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Summary: Background: Although dementia incidence has decreased in high-income countries, it is important to monitor the prevalence of dementia and identify potential underdiagnosis in population subgroups. This study provides the most up-to-date prevalence of dementia diagnosis in Sweden, by geographical regions and sociodemographic groups. Methods: We identified all individuals aged ≥62 years, registered and alive in Sweden at the end of 2022 (n = 2.48 million). Dementia diagnoses were identified using ICD-9/10 codes in the National Patient Register since 1987, as well as anti-dementia drug use from the Prescribed Drug Register since 2005. Findings: At the end of 2022, 3.7% (92,293/2,483,798) of people aged ≥62 years in Sweden had a dementia diagnosis from specialist care or drug prescriptions and varied from 0.6% in ages 62–69 to 14.8% in ages ≥90. The prevalence of cognitive impairment diagnosis was 2.5%. There was some geographical variation in the prevalence of dementia diagnosis, with a larger proportion of diagnoses coming from drug prescriptions than from specialist care in northern Sweden. While people born abroad and people without a close relative had a slightly higher prevalence of dementia diagnosis than Swedish born and those with close relatives, the prevalence was substantially lower for people living alone than for cohabiting individuals. Interpretation: Comparing case estimates from previous screening cohorts, our results suggest underdiagnosis of dementia in the general older population, particularly among people who live alone. In more rural areas with lower availability of memory clinics, primary care may play an important role in diagnosing older adults with dementia. Funding: Swedish Research Council for Health, Working Life and Welfare; Swedish Research Council; Region Stockholm.

BACKGROUND: We examined the sequences of clinical care leading to diagnoses of Alzheimer's disease and related dementias (ADRD) using electronic health records from a large academic medical center. METHODS: We included patients aged 65+ with their first ADRD diagnoses from January 1, 2014 to December 31, 2019. Using state sequence analysis, care sequences were defined by the ordering of healthcare utilizations occurred in the 2 years before ADRD diagnosis. RESULTS: Of 3621 patients (median age 80), nearly half followed a care sequence of having one primary care visit close to their ADRD diagnosis. Additional care sequences included periodic (n = 322, 8.9%) and multiple (n = 416, 11.5%) outpatient visits to primary care and having one (n = 395, 10.9%), multiple (n = 469, 13.0%), or highly frequent (n = 357, 10.7%) outpatient visits to other specialties. Patients' sociodemographic traits contributed to the variability in care sequences. CONCLUSIONS: Several distinct patterns of care leading to ADRD diagnoses were identified. Integrated care models are needed to promote early identification of ADRD. Highlights: Dementia patients followed distinct care pathways prior to their dementia diagnoses.Key sociodemographic traits contributed to the variation in the sequences of care.Racial differences in the sequencing of care were also found, but only in women. [ABSTRACT FROM AUTHOR]

Abstract Objective Although knowledge about the experience of being diagnosed with dementia is limited, with the expected rise in dementia’s prevalence in the coming decades, such knowledge is pivotal for the people diagnosed, their families, and healthcare planners. Thus, the aim of our study was to explore the experience of living with cognitive impairment and dementia and the impact of being diagnosed with dementia. Method A qualitative design was applied. Participants were recruited based on age-adjusted values below ​​threshold values on the Montreal Cognitive Assessment Scale (i.e. 70–79 years,

Alzheimer’s disease (AD) is a relatively common senile neurodegenerative disease and the main manifestation of senile dementia. In the pathological changes of AD, the asymmetry of the brain also changes. Therefore, finding an early diagnosis method of AD based on asymmetry is the key to the treatment of Alzheimer’s. Magnetic resonance (MR) imaging can quantitatively reflect the structural and functional changes of various tissues in the brain. It has the advantages of non-invasive, high spatial resolution, and non-radiation, and has been widely used in the early diagnosis of AD. In this work, asymmetric images were extracted from multiple brain MR images, and different morphological and texture features were extracted. By establishing a feature selection classification integration model, image features in the image were deeply fused to obtain higher and more stable recognition results than before. By filtering image samples, the corresponding sample feature matrix was obtained. Support vector machine was used for classification, and its classification accuracy had improved significantly compared with that before selection. In the experimental data of normal control group and AD group, the accuracy, sensitivity, and specificity of the feature selection algorithm were 93.34, 90.69, and 95.87%, respectively. In the normal control group and the mild cognitive impairment group, the accuracy, sensitivity, and specificity of the feature selection algorithm in this work were 85.31, 79.68, and 88.54%, respectively. On the whole, the classification accuracy of the feature selection algorithm in this work was much higher than that of other items. In addition, from the classification ability and distribution of asymmetric features, it can be seen that this asymmetric feature had a more significant consistent diagnostic role in clinical practice.

Abstract Background General practice offers good conditions to detect and provide care for dementia-related diseases. Nonetheless, the effectiveness of dementia care in general practice is repeatedly criticised. To date, few studies have attempted to form a comprehensive picture of the status quo of dementia care in general practice that focuses on GP perspectives of experience and action. The aim of this study was to identify potential strengths and weaknesses of GP-based dementia care, by means of combined consideration of relevant care and treatment dimensions (construct of ‘dementia sensitivity’). Methods Through an online poll, a total of 4,511 GPs who are active as treatment providers in Baden-Württemberg, Hesse, Rhineland-Palatinate and Saarland were surveyed between September 2022 and January 2023. In addition to the descriptive analysis, a T-test with independent samples was used to identify significant differences between two groups (interval-scaled or metric variables). Pearson’s chi-squared test (χ2) was used to analyze the percentage values. Two levels of significance were tested for (mean difference at p

Background: Objective measurement of regional cortical atrophy in individual patients would be a highly desirable adjunct for diagnosis of degenerative dementias. Objective: We hypothesized that increasing the resolution of magnetic resonance scans would improve the sensitivity of cortical atrophy detection for individual patients. Methods: 46 participants including 8 semantic-variant primary progressive aphasia (svPPA), seven posterior cortical atrophy (PCA), and 31 cognitively unimpaired participants underwent clinical assessment and 3.0T brain scans. SvPPA and PCA were chosen because there is overwhelming prior knowledge of the expected atrophy pattern. Two sets of T1-weighted images with 0.8 mm3 (HighRes) and conventional 1.0 mm3 (ConvRes) resolution were acquired. The cortical ribbon was segmented using FreeSurfer software to obtain surface-based thickness maps. Inter-sequence performance was assessed in terms of cortical thickness and sub-cortical volume reproducibility, signal-to-noise and contrast-to-noise ratios. For clinical cases, diagnostic effect size (Cohen's d) and lesion distribution (z-score and t-value maps) were compared between HighRes and ConvRes scans. Results: The HighRes scans produced higher image quality scores at 90 seconds extra scan time. The effect size of cortical thickness differences between patients and cognitively unimpaired participants was 15–20% larger for HighRes scans. HighRes scans showed more robust patterns of atrophy in expected regions in each and every individual patient. Conclusions: HighRes T1-weighted scans showed superior precision for identifying the severity of cortical atrophy in individual patients, offering a proof-of-concept for clinical translation. Studying svPPA and PCA, two syndromes with well-defined focal atrophy patterns, offers a method to clinically validate and contrast automated algorithms. [ABSTRACT FROM AUTHOR]

Background: General practice offers good conditions to detect and provide care for dementia-related diseases. Nonetheless, the effectiveness of dementia care in general practice is repeatedly criticised. To date, few studies have attempted to form a comprehensive picture of the status quo of dementia care in general practice that focuses on GP perspectives of experience and action. The aim of this study was to identify potential strengths and weaknesses of GP-based dementia care, by means of combined consideration of relevant care and treatment dimensions (construct of 'dementia sensitivity'). Methods: Through an online poll, a total of 4,511 GPs who are active as treatment providers in Baden-Württemberg, Hesse, Rhineland-Palatinate and Saarland were surveyed between September 2022 and January 2023. In addition to the descriptive analysis, a T-test with independent samples was used to identify significant differences between two groups (interval-scaled or metric variables). Pearson's chi-squared test (χ2) was used to analyze the percentage values. Two levels of significance were tested for (mean difference at p < 0.05 and p < 0.001). In the course of the analysis, there were particular differences with regard to the sociodemographic variables 'urban vs. rural doctors' and 'doctors with geriatric training vs. doctors with no geriatric training'. Therefore, a complete listing of these parameters is given in the tables. In addition, the factor analysis method was employed. Results: The respondents consider it important for GPs to provide care and support for dementia patients. The doctors express the desire to offer active support to patients and their family caregivers. At the same time, many GPs experience challenges and difficulties when it comes to practical diagnostic steps (in line with guidelines), the (early) identification of dementia and consistent disease management, including the anticipation of care and treatment needs. Moreover, it appears that a significant proportion of the sample has only limited confidence when it comes to review relevant help and support services. One consistent finding is that some doctors in urban practices who also have geriatric training show substantial increases in knowledge and information with regard to dementia care. Conclusions: In the light of the findings, it seems particularly advisable to strengthen the geriatric competence of GPs. Moreover, it seems to be essential to ensure that they are better informed about cooperation and support structures in the area of dementia care and better integrated into these. [ABSTRACT FROM AUTHOR]

Background: Hospitalization with heart failure (HF) may signal an increased risk of Alzheimer's disease and related dementias (ADRD). Nursing homes routinely assess cognition but the association of these results with new ADRD diagnosis in a population at high risk of ADRD is not known. Objective: To determine the association between nursing home cognitive assessment results and new diagnosis of dementia after heart failure hospitalization. Methods: This retrospective cohort study included Veterans hospitalized for HF and discharged to nursing homes, from 2010 to 2015, without a prior diagnosis of ADRD. We determined mild, moderate, or severe cognitive impairment using multiple items of the nursing home admission assessment. We used Cox regression to determine the association of cognitive impairment with new ADRD diagnosis during 365 days of follow-up. Results: The cohort included 7,472 residents, new diagnosis of ADRD occurred in 4,182 (56%). The adjusted hazard ratio of ADRD diagnosis was 4.5 (95% CI 4.2, 4.8) for the mild impairment group, 5.4 (95% CI 4.8, 5.9) for moderate impairment, and 4.0 (95% CI 3.2, 5.0) for severe impairment compared to the cognitively intact group. Conclusion: New ADRD diagnoses occurred in more than half of Veterans with HF admitted to nursing homes for post-acute care. [ABSTRACT FROM AUTHOR]

Background: Disparities in diagnosis persist among persons living with dementia (PLWD); most research on delayed diagnosis relies on medical records or administrative claims. This study aimed to identify factors that delay or facilitate dementia diagnoses in racial or ethnic minoritized PLWD and elicit care partner perspectives on timing and effects of diagnosis. Methods: Maryland‐based participants cared for a PLWD age 60 or older, self‐identified as Black/African/African‐American, Asian, or Hispanic/Latino, and spoke English. Nineteen care partner in‐depth, semi‐structured interviews were conducted and analyzed using conventional qualitative content analysis methods. Results: Biological, sociocultural, and environmental factors delayed dementia diagnosis. Memory loss was the most common early symptom, but the onset was often subtle or perceived as normal aging. Stigma and secrecy surrounding dementia influenced recognition and discussion of dementia among families and communities. Diagnoses were family‐initiated and started in primary care. Care partners were divided in their perceptions of diagnosis timeliness and whether earlier diagnosis would have changed outcomes. Family reactions to dementia diagnoses varied; most participants expressed a strong sentiment of service and duty to care for older family members. Participants overwhelmingly felt the benefits of obtaining a dementia diagnosis outweighed harms. Conclusions: Numerous factors affect dementia diagnosis in racial and ethnic minoritized PLWD. Normalization of brain health discussions and systematic, proactive discussion and detection of dementia in primary care may address multilevel barriers and facilitators to diagnosis. Systems‐level and community‐led public health interventions may also help address disparities in brain health education and dementia diagnosis. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNN), which have been proven to be effective computational methods for identifying pictures, are of special interest in neuroscience research due to their significance in identifying Alzheimer's disease (AD). The most prevalent form of dementia in the elderly community is AD. The necessity of swift pathology of AD identification by magnetic resonance imaging (MRI) persists. Many pre-processing techniques have converted three alternative projections of T1-weighted volumetric MRI scans into 2D space. Four CNN models utilizing transfer learning, i.e., VGG-19, Wide ResNet 50-2, GoogleNet, and Inception v3, employ pre-processed MRI for generating the outcome values that the proposed ensemble model would later combine. The proposed prediction model employs an ensemble approach to produce fuzzy rankings of the fundamental classification approaches using the Gompertz function and automatically integrates the base models' decision results to arrive at ultimate forecasts on the test instances for the stage of AD, i.e., mild demented, moderate demented, non demented, and very mild demented. The system's reliability is demonstrated by the framework's outstanding results on publicly accessible MRI datasets. Achieving an accuracy of 99.22%, recall of 99.53, precision of 99.69, f1-score of 99.61, and AUC of 98, the suggested ensemble performs better than the other underlying base classifier. When combined with additional medical examinations, the proposed ensemble model will be a useful and effective diagnostic tool for MRI scans for AD. [ABSTRACT FROM AUTHOR]

INTRODUCTION: We describe the development and feasibility of using an online consensus approach for diagnosing cognitive impairment and dementia in rural South Africa. METHODS: Cognitive assessments, clinical evaluations, and informant interviews from Cognition and Dementia in the Health and Aging in Africa Longitudinal Study (HAALSI Dementia) were reviewed by an expert panel using a web‐based platform to assign a diagnosis of cognitively normal, mild cognitive impairment (MCI), or dementia. RESULTS: Six hundred thirty‐five participants were assigned a final diagnostic category, with 298 requiring adjudication conference calls. Overall agreement between each rater's independent diagnosis and final diagnosis (via the portal or consensus conference) was 78.3%. A moderate level of agreement between raters' individual ratings and the final diagnostic outcomes was observed (average κ coefficient = 0.50). DISCUSSION: Findings show initial feasibility in using an online consensus approach for the diagnosis of cognitive impairment and dementia in remote, rural, and low‐resource settings. [ABSTRACT FROM AUTHOR]

Abstract INTRODUCTION We describe the development and feasibility of using an online consensus approach for diagnosing cognitive impairment and dementia in rural South Africa. METHODS Cognitive assessments, clinical evaluations, and informant interviews from Cognition and Dementia in the Health and Aging in Africa Longitudinal Study (HAALSI Dementia) were reviewed by an expert panel using a web‐based platform to assign a diagnosis of cognitively normal, mild cognitive impairment (MCI), or dementia. RESULTS Six hundred thirty‐five participants were assigned a final diagnostic category, with 298 requiring adjudication conference calls. Overall agreement between each rater's independent diagnosis and final diagnosis (via the portal or consensus conference) was 78.3%. A moderate level of agreement between raters’ individual ratings and the final diagnostic outcomes was observed (average κ coefficient = 0.50). DISCUSSION Findings show initial feasibility in using an online consensus approach for the diagnosis of cognitive impairment and dementia in remote, rural, and low‐resource settings.

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Including the 'voices' of people living with dementia in a meaningful way is pivotal in shaping local, national and international health and social dementia care research. The Alzheimer's Society (United Kingdom) funded Angela Project (2016–19) was aimed at improving the diagnosis and post-diagnostic support for younger people living with dementia. From the outset, the Project Team ensured that the knowledge and expertise of people living with a younger onset dementia was integral to all decisions taken in respect to overall project design, implementation, and dissemination processes. This was achieved by establishing two project public and patient involvement (PPI) forums; a London PPI Forum and a Bradford-based local PPI Hub. This paper describes how the two groups were formed; the format of the meetings; and the key points learnt by the Project Team from involving people with dementia in all aspects of developing and delivering the Angela Project. Ultimately, the aim is to demonstrate to other researchers in the dementia field how the perspectives of those with a diagnosis can be included in research studies in an active and meaningful way. [ABSTRACT FROM AUTHOR]

Background: The association between platelet endothelial cell adhesion molecule-1 (PECAM-1) with cerebral small-vessel disease and cognition in dementia-free subjects remains uninvestigated., Methods and Results: A prospective cohort of dementia-free subjects was recruited from memory clinics and followed up for 5 years. Annual neurocognitive assessments and twice-yearly brain magnetic resonance imaging scans were performed. Associations of baseline plasma PECAM-1 levels with cerebral small-vessel disease, cognitive decline (Montreal Cognitive Assessment scores and executive function Z scores), and incident dementia were evaluated. Of 213 subjects (aged 70.2±7.7 years, 51.2% men), median PECAM-1 levels were 0.790 (interquartile range, 0.645-0.955 ng/mL). Compared with the highest tertile, subjects within the lowest PECAM-1 tertile had greater cross-sectional white matter hyperintensity volume (β=4.84 [95% CI, 0.67-9.01]; P =0.023), age-related white matter change scores (β=1.39 [95% CI, 0.12-2.67]; P =0.033), and cerebral microbleeds (Adjusted risk ratio, 2.59 [95% CI, 1.19-5.62]; P =0.016). Of the 204 participants with follow-up data (median, 60.0 [interquartile range, 60.0-60.0] months), 24 (11.8%) developed incident dementia. Compared with the highest tertile, subjects within the lower tertiles of PECAM-1 had a higher risk of incident dementia (first tertile: adjusted hazard ratio [AHR], 4.52 [95% CI, 1.35-15.13]; P =0.024; second tertile: AHR, 3.28 [95% CI, 1.02-10.60]; P =0.047). The lowest PECAM-1 tertile was associated with greater progression of white matter hyperintensity volume (β=4.15 [95% CI, 0.06-8.24]; P =0.047), cerebral microbleeds (incident relative risk [IRR], 2.21 [95% CI, 1.05-4.65]; P =0.036), and decline in executive function (β=-0.45 [95% CI, -0.76 to -0.14]; P =0.004), and Montreal Cognitive Assessment (β=-1.32 [95% CI, -2.30 to -0.35]; P =0.008) scores., Conclusions: In dementia-free subjects, lower circulating PECAM-1 levels are associated with greater cerebral small-vessel disease progression and cognitive decline, thus warranting future study as a potential therapeutic target.

Background: Detecting cognitive impairment in Parkinson's disease (PD) is challenging due to diverse manifestations and outdated diagnostic criteria. Cognitive screening tools, as Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA), are adopted worldwide, but despite several cutoffs has been proposed for PD, no consensus has been reached, hindered by limited sample sizes, lack of validation, and inconsistent age- and education-adjustments., Objectives: Determine the optimal MMSE and MoCA cutoffs in a large PD cohort, spanning from normal cognition (PD-NC), mild cognitive impairment (PD-MCI) to dementia (PDD), and develop a decision tree model to assist physicians in cognitive workups., Methods: Our retrospective Italian multicenter study involves 1780 PD, cognitively diagnosed with a level-II assessment: PD-NC(n = 700), PD-MCI(n = 706), and PDD(n = 374). Optimal cutoffs (for raw scores) were determined through ROC analysis. Then, a machine learning approach-decision trees-was adopted to validate and analyze the possible inclusion of other relevant clinical features., Results: The decision tree model selected as primary feature a MMSE cutoff ≤24 to predict dementia, and a score ≤ 27 for PD-MCI. To enhance PD-MCIvs.PD-NC accuracy, it also recommends including a MoCA score ≤ 22 for PD-MCI, and > 22 for PD-NC. Age and education were not selected as relevant features for the cognitive workup. Both MoCA and MMSE cutoffs exhibited high sensitivity and specificity in detecting PD cognitive statues., Conclusions: For the first time, a clinical decision tree model based on robust MMSE and MoCA cutoffs has been developed, allowing to diagnose PD-MCI and/or PDD with a high accuracy and short administration time., Competing Interests: Declaration of competing interest The authors declare no competing financial interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Intravascular large B-cell lymphoma (IVLBCL) is a rare hematological malignancy where its development in the intravascular environment is the main characteristic. Despite its ability to affect multiple organic systems, there is a tropism for the central nervous system, which may be related to several clinical syndromes, making this condition a great mimic and consequently a diagnostic challenge. Rapidly progressive dementia may be one of the presenting phenotypes of IVLBCL. This case report aims to highlight the main red flags, such as sustained elevation of lactate dehydrogenase, organomegaly and specific lesions with vasculitis-like bleeding, all that can be used as clinical clues to direct the differential diagnosis. In addition, it reinforces the role of early brain biopsy in this context, since IVLBCL is a treatable disease., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Dementia is characterized by a decline in memory and thinking that is significant enough to impair function in activities of daily living. Patients seen in dementia specialty clinics are highly heterogenous with a variety of different symptoms that progress at different rates. Recent research has focused on finding data-driven subtypes for revealing new insights into dementia's underlying heterogeneity, rather than assuming that the cohort is homogenous. However, current studies on dementia subtyping have the following limitations: (i) focusing on AD-related dementia only and not examining heterogeneity within dementia as a whole, (ii) using only cross-sectional baseline visit information for clustering and (iii) predominantly relying on expensive imaging biomarkers as features for clustering. In this study, we seek to overcome such limitations, using a data-driven unsupervised clustering algorithm named SillyPutty, in combination with hierarchical clustering on cognitive assessment scores to estimate subtypes within a real-world clinical dementia cohort. We use a longitudinal patient data set for our clustering analysis, instead of relying only on baseline visits, allowing us to explore the ongoing temporal relationship between subtypes and disease progression over time. Results showed that subtypes with very mild or mild dementia were more heterogenous in their cognitive profiles and risk of disease progression., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Kumar et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: While Type 2 Diabetes Mellitus (T2DM) prevalence is increasing among younger individuals, few studies have examined how age at T2DM diagnosis relates to dementia risk in diabetic populations. We aimed to investigate the association between age at T2DM diagnosis and subsequent dementia risk, and to determine whether obesity moderates this relationship., Methods: We conducted a prospective cohort study using data from the Health and Retirement Study (2002-2016) matched with its 2003 Diabetes Mail-Out Survey. The study included 1,213 dementia-free adults aged ≥50 with diagnosed T2DM. Primary exposures were age at T2DM diagnosis (categorized as <50, 50-59, 60-69, and ≥70 years) and obesity status (BMI ≥30 kg/m2). The outcome was incident dementia, assessed using the Telephone Interview for Cognitive Status. Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs), adjusting for sociodemographic factors, health behaviors, health status, and diabetes medication use., Results: Over a median follow-up of 10 (interquartile range, 6-14) years, 216 (17.8%) participants developed dementia. Compared to participants diagnosed with T2DM at age ≥70 years, those diagnosed at younger ages had increased dementia risk: HR 1.70 (95% CI, 1.03-2.80) for 60-69 years, 1.72 (95% CI, 1.06-2.79) for 50-59 years, and 1.90 (95% CI, 1.14-3.18) for <50 years. Obesity significantly moderated this relationship, with obese individuals diagnosed with T2DM before age 50 showing the highest dementia risk (HR 3.05; 95% CI 1.23-7.56) compared to non-obese individuals diagnosed at ≥50 years., Conclusions: Younger age at diagnosis of T2DM was significantly associated with a higher risk of dementia, particularly among individuals with obesity. Interventions specifically targeting obesity may be more effective in preventing dementia for adults with a younger onset of T2DM., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright: © 2024 Qi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Mild cognitive impairment (MCI) is a major risk factor for delirium. Few studies with mid- to long-term follow-up periods have examined delirium, MCI, and the conversion of MCI to dementia. This prospective, longitudinal cohort study aims to assess the incidence of dementia after delirium onset in patients with MCI and to develop an artificial intelligence algorithm for predicting the conversion of MCI to dementia., Methods: A 30-day evaluation for delirium will be performed for adults aged ≥ 65 years diagnosed with MCI who score 18-23 on the Korean Mini-Mental State Exam. Individuals exhibiting delirium at least once will be classified into the delirium group and the remainder into the non-delirium group. Over 3 years, patients will undergo follow-ups for survival and conversion to dementia at 30-day intervals to analyze risk factors for delirium and clinical outcomes. Differences between the two groups will be analyzed using the chi-square and independent t-tests. Kaplan-Meier survival and Cox proportional hazard regression will be used to assess the effects on 30-day, 60-day, 12-month, 24-month, and 36-month mortality, whereas linear regression will be used to assess the length of stay at long-term care facilities and medical costs., Discussion: The results will emphasize the importance of preventing delirium in MCI patients, and preventive interventions can be strengthened., Trial Registration: NCT05113446 (ClinicalTrials.gov). Registered 9 November 2021 - Retrospectively registered., (© 2024. The Author(s).)

In a patient presenting with forgetfulness, history taking comprises asking questions pertaining to specific cognitive domains namely memory, language, executive function, visuospatial functions, and social cognition to characterize the clinical phenotype. The next step is to administer a standardized screening test for cognitive assessment, namely the Montreal Cognitive Assessment (MoCA)/mini mental status examination (MMSE). These have been validated in five Indian languages. Detailed lobar function tests to assess functions of frontal, temporal, parietal, and occipital lobes namely planning, set-shifting, recent and remote memory, apraxia, agnosia, cortical sensory loss, language, etc., are the final step to identify the possible subtype of dementia. Attention testing with random letter cancellation test must be performed at the outset, as an inattentive patient cannot complete rest of the examination. Clock drawing is a simple bedside test that can assess global cognitive functions by detecting deficits in attention, planning, right-left orientation, constructional ability, visuospatial orientation, and neglect., (© Journal of the Association of Physicians of India 2024.)

Introduction: People from minoritised ethnic groups are diagnosed with dementia later in the disease. We explored pathways that may determine the timing of diagnoses in a UK ethnically diverse, urban area., Methods: We conducted 61 semi-structured interviews: 10 community-dwelling older people from minoritised ethnic backgrounds with diagnosed and undiagnosed dementia (mean age = 72 years; males = 5/10), 30 family members (51; 10/30), 16 health or social care professionals (42; 3/15), 3 paid carers and 2 interpreters for people with dementia. We used reflexive thematic analysis and the Model of Pathways to Treatment to consider diagnostic delay., Findings: We identified three themes: (1) Cultural identity and practices shape responses: gendered expectations that families relieve elders of household roles reduce awareness or concern when functioning declines; expectations that religious practices are maintained mean problems doing so triggers help-seeking. Second-generation family members often held insider and outsider identities, balancing traditional and Western perspectives. (2) Becoming like a tourist: daily experiences became unfamiliar for people developing dementia in an adopted country, sometimes engendering a need to reconnect with a home country. For professionals and interpreters, translating meanings faithfully, and balancing relatives' and clients' voices, were challenging. (3) Naming and conceptualising dementia: the term dementia was stigmatised, with cultural nuances in how it was understood; initial presentations often included physical symptoms with cognitive concerns., Conclusion: Greater understanding of dilemmas faced by minoritised ethnic communities, closer collaboration with interpreters and workforce diversity could reduce time from symptom appraisal to diagnosis, and support culturally competent diagnostic assessments., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.)

In the course of several neurodegenerative conditions, the presence of a sensory alteration, even before the appearance of cognitive disorders or complaints concerning autonomy, can potentially lead to earlier diagnosis and more efficient management of these complex patients. The mechanisms underlying the association between sensory impairment and the risk of progression to dementia are increasingly better understood and should ultimately improve the accuracy of the diagnosis process for the most common neurodegenerative conditions, but also participate in the differential diagnosis between these conditions. Finally, early management of these sensory impairments offers a relatively easy way to modify patient's progression by delaying the onset of several symptoms during the progression towards a dementia syndrome.

Introduction: Approximately 2 million people in Italy are currently living with dementia or mild cognitive impairment (MCI), and 4 million are involved as family members or caregivers. Considering the significant impact of dementia, the Italian Ministry of Health entrusted the Italian National Institute of Health (Istituto Superiore di Sanità) with the development of a guideline within the Italian National Guideline System (Sistema Nazionale Linee Guida, SNLG) on the diagnosis and treatment of dementia and MCI. The main objective was to provide evidence-based recommendations aimed at reducing the variability and ensuring the appropriateness of clinical practices throughout the whole care process from identification and diagnosis to the end of life for people with dementia (PwD) or MCI and their families/caregivers., Methods: The GRADE-ADOLOPMENT approach was used to adopt, adapt and update the guideline developed by the National Institute for Health and Care Excellence in 2018 (NG97). The methodology was based on the Methodological Handbook produced by the SNLG. A multidisciplinary panel of 29 experts and four representatives of family members/caregivers discussed and approved 47 review questions. Of these, 34 questions were adopted from the NG97, and 13 were new questions, including 10 questions referring to MCI. Systematic literature reviews were performed for each question, and a team of methodological and clinical experts qualitatively assessed and summarised results from included studies based on the GRADE approach. To facilitate the implementation and dissemination of the contents of this guideline, a care pathway and a leaflet dedicated to PwD or MCI and their families/caregivers were also developed., Results: The literature review for this guideline included studies published up to November 2023. More than 1000 peer-reviewed publications were included, covering the following areas: (i) identification, diagnosis and post-diagnostic support; (ii) care models and care coordination; (iii) pharmacological interventions for cognitive symptoms; (iv) non-pharmacological interventions for cognitive symptoms; (v) non-cognitive symptoms, intercurrent illnesses and palliative care. The multidisciplinary panel discussed and approved 167 clinical practice recommendations and 39 research recommendations., Commentary: Italy's first National Guideline on dementia and MCI addresses diagnosis, treatment and care within the National Healthcare System. It includes recommendations on pharmacological and non-pharmacological approaches, and emphasises tailored interventions, comprehensive cognitive assessment, staff training and palliative care. The guideline also underlines the need to involve PwD in decision-making and supporting caregivers throughout the entire course of the disease., Conclusions: Structured strategies for the dissemination and implementation of the guideline will be defined within the Italian Fund for Alzheimer and other Dementias 2024-2026. An interactive care pathway and a leaflet dedicated to PwD and their carers are already available. The guideline will be updated starting January 2027, but early updates may be planned in case of breakthrough advancements., (© The Author(s) 2024. Published by Oxford University Press on behalf of the British Geriatrics Society.)

Cognitive decline in Parkinson's disease (PD) varies widely. While models to predict cognitive progression exist, comparing traditional probabilistic models to deep learning methods remains understudied. This study compares sequential modeling techniques to identify cognitive progression in individuals with and without PD. Using data from the Parkinson's Progression Marker Initiative, shallow Markov, deep recurrent (long short-term memory [LSTM]), and nonrecurrent (temporal fusion transformer [TFT]) models were compared to predict cognitive status over time. Cognitive status was categorized into normal cognition (NC), mild cognitive impairment (MCI), and dementia. Predictions were made annually for up to 3 years using clinical data, including demographics, cognitive assessments, PD severity, and medical history. Each approach was evaluated using inverse probability weighted (IPW-) F1 scores. An ensemble method combined outputs from the Markov, LSTM, and TFT models. The dataset included 917 individuals (53% PD; 30% at risk for PD; 17% Healthy Controls). The TFT model outperformed others across all annual periods (IPW-F1 = 0.468) compared to the Markov (IPW-F1 = 0.349) and LSTM (IPW-F1 = 0.414) models, with improved performance using an ensemble approach (IPW-F1 = 0.502). For MCI and dementia predictions, which were rarer occurrences compared to NC status (ratios: 50:8:1), the TFT model consistently outperformed competing models, achieving IPW-F1 scores of 0.496 and 0.533 for MCI and dementia, respectively. In conclusion, sequential deep learning models like TFT, which mitigate long-term memory loss and can interpret complex, high-dimensional data, perform best overall in predicting clinically important cognitive transitions. These methods should be further explored for predicting degenerative conditions., (© 2024 The Author(s). Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Introduction: Identifying people at high risk of Alzheimer's disease (AD) dementia allows for timely intervention, which, if successful, will result in preventing or delaying the onset of the disease., Methods: Utilizing data from the Chicago Health and Aging Project (CHAP; n = 2130), we externally evaluated four risk-prediction models for AD dementia, including Cardiovascular Risk Factors, Aging, and Dementia (CAIDE), Australian National University Alzheimer's Disease Risk Index (ANU-ADRI), Brief Dementia Screening Indicator (BDSI), and Dementia Risk Score (DRS), in Black or African American and White adults., Results: BDSI had the highest discriminate abilities for AD dementia (c-statistics of 0.79 in Black and 0.77 in White adults), followed by ANU-ADRI, within the age range and follow-up period of the original development cohort. CAIDE had the lowest discriminating power (c-statistic ≤0.55). With increasing follow-up periods (i.e., 10-15 years), the discrimination abilities for all models declined., Discussion: Because of racial disparities in AD dementia and longer preclinical and prodromal stages of disease development, race-specific models are needed to predict AD risk over 10 years., Highlights: Utilizing risk-prediction models to identify individuals at higher risk of Alzheimer's disease (AD) dementia could benefit clinicians, patients, and policymakers. Clinicians could enroll high-risk individuals in clinical trials to test new risk-modifiable treatments or initiate lifestyle modifications, which, if successful, would slow cognitive decline and delay the onset of the disease. Current risk-prediction models had good discriminative power during the first 6 years of follow-up but decreased with longer follow-up time. Acknowledging the longer preclinical phase of AD dementia development and racial differences in dementia risk, there is a need to develop race-specific risk-prediction models that can predict 10 or 20 years of risk for AD and related dementias., (© 2024 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Mild cognitive impairment (MCI) has been described as a transitional state between normal aging and dementia, which can be both identified and tracked over time from qualitative and/or quantitative perspectives. Each definition of MCI involves some subjective cognitive complaint, some level of objective cognitive impairment, and generally intact daily functioning. Progression to dementia is common on follow-up in MCI, but stability and reversion to normal cognition can also occur. Quantitative methods might allow health care providers to evaluate and follow the subtle declines in MCI, as well as examine possible benefits of interventions with this at-risk condition., (Copyright © 2024 Elsevier Inc. All rights reserved.)

People with dementia have an increased risk of hospitalization and mortality due to infections. We aimed to explore decision-making processes and interventions for detecting and managing suspected infections in people with dementia and involved actors and determinants. We conducted a scoping review, searching CINAHL and PubMed, and synthesized data through mapping and narratively. We identified 22 studies, based mostly on nursing homes and US data. Decision-making processes included recognition of infections based on observations of early signs and symptoms, actions when suspecting infections, and proxy/family involvement. Interventions included antimicrobial stewardship and other decision-support tools. Determinants included healthcare staff perceptions, and other system/person-related factors. Healthcare staff were the main actors, proxy/family were mentioned scarcely, and people with dementia only once. Our findings show scarcity of evidence on people with dementia and outside of the nursing homes. We highlight knowledge gaps and inform research shaping interventions for improving infection detection and management., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Mihaela Ivosevic reports financial support was provided by Novo Nordisk Foundation. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Motoric cognitive risk syndrome (MCR) is defined as the presence of slow gait-speed and subjective cognitive decline in older individuals without mobility disability or dementia. While some studies suggest that MCR is a pre-dementia syndrome and may help predict the risk of cognitive impairment and dementia, not all studies concur. The objective of this study is to comprehensively summarize and synthesize evidence to assess the association between MCR and cognitive impairment and dementia., Methods: Following a pre-specified protocol, two authors systematically searched PubMed, Embase, and The Cochrane Library from inception to 19 August 2024 for observational or randomized studies pertaining to the association between MCR and cognitive impairment and dementia. We favoured maximally adjusted hazards and odds ratios to determine the longitudinal and cross-sectional risk of cognitive impairment and dementia. We investigated for potential sources of heterogeneity and also conducted sensitivity and subgroup analyses by continent and the type of cognitive outcome. The quality of evidence was assessed using the Newcastle-Ottawa Scale (NOS) and the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) framework., Results: We included 20 studies comprising a combined cohort of 1206,782 participants, of which 17 studies were included in the quantitative analysis. The pooled analysis outlined that individuals with MCR exhibited 2.20-fold higher risk of cognitive impairment and dementia, compared to controls (RR=2.20; 95 %CI=1.91-2.53). These findings remained robust across all subgroup analyses, sensitivity analyses and assessments of publication bias., Conclusion: MCR may be considered a predictive factor for long-term cognitive impairment and dementia. This should be taken into consideration when clinically evaluating the risk of cognitive impairment and dementia but further research is required to lend greater clarity to this association., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Subjective cognitive decline (SCD) is considered a pre-symptomatic stage of dementia characterized by cognitive complaints. The ability of education to reduce the risk of dementia is well known. Our objective is to investigate the influence of education on the risk of progression from SCD to MCI or dementia., Methods: Prospective longitudinal studies of adults (≥50 years) with SCD evaluating progression to objective cognitive decline, MCI, or dementia were selected. Pooled estimates (random effects model) and 95 % confidence intervals were calculated, exploring heterogeneity. Standardized education differences, Odds Ratio, or Hazard Ratio between converters and non-converters were estimated., Results: The systematic review carried out showed that high education, as well as other cognitive reserve proxies, delays cognitive decline. The first meta-analysis showed a significant association of SCD with conversion in both high and low education strata. A second meta-analysis considering education as a continuous variable found that SCD converters showed two years less education than non-converters., Conclusions: Our results suggest that education has a delaying effect against cognitive decline progression. The presumed improvement in accurately detecting cognitive decline associated with better metacognitive skills in higher-educated SCD participants does not seem to neutralize the incremental risk of objective cognitive decline associated with lower educational attainment., Competing Interests: Declaration of Competing Interest The authors declare that they have no financial or personal relationships with other people or organizations that could inappropriately influence the work reported in this paper. The authors do not have any competing interests such as employment, consultancies, stock ownership, honoraria, paid expert testimony, patent applications/registrations, or grants or other funding that could be perceived as conflicts of interest in connection with this work. The authors confirm that there are no potential competing interests to disclose. Disclosure statement The authors have no conflicts of interest to report., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: Gait performance can provide valuable insights into cognitive functioning in older adult and may be used to screen for cognitive impairment. However, the optimal test condition and spatiotemporal parameter for accuracy have not yet been determined. This study aims to determine the gait measure with the highest accuracy identifying cognitive decline., Methods: A total of 711 participants were recruited, including 332 cognitively healthy individuals, 264 with mild cognitive impairment (MCI), and 115 with dementia, with a mean age of 72 years (interquartile range 69-76), and 43% (n = 307) of women. The participants underwent gait assessment in three different conditions, including a single task and dual tasks of counting backward by ones and naming animals., Results: Gait performance was deteriorated as cognitive impairment progressed. The gait test performed during naming animals condition was the most accurate in differentiating between cognitive groups. Specifically, the naming animals gait speed was more accurate in discriminating control participants from those with cognitive impairment (area under the curve [AUC] = 76.9% for MCI and 99.7% for people with dementia with control group as reference). The coefficient of stride length variability while naming animals was the most effective parameter in discriminating between MCI and dementia groups (AUC = 96.7%)., Conclusions: The naming animals dual-task gait test can be a valuable assessment for screening cognitive impairment in older adults, regardless of their cognitive abilities. The test is useful in clinical settings for subjects with a range of cognitive profiles., (© 2024 The Author(s). Journal of the American Geriatrics Society published by Wiley Periodicals LLC on behalf of The American Geriatrics Society.)

Objective: The main aim of our study is to know the sociodemographic, clinical, analytical, and functional variables that predict the probability of developing dementia in patients with delirium who attend the emergency room., Method: All patients with delirium (n=45) from the emergency room who were admitted to the Geriatrics service of the General University Hospital of Ciudad Real (HGUCR) in 2016-2018 and met the inclusion and exclusion criteria were included. Subsequently, we ran a bivariate and multivariate analysis of the variables that predicted a diagnosis of dementia at six months and a discriminant analysis., Results: 15.6% of patients presented dementia at six months of follow-up, 22.2% had developed cognitive impairment. We conducted a multivariate model (R2 Nagelkerke 0.459) for the probability of developing dementia, with elevated heart rate being the most crucial variable (OR=11.5). The model could excluded dementia with 100% accuracy. Finally, we achieved a discriminant function capable of correctly classifying 95.6% of the cases. It included the following variables of influence: pH, Lawton Brody index, calcium, urea, and heart rate., Conclusions: A few clinical and analytical variables that are easily detectable in the emergency room, especially tachycardia, could help us better identify those patients with delirium at higher risk of developing dementia, as well as formulate hypotheses about the variables involved in the development of dementia in patients with delirium., (Copyright © 2024 Sociedad Española de Médicos de Atención Primaria (SEMERGEN). Publicado por Elsevier España, S.L.U. All rights reserved.)

Background: Cognitive impairment can be caused by infections with various pathogens, including SARS-CoV-2. Research has yet to determine the true incidence and course of cognitive impairment in older adults following COVID-19. Furthermore, research has theorised that COVID-19 is associated with dementia progression and diagnosis but this association has yet to be fully described., Methods: A systematic review was registered in Prospero and conducted on the databases PubMed, Embase, Ovid, CENTRAL and Cochrane Library. Studies reporting cognitive impairment and dementia outcomes in post-acute and post-COVID-19 patients aged ≥65 years, and which included control data, were included in this review., Results: 15,124 articles were identified by the search strategy. After eliminating duplicate titles and completing title, abstracts and full-text review, 18 studies were included comprising of 412,957 patients with COVID-19 (46.63 % male) and 411,929 patients without COVID-19 (46.59 % male). The overall mean Montreal Cognitive Assessment (MoCA) score in COVID-19 patients was 23.34 out of 30 (95 % CI [22.24, 24.43]). indicating cognitive impairment. The overall proportion of patients identified as having new onset cognitive impairment was 65 % (95 % CI [44,81]). Subgroup analyses indicated that time since infection significantly improves overall MoCA score and reduces proportion of patients with cognitive impairment., Conclusion: This study indicates that cognitive impairment may be an important sequela of COVID-19. Further research with adequate sample sizes is warranted regarding COVID-19's association with new-onset dementia and dementia progression, and the effect of repeat infections. There is a need for development of diagnostic and management protocols for COVID-19 patients with cognitive impairment., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Informant report dementia severity staging measures, such as the Quick Dementia Rating System (QDRS) offer clinicians useful diagnostic and staging information. These measures also potentially avoid many of the pitfalls inherent in mental status examinations (e.g., cultural bias, educational bias, floor and ceiling effects). We derive cut points for the QDRS and comprehensively examine their classification accuracy in a large, diagnostically heterogeneous, rural, memory disorder clinic sample. Our findings suggest the QDRS may be helpful when used in the context of a comprehensive diagnostic and staging evaluation. When used in isolation, the QDRS is insufficiently accurate for diagnosis and staging of dementia.

Background: Dementia and hepatic encephalopathy (HE) have symptom overlap and are challenging to differentiate. The presence of undiagnosed cirrhosis may lead to missed opportunities to treat HE, which was found in a veterans database. This needs validation in a non-veteran cohort., Methods: A retrospective cohort study was conducted between 2009 and 2019 using national non-Veteran patient data from the multi-center TriNetX database. Participants included 68,807 patients with a dementia diagnosis at ≥2 visits, no prior diagnosis of cirrhosis, and with sufficient laboratory test results to calculate the Fibrosis-4 (FIB-4) index, which indicates liver disease. Prevalences of high FIB-4 scores (>2.67 and >3.25) were measured within the cohort, and associations between high FIB-4 and comorbidities/demographics were examined., Results: Within the cohort (44.7% male, 78.0% White, mean age 72.73 years (±11.09), 7.6% (n = 5815) had a FIB-4 index > 3.25 and 12.8% (n = 8683) had FIB-4 > 2.67. In multivariable logistic regression models, FIB-4 > 3.25 was associated with male gender (OR: 1.42 [1.33-1.51]), congestive heart failure (OR: 1.73 [1.59-1.87]), viral hepatitis (OR: 2.23 [1.84-2.68]), alcohol use disorder (OR: 1.39 [1.22-1.58]), and chronic kidney disease (OR: 1.38 [1.28-1.48]), and inversely associated with White race (OR: 0.76 [0.71-0.82]) and diabetes (OR: 0.82 [0.77-0.88]). Similar findings were associated with the FIB-4 > 2.67 threshold., Conclusion: The findings of this national cohort suggest that the FIB-4 index could be utilized to screen for potential undiagnosed cirrhosis in patients with dementia, and that hepatic encephalopathy might be misdiagnosed as dementia or cause worsening of cognitive function in patients with dementia., (Published by Elsevier Inc.)

The Revised Hasegawa Dementia Scale (HDS-R) is the most widely used instrument to screen for dementia in Japan and is similar to the Mini-Mental State Examination (MMSE). The development of a quicker and simpler screening tool, the Japanese Old Stories Cognitive Scale (JOSS), was previously reported. A total of 953 new outpatients from 8 memory clinics in Japan completed the JOSS, HDS-R, and MMSE at first visit. We investigated the relationship of JOSS score with both the total and individual domain scores on the HDS-R and MMSE. We found a significant relation between JOSS score and total HDS-R and MMSE scores. In addition, JOSS score was significantly related to scores on 8 of the 9 HDS-R domains and 7 of the 11 MMSE domains. We obtained regression lines for JOSS score versus HDS-R and MMSE scores. JOSS score could be useful for predicting HDS-R and MMSE scores and thus in estimating cognitive functioning., Competing Interests: Declaration of Conflicting InterestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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.

Objective: Cognitive impairment in Parkinson's disease (PD) can show a very heterogeneous trajectory among patients. Here, we explored the mechanisms involved in the expression and prediction of different cognitive phenotypes over 4 years., Methods: In 2 independent cohorts (total n = 475), we performed a cluster analysis to identify trajectories of cognitive progression. Baseline and longitudinal level II neuropsychological assessments were conducted, and baseline structural magnetic resonance imaging, resting electroencephalogram and neurofilament light chain plasma quantification were carried out. Linear mixed-effects models were used to study longitudinal changes. Risk of mild cognitive impairment and dementia were estimated using multivariable hazard regression. Spectral power density from the electroencephalogram at baseline and source localization were computed., Results: Two cognitive trajectories were identified. Cluster 1 presented stability (PD-Stable) over time, whereas cluster 2 showed progressive cognitive decline (PD-Progressors). The PD-Progressors group showed an increased risk for evolving to PD mild cognitive impairment (HR 2.09; 95% CI 1.11-3.95) and a marked risk for dementia (HR 4.87; 95% CI 1.34-17.76), associated with progressive worsening in posterior-cortical-dependent cognitive processes. Both clusters showed equivalent clinical and sociodemographic characteristics, structural magnetic resonance imaging, and neurofilament light chain levels at baseline. Conversely, the PD-Progressors group showed a fronto-temporo-occipital and parietal slow-wave power density increase, that was in turn related to worsening at 2 and 4 years of follow-up in different cognitive measures., Interpretation: In the absence of differences in baseline cognitive function and typical markers of neurodegeneration, the further development of an aggressive cognitive decline in PD is associated with increased slow-wave power density and with a different profile of worsening in several posterior-cortical-dependent tasks. ANN NEUROL 2024;96:981-993., (© 2024 The Author(s). Annals of Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Purpose: Dementia includes all the symptoms associated with declining mental and cognitive skills, resulting in an inability to perform daily activities., Objectives: We aimed to translate and adapt the Montréal Cognitive Assessment (MoCA) test into the Moroccan cultural context. We compared the sensitivity and specificity between MoCA and Mini-Mental State of Folstein (MMS) in the screening of dementia., Materials and Methods: The participants in this study were residents in the Fez-Meknes region and over 50 years old. We performed translation and adaptation of the English MoCA 8.1 version into all Moroccan languages: Darija, Tamazight in its three variants (Tachelhit, Tarifit, Atlas Tamazight), and Arabic. We validated Moroccan MoCA according to the Beaton et al. instructions., Results: The sensitivity, specificity, and alpha Cronbach of the MoCA test were 88.5, 93.8%, and 0.87, while they were 90.2, 90.8%, and 0.79 for the MMS test., Conclusion: The Moroccan MoCA test had high sensitivity, specificity, and internal reliability compared to the MMS test. The availability of the MoCA in the Moroccan language will be helpful in the screening of dementia and research studies in Morocco and other countries.

Background: Orthostatic hypotension (OH) is a common condition in Parkinson's disease (PD) with a possible link to cognitive decline., Objective: The aim was to explore the association between OH and PD-associated mild cognitive impairment (PD-MCI) and dementia (PDD) over 9 years in a population-based incident PD cohort., Methods: We prospectively followed up patients from PD diagnosis with serial blood pressure measurements, clinical examinations, and neuropsychological assessments. We defined OH using (1) consensus-based criteria and (2) clinically significant OH by mean arterial pressure (MAP) in standing position ≤75 mmHg. PD-MCI and PDD were diagnosed according to acknowledged criteria. We applied generalized estimating equations models to investigate associations between OH measurements and cognitive impairment over time. Weibull accelerated failure time regression models were used to study if early OH (≤3 years of PD diagnosis) accelerates the time to incident PD-MCI and PDD., Results: Of 186 enrolled patients, consensus-based OH affected 68.8%, clinically significant OH 33.9%, PD-MCI 60.8%, and PDD 31.2%. Consensus-based OH was associated with PD-MCI (odds ratio [OR]: 2.04, 95% confidence interval: 1.44-2.90, P < 0.001), whereas clinically significant OH was associated with both PD-MCI (OR: 1.95, 1.11-3.43, P = 0.020) and PDD (OR: 3.66, 1.95-6.86, P < 0.001). Early clinically significant OH, but not early consensus-based OH, reduced time to incident PD-MCI by 54% (P = 0.021) and time to PDD by 44% (P = 0.003) independently of potential confounders, including supine hypertension and cardiovascular disease., Conclusions: MAP in standing position emerged as a stronger predictor of cognitive decline than OH determined using consensus-based criteria. These findings have implications for both research and clinical practice., (© 2024 International Parkinson and Movement Disorder Society.)

Background: We aimed to develop risk tools for dementia, stroke, myocardial infarction (MI), and diabetes, for adults aged ≥ 65 years using shared risk factors., Methods: Data were obtained from 10 population-based cohorts (N = 41,755) with median follow-up time (years) for dementia, stroke, MI, and diabetes of 6.2, 7.0, 6.8, and 7.4, respectively. Disease-free participants at baseline were included, and 22 risk factors (sociodemographic, medical, lifestyle, laboratory biomarkers) were evaluated. Two risk tools (DemNCD and DemNCD-LR based on Fine and Gray sub-distribution and logistic regression [LR], respectively) were developed and validated. Predictive accuracies of these risk tools were assessed using Harrel's C-statistics and area under the curve (AUC) and 95% confidence interval (CI). Model calibration was conducted using Hosmer-Lemeshow goodness of fit test along calibration plots., Results: Both the DemNCD and DemNCD-LR resulted in similar predictive accuracy for each outcome. The overall AUC (95% CI) for dementia, stroke, MI, and diabetes risk tool were 0·68 (0·65, 0·70), 0·58 (0·54, 0·61), 0·65 (0·61, 0·68), and 0·68 (0·64, 0·72), respectively, for males. For females, these figures were 0·65 (0·63, 0·67), 0·55 (0·52, 0·57), 0·65 (0·62, 0·68), and 0·61 (0·57, 0·65)., Conclusions: The DemNCD is the first tool to predict both dementia and multiple cardio-metabolic diseases using comprehensive risk factors and provided similar predictive accuracy to existing risk tools. It has similar predictive accuracy as tools designed for single outcomes in this age-group. DemNCD has the potential to be used in community and clinical settings as it includes self-reported and routinely available clinical measures., (© 2024. The Author(s).)

Background: Cluster randomized trials (CRTs) are increasingly important for evaluating interventions embedded in health care systems. An essential parameter in sample size calculation to detect both overall and heterogeneous treatment effects for CRTs is the intra-cluster correlation coefficient (ICC) of both outcome and covariates of interest. However, obtaining advance estimates for the ICC can be challenging. When trial outcomes will be obtained from routinely collected data sources, there is an opportunity to obtain reliable ICC estimates in advance of the trial. Using USA national Medicare data, we estimated ICCs for a range of outcomes to inform the design of CRTs for people living with Alzheimer's and related dementias (ADRD)., Method: Data from 2018 Medicare Fee-for-Service beneficiaries, specifically, 1,898,812 individuals (≥ 65 years) with diagnosis of ADRD within 3436 hospital service areas (treated as clusters) and 306 hospital referral regions (treated as fixed strata), were used to calculate unadjusted and adjusted ICC estimates for three outcomes: death, any hospitalizations, and any emergency department (ED) visits and three covariates: age, race and sex. We present both overall and stratum-specific ICC estimates. We illustrate their use in sample size calculations for overall treatment effects as well as detecting treatment effect heterogeneity., Results: The unadjusted overall ICCs for death, hospitalizations, and ED visits were 0.001, 0.010, and 0.017 respectively. Stratum-specific ICCs varied widely across the 306 HRRs: median 0.001, 0.010 and 0.025 for death, hospitalizations, and ED visits respectively and 0.007, 0.001, and 0.080 for age, sex and race. An interactive R Shiny app is provided that allows users to retrieve estimates overlayed on a map of the USA., Conclusions: We presented both adjusted and unadjusted ICCs for outcomes as well as unadjusted ICCs for covariates of potential interest from population-level data in the USA and demonstrated how the estimates may be used in sample size calculations for CRTs in ADRD., (© 2024. The Author(s).)

Introduction: Clinical notes, biomarkers, and neuroimaging have proven valuable in dementia prediction models. Whether commonly available structured clinical data can predict dementia is an emerging area of research. We aimed to predict gold-standard, research-based diagnoses of dementia including Alzheimer's disease (AD) and/or Alzheimer's disease related dementias (ADRD), in addition to ICD-based AD and/or ADRD diagnoses, in a well-phenotyped, population-based cohort using a machine learning approach., Methods: Administrative healthcare data (k = 163 diagnostic features), in addition to census/vital record sociodemographic data (k = 6 features), were linked to the Cache County Study (CCS, 1995-2008)., Results: Among successfully linked UPDB-CCS participants (n = 4206), 522 (12.4%) had incident dementia (AD alone, AD comorbid with ADRD, or ADRD alone) as per the CCS "gold standard" assessments. Random Forest models, with a 1-year prediction window, achieved the best performance with an Area Under the Curve (AUC) of 0.67. Accuracy declined for dementia subtypes: AD/ADRD (AUC = 0.65); ADRD (AUC = 0.49). Accuracy improved when using ICD-based dementia diagnoses (AUC = 0.77)., Discussion: Commonly available structured clinical data (without labs, notes, or prescription information) demonstrate modest ability to predict "gold-standard" research-based AD/ADRD diagnoses, corroborated by prior research. Using ICD diagnostic codes to identify dementia as done in the majority of machine learning dementia prediction models, as compared to "gold-standard" dementia diagnoses, can result in higher accuracy, but whether these models are predicting true dementia warrants further research., (© 2024. The Author(s).)

Objective: In dementia research, the Driving Scenes test from the Neuropsychological Assessment Battery has been shown to relate to memory, dementia diagnosis, and functional impairment. The aim of the current study was to examine Driving Scenes and its component scores, and their relationships with cognition and daily functioning, in a mixed dementia clinic sample., Method: One hundred U.S. military veterans between the ages of 55 and 88 were administered a full neuropsychological protocol that included Driving Scenes., Results: The Driving Scenes score and its subscores were strongly related to memory skills, and there were additional subscore associations with language and visuospatial functions. Driving Scenes uniquely predicted reported bill payment difficulties and tendency to get lost while driving, which were not predicted by other performances across cognitive domains., Conclusion: Driving Scenes is a clinically and functionally relevant measure of memory. Although the Driving Scenes total score remains useful in dementia evaluations, component scores and error scores contribute additional practical information., (Published by Oxford University Press 2024.)

Objective: The number of computer-based cognitive tests has increased in recent years, but there is a need for tests focusing on the assessment of executive function (EF), as it can be crucial for the identification of early-onset neurodegenerative disorders. This study aims to examine the ability of the Flexible Attention Test (FAT), a new computer-based test battery for detecting executive dysfunction of early-onset cognitive impairment and dementia patients., Method: We analyzed the FAT subtask results in memory clinic patients with cognitive symptom onset at ≤65 years. The patients were divided into four groups: early onset dementia (EOD, n = 48), mild cognitive impairment due to neurological causes (MCI-n, n = 34), MCI due to other causes (MCI-o, n = 99), and subjective cognitive decline (SCD, n = 14). The test accuracy to distinguish EOD patients from other groups was examined, as well as correlations with pen-and-paper EF tests. We also reported the 12-months follow-up results., Results: The EOD and MCI-n patients performed significantly poorer (p ≤ .002) than those in the MCI-o and SCD groups in most of the FAT subtasks. The accuracies of the FAT subtasks to detect EOD from other causes were mainly moderate (0.34 ≤ area under the curve < 0.74). The FAT subtasks correlated logically with corresponding pen-and-paper EF tests (.15 ≤ r ≤ .75). No systematic learning effects were detected in the FAT performance at follow-up., Conclusions: The FAT appears to be a promising method for the precise evaluation of EF and applicable distinguishing early-onset neurodegenerative disorders from patients with other causes of cognitive problems., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Objective: The purpose of this retrospective archival study was to explore the clinical utility of the Judgment subtest of the Neuropsychological Assessment Battery (NAB) in older adults who were referred because of cognitive concerns. Specifically, we were interested in how NAB Judgment covaried with other measures of executive functioning., Method: 226 adults, aged 61-89 years (48% dementia, 35% mild cognitive impairment, 18% cognitively intact) completed NAB Judgment. They also completed Trail Making Test (TMT) A and B. In addition, Behavior Rating Inventory of Executive Function (BRIEF-A) informant and self-reports were obtained to measure executive functioning in daily life., Results: Scores on NAB Judgment did not correlate significantly with BRIEF-A informant ratings. However, there was a statistically significant correlation between BRIEF-A informant ratings and TMT B. Better performance on TMT B was associated with fewer informant concerns. Furthermore, subgroups with versus without informant BRIEF-A Metacognition indices in the range of impairment demonstrated a statistically significant difference on TMT B but not on Judgment., Conclusions: Executive functioning in older adults should not be assessed using NAB Judgment alone. Such an evaluation should be supplemented with other in-person tests as well as informant ratings of daily functioning., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)