with MMSE.

CONCLUSION

This method may support clinicians to provide a second opinion concerning high prognostic power in the progression of cognitive impairment. The MLM used in this study is based on big data that were confirmed in enrolled patients and given a credibility about the presence of determinant risk factors also supported by a cognitive test score.

Expected and diagnosed rates of mild cognitive impairment and dementia in the U.S. Medicare population: observational analysis

BACKGROUND

With the emergence of disease-modifying Alzheimer's treatments, timely detection of early-stage disease is more important than ever, as the treatment will not be indicated for later stages. Contemporary population-level data for detection rates of mild cognitive impairment (MCI), the stage at which treatment would ideally start, are lacking, and detection rates for dementia are only available for subsets of the Medicare population. We sought to compare documented diagnosis rates of MCI and dementia in the full Medicare population with expected rates based on a predictive model.

METHODS

We performed an observational analysis of Medicare beneficiaries aged 65 and older with a near-continuous enrollment over a 3-year observation window or until death using 100% of the Medicare fee-for-service or Medicare Advantage Plans beneficiaries from 2015 to 2019. Actual diagnoses for MCI and dementia were derived from ICD-10 codes documented in those data. We used the 2000-2016 data of the Health and Retirement Study to develop a prediction model for expected diagnoses for the included population. The ratios between actually diagnosed cases of MCI and dementia over number of cases expected, the observed over expected ratio, reflects the detection rate.

RESULTS

Although detection rates for MCI cases increased from 2015 to 2019 (0.062 to 0.079), the results mean that 7.4 of 8 million (92%) expected MCI cases remained undiagnosed. The detection rate for MCI was 0.039 and 0.048 in Black and Hispanic beneficiaries, respectively, compared with 0.098 in non-Hispanic White beneficiaries. Individuals dually eligible for Medicare and Medicaid had lower estimated detection rates than their Medicare-only counterparts for MCI (0.056 vs 0.085). Dementia was diagnosed more frequently than expected (1.086 to 1.104) from 2015 to 2019, mostly in non-Hispanic White beneficiaries (1.367) compared with 0.696 in Black beneficiaries and 0.758 in Hispanic beneficiaries.

CONCLUSIONS

These results highlight the need to increase the overall detection rates of MCI and of dementia particularly in socioeconomically disadvantaged groups.

Dementia: recognition and cognitive testing in community and primary care settings

Dementia is an umbrella term used to describe a group of symptoms characterised by behavioural changes, as well as loss of cognitive and social functioning brought about by progressive neurological disorders. There are approximately 944 000 people living with dementia in the UK and estimates indicate this will increase to over 2 million by 2051. Dementia, if left undiagnosed, can have an insidious and harmful impact on the people and their families who are affected by it. A timely diagnosis can be made when a person with a possible dementia comes to the attention of clinicians due to concerns about changes in their cognition, behaviour, or functioning. Community nurses are well-placed to observe changes in their older patients, which may be indicative of early dementia. This paper uses a case study to illustrate possible early signs of dementia and discusses the recognition and initial cognitive tests that can be used in a primary care setting.

Understanding Barriers Along the Patient Journey in Alzheimer's Disease Using Social Media Data

INTRODUCTION

We speculated that social media data from Alzheimer's disease (AD) stakeholders (patients, caregivers, and clinicians) could identify barriers along the patient journey in AD, and that insights gained may help devise strategies to remove barriers, and ultimately improve the patient journey.

METHODS

Our sample was drawn from a repository of social media posts extracted from 112 public sources between January 1998 and December 2021 using natural language processing text-mining algorithms. The patient journey was classified into three phases: (1) early signs/experiences (Early Signs); (2) screening/assessment/diagnosis (Screening); and (3) treatment/management (Treatment). In the Early Signs phase, issues/challenges derived from a conceptual AD identification framework (ADIF) were examined. In subsequent phases, behavioral/psychiatric challenges, access/barriers to health care, screening/diagnostic methods, and symptomatic treatments for AD were identified. Posts were classified by AD stakeholder type or disease stage, if possible.

RESULTS

We identified 225,977 AD patient journey-related social media posts. Anxiety was a predominant issue/challenge in all patient journey phases. In the Screening and Treatment phases combined, access/barriers to care were described in 16% of posts; unwillingness/resistance to seeking care was a major barrier (≥ 75% of access-related posts across all stakeholders). Commonly identified structural barriers (e.g., affordability/cost, geography/transportation/distance) were more common in patient/caregiver posts than clinician posts. Among Screening-related posts, imaging/scans were commonly mentioned by all stakeholders; biomarkers were more commonly mentioned by patients than clinicians. Treatment-related concerns were identified in 17% of stakeholder-specified posts that named pharmacological agents/classes for the symptomatic management of AD.

CONCLUSION

This descriptive analysis of out-of-clinic experiences reflected in AD social media posts found that unwillingness/resistance to seeking care was a key barrier, followed by structural barriers to health care, such as affordability/cost. Insights from the lived experiences of AD stakeholders are valuable and highlight the need to improve the patient journey in AD and ease patient and caregiver burden.

Focus Group Study of Medical Stakeholders to Inform the Development of Resilient Together for Dementia: Protocol for a Postdiagnosis Live Video Dyadic Resiliency Intervention

BACKGROUND

Alzheimer disease and related dementias (ADRD) are increasingly common conditions that disrupt the lives of persons living with dementia and their spousal care partners. At the time of ADRD diagnoses, many couples experience challenges that produce emotional distress and relationship strain. At present, there are no interventions to address these challenges early after diagnoses to promote positive adjustment.

OBJECTIVE

The study protocol described here is part of the first phase of a larger program of research that aims to develop, adapt, and establish the feasibility of Resilient Together for Dementia (RT-ADRD), a novel dyadic skills-based intervention to be delivered over live video early after diagnosis, with the goal of preventing chronic emotional distress. This study will elicit and systematically summarize perspectives of ADRD medical stakeholders to inform the procedures (eg, recruitment and screening methods, eligibility, timing of intervention, and intervention delivery) of the first iteration of RT-ADRD prior to pilot-testing.

METHODS

We will recruit interdisciplinary medical stakeholders (eg, neurologists, social workers, neuropsychologists, care coordinators, and speech language pathologists) from academic medical center clinics in the departments treating persons living with dementia such as neurology, psychiatry, and geriatric medicine via flyers and word-of-mouth referrals from clinic directors and members of relevant organizations (eg, dementia care collaboratives and Alzheimer disease research centers). The participants will complete electronic screening and consent procedures. Consenting individuals will then participate in a 30- to 60-minute qualitative virtual focus group, held either via telephone or Zoom, using an interview guide designed to assess provider experiences with postdiagnosis clinical care and to gather feedback on the proposed RT-ADRD protocol. The participants will also have the opportunity to participate in an optional exit interview and web-based survey to gather additional feedback. Qualitative data will be analyzed using a hybrid inductive-deductive approach and the framework method for thematic synthesis. We will conduct approximately 6 focus groups with 4-6 individuals in each group (maximum N=30 individuals; until saturation is reached).

RESULTS

Data collection began in November 2022 and will continue through June 2023. We anticipate that the study will be completed by late 2023.

CONCLUSIONS

The results from this study will inform the procedures of the first live video RT-ADRD dyadic resiliency intervention focused on the prevention of chronic emotional and relational distress in couples shortly after ADRD diagnoses. Our study will allow us to gather comprehensive information from stakeholders on ways to best deliver our early prevention-focused intervention and gain detailed feedback on study procedures prior to further testing.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/45533.