Search

Abstract Many women experience impairment in cognitive function during perimenopause. These symptoms are often not attributed to perimenopause by women themselves, by family and friends, or by healthcare professionals. In this article, we present a case in which perimenopausal complaints were attributed to early dementia and discuss mechanisms contributing to the low level of awareness of perimenopausal symptoms amongst patients and clinicians. Stigma amongst women and healthcare professionals impairs the recognition of perimenopausal complaints, and consideration of treatment options by clinicians. We advocate raising awareness in patients and physicians with more education, and the incorporation of potential menopause-related symptoms in general clinical guidelines.

Introduction: Care for people with vascular cognitive impairment (VCI), like vascular dementia or post-stroke cognitive impairment, is provided by various healthcare professionals. People with VCI present in different settings like (acute) neurology, rehabilitation and dementia care, all with their own guidelines and workflow. We explored experiences and perspectives of healthcare professionals on care provision, organization and collaboration regarding care for people with VCI. Methods: We performed a qualitative focus group study in regions across the Netherlands. Focus groups were divided in three types: (i) primary care, (ii) secondary care and (iii) mixed focus groups with healthcare professionals from both settings. We included forty healthcare professionals across seven focus groups, including medical specialists, elderly care physicians, general practitioners, nurses, paramedics and case managers in dementia care. Inclusion ended when we reached thematic saturation, meaning new data did not provide additional (sub-)themes. Focus groups were audiotaped and transcribed verbatim. Transcripts were iteratively coded, recoded, analyzed and grouped into themes according to the inductive thematic analysis method by Braun & Clarke. Results: Three themes were identified. An overarching theme was “Knowledge and awareness of VCI.” Participants stated that the general public as well as healthcare professionals had insufficient knowledge of VCI. They agreed that awareness of the condition was a prerequisite for adequate care for people with VCI. The second theme was “Specific care.” Participants noted a lack of differentiation in current VCI care, while specific recommendations are needed for typical symptoms and fluctuations in functioning. Participants also highlighted the need to unburden informal caregivers, who struggle with symptoms like apathy or uncertainty of the disease course, described by one participant as a “no man's land”. The third theme was “Integrated care.” Current care for VCI was perceived as highly fragmented: various professionals provided a specific part, but a central lead or coordinator was often lacking. Participants proposed an integrated and transmural VCI-network. Discussion: More specific and integrated care is needed to accommodate people with VCI and informal caregivers, combining expertise from dementia and rehabilitation settings. Knowledge and awareness of VCI should be improved by providing (psycho-)education to professionals and the public.

The number of people living with dementia, such as Alzheimer's disease, is increasing worldwide. Persons with dementia often have a high risk of atherosclerotic cardiovascular disease and they are therefore theoretically eligible for treatment of hypertension and hyperlipidemia. However, in this population, beneficial and harmful effects of cardiovascular risk management (CVRM) may be different compared to older persons without cognitive impairment. Current CVRM guidelines are based on trials from which persons with dementia were excluded. In this narrative review, we will discuss how current guidelines can be translated to persons with dementia and which aspects should be taken into account when treating hypertension and hyperlipidemia to prevent major adverse cardiovascular events (MACE). Survival time is significantly shorter in persons with dementia. We therefore suggest that since the main goal of CVRM is prevention of MACE, first of all, the patient's life expectancy and treatment wishes should be evaluated. Risk assessment tools are to be used with care, as they tend to overestimate the 5- and 10-year risk of MACE and benefit from CVRM in the prevention of MACE in persons with dementia. When the clinician and patient have decided that treatment is initiated or intensified, patients should be closely monitored since they are at high risk for adverse drugs events and overtreatment due to the natural course of blood pressure in persons with dementia. In the event of intolerance or side effects, medication should be switched or withdrawn. For persons with dementia and limited life expectancy, deprescribing should be part of usual care.

Introduction: Research is lacking regarding the effect of cerebral small vessel disease (CSVD) on different domains of functioning and their interrelations. Network analyses provides a holistic overview of interrelationships between different variables. Therefore, we applied network analysis on data of older people with varying levels of CSVD and their cognitive, physical, emotional and daily functioning. Methods: We included participants (n=807) from the Amsterdam Aging Cohort. Inclusions criteria were a memory clinic visit including (i) comprehensive geriatric assessment, (ii) brain imaging and (iii) neuropsychological evaluation.CSVD was operationalized as White Matter Hyperintensities (WMH), according to the Fazekas scale, dividing the sample in three levels: no/mild WMH (Fazekas 0/1), moderate WMH (Fazekas 2) and severe WMH (Fazekas 3)Domains of functioning were operationalized as follows. Physical functioning: gait speed and handgrip strength (HGS). Cognitive functioning: composite z-scores in the domains memory, language, attention/speed and executive functioning. Daily functioning: Katz ADL and the Lawton iADL. Emotional functioning: Geriatric Depression Scale-15, Apathy (GDS-3A) and Depression (GDS-12D) subscales. Health related Quality of Life (hrQoL): EQ5D-VAS. We ran a network (mixed graphical model) to assess the associations between the domains of functioning. We tested whether these associations were different for different levels of CSVD in a moderated network model. Multiple regression, corrected for sex, age and education level, was used to assess the difference in domains of functioning between CSVD levels. Results: In the network model, more depressive and apathy symptoms are associated with lower hrQoL. Lower physical & cognitive functioning are associated with worse daily functioning (Figure). The moderated network did not significantly differ between CSVD levels. Yet, our multiple regression analyses did show differences that WMH severity is related with worse physical functioning, worse daily functioning, lower hrQoL, more apathy symptoms and lower cognitive functioning in the attention and language domains (Table). Discussion: Domains of functioning are highly connected in this older population, while CSVD is associated with worse functioning in all domains. This implicates that cognitive and emotional changes prevalent in CSVD (apathy, reduced speed) co-occur with worse daily functioning and decreased quality of life, warranting a holistic approach in clinical care.

Introduction: It is known that vascular damage is associated with decreased brain health. Therefore, the study VARIATION, focusing on vascular phenotypes in patients visiting a memory clinic, was launched as a substudy of the Amsterdam Ageing Cohort. The objective of this study is to assess micro and macrovascular function and damage in patients visiting the memory clinic and relate this to long term cognitive and functional outcomes. Here, we present preliminary baseline results of the first 51 participants. Methods: All patients underwent an extensive vascular assessment including blood pressure measurements (supine and standing), carotid pulse wave velocity, carotid stiffness index, intima media thickness, reactive hyperemia index (as a measure of microvascular function), estimated glomerular filtration rate, cerebral small vessel disease (WMH, lacunes, microbleeds) on 3T MRI, as well as cognitive and physical function measurements. Results: In this memory clinic population (N=51, mean (SD) age 80 (6), 31% women) 30% had subjective cognitive decline, 40% MCI, and 30% dementia. Both vascular dysfunction and damage was highly prevalent, with an impaired endothelial function of 35% (reactive hyperemia index 8.5 ms/). Mean (SD) systolic blood pressure was 138 ± 21 mmHg, and 33% had orthostatic hypotension. Furthermore, cerebral small vessel was highly prevalent on cerebral imaging, 55% of patients had Fazekas score >= 2, 20% had >= 3 microbleeds and lacunes were present in 18%. Discussion: In this preliminary results of VARIATION we presented an extensively vascular phenotyped memory-clinic cohort, with high prevalence of micro- and macrovascular damage. Data on if and how impaired vascular function is associated with cognitive and functional decline will follow.

Introduction: Globally, women with dementia have a higher disease burden than men with dementia. In addition, women with diabetes especially are at higher risk for cognitive impairment and dementia compared to men with diabetes. Differences in the influence of diabetes on the cerebral vasculature and brain structure may contribute to these sex-specific differences. We examined sex-specific patterns in the relationship between diabetes and brain structure, as well as diabetes and cognitive function. We aimed to investigate if women with diabetes have a higher incidence of cerebral vascular impairment compared to men, and whether this also translates in differences in cognitive function between men and women. Methods: In total, 893 patients [age 79 ± 6.6 years, 446 (50%) women] from the Amsterdam Ageing Cohort with available data on brain structure (assessed by an MRI or CT scan) and cognitive function and were included. All patients underwent a thorough standardized clinical and neuropsychological assessment (including tests on memory, executive functioning, processing speed, language). Brain structure abnormalities were quantified using visual scales, including lacunes, white matter hyperintensities, atrophy and microbleeds. Results: Cross-sectional multivariable regression analyses showed that diabetes was associated with increased incidence of cerebral lacunes and brain atrophy in women (OR 2.18 (1.00–4.72) but not in men. Furthermore, diabetes was associated with decreased executive function, processing speed and language in women [B −0.07 (0.00–0.13), −0.06 (0.02–0.10) and −0.07 (0.01–0.12) resp.] but not in men. These effects persisted when correcting for lifestyle factors, other cardiovascular diseases and cardiovascular risk factors, age and level of education. Discussion: in our cohort of elderly patients, diabetes is related to increased risk of having lacunes, brain atrophy and impaired cognitive function in women but not in men. Furthermore, diabetes is a significant risk factor for functional cognitive impairment in women, but not in men. Further research is required to understand the mechanisms behind this inequality, in terms of biological (sex) differences, as well as social (gender) differences, in order to achieve personalised care and improve preventive clinical practice for all patients.

Introduction: The prevalence of atherosclerotic cardiovascular diseases and its associated mortality are increasing worldwide. In persons with cognitive impairment, the potential benefits from treatment of hypertension and dyslipidaemia may be overestimated due to competing mortality risks related to cognitive impairment. We therefore aim to explore the association between cardiovascular risk and all-cause mortality in a memory clinic population, and whether this relation is modified by cognitive and physical performance. Methods: All patients from the Amsterdam Ageing Cohort who visited the memory clinic were included. Cardiovascular risk was assessed with the SCORE2-OP, a validated instrument to estimate 5- and 10-year risk for non-fatal myocardial infarction, non-fatal stroke and cardiovascular mortality in persons aged ≥70 years. A 10-year risk of

Abstract The key to stopping Alzheimer's disease (AD) lies in the pre‐dementia stages, with the goal to stop AD before dementia has started. We present the rationale and design of the ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) project, which aims to invest in personalized medicine for AD. ABOARD is a Dutch public–private partnership of 32 partners, connecting stakeholders from a scientific, clinical, and societal perspective. The 5‐year project is structured into five work packages on (1) diagnosis, (2) prediction, (3) prevention, (4) patient‐orchestrated care, and (5) communication and dissemination. ABOARD functions as a network organization in which professionals interact cross‐sectorally. ABOARD has a strong junior training program “Juniors On Board.” Project results are shared with society through multiple communication resources. By including relevant partners and involving citizens at risk, patients, and their care partners, ABOARD builds toward a future with personalized medicine for AD. Highlights ABOARD (A Personalized Medicine Approach for Alzheimer's Disease) is a public–private research project executed by 32 partners that functions as a network organization. Together, the project partners build toward a future with personalized medicine for Alzheimer's disease. Although ABOARD is a Dutch consortium, it has international relevance. ABOARD improves diagnosis, prediction, prevention, and patient‐orchestrated care.

IntroductionGlobally, women with dementia have a higher disease burden than men with dementia. In addition, women with diabetes especially are at higher risk for cognitive impairment and dementia compared to men with diabetes. Differences in the influence of diabetes on the cerebral vasculature and brain structure may contribute to these sex-specific differences. We examined sex-specific patterns in the relationship between diabetes and brain structure, as well as diabetes and cognitive function.MethodsIn total, 893 patients [age 79 ± 6.6 years, 446 (50%) women] from the Amsterdam Ageing Cohort with available data on brain structures (assessed by an MRI or CT scan) and cognitive function were included. All patients underwent a thorough standardized clinical and neuropsychological assessment (including tests on memory, executive functioning, processing speed, language). Brain structure abnormalities were quantified using visual scales.ResultsCross-sectional multivariable regression analyses showed that diabetes was associated with increased incidence of cerebral lacunes and brain atrophy in women (OR 2.18 (1.00–4.72) but not in men. Furthermore, diabetes was associated with decreased executive function, processing speed and language in women [B −0.07 (0.00–0.13), −0.06 (0.02–0.10) and −0.07 (0.01–0.12) resp.] but not in men.ConclusionsDiabetes is related to increased risk of having lacunes, brain atrophy and impaired cognitive function in women but not in men. Further research is required to understand the time trajectory leading up to these changes and to understand the mechanisms behind them in order to improve preventive health care for both sexes.

Differentiating between different types of neurodegenerative diseases is not only crucial in clinical practice when treatment decisions have to be made, but also has a significant potential for the enrichment of clinical trials. The purpose of this study is to develop a classification framework for distinguishing the four most common neurodegenerative diseases, including Alzheimer's disease, frontotemporal lobe degeneration, Dementia with Lewy bodies and vascular dementia, as well as patients with subjective memory complaints. Different biomarkers including features from images (volume features, region-wise grading features) and non-imaging features (CSF measures) were extracted for each subject. In clinical practice, the prevalence of different dementia types is imbalanced, posing challenges for learning an effective classification model. Therefore, we propose the use of the RUSBoost algorithm in order to train classifiers and to handle the class imbalance training problem. Furthermore, a multi-class feature selection method based on sparsity is integrated into the proposed framework to improve the classification performance. It also provides a way for investigating the importance of different features and regions. Using a dataset of 500 subjects, the proposed framework achieved a high accuracy of 75.2% with a balanced accuracy of 69.3% for the five-class classification using ten-fold cross validation, which is significantly better than the results using support vector machine or random forest, demonstrating the feasibility of the proposed framework to support clinical decision making. Keywords: Neurodegenerative diseases, Differential diagnosis, MRI, Dementia, Imbalance learning, Multi-class feature selection

Different neurodegenerative diseases can cause memory disorders and other cognitive impairments. The early detection and the stratification of patients according to the underlying disease are essential for an efficient approach to this healthcare challenge. This emphasizes the importance of differential diagnostics. Most studies compare patients and controls, or Alzheimer's disease with one other type of dementia. Such a bilateral comparison does not resemble clinical practice, where a clinician is faced with a number of different possible types of dementia. Here we studied which features in structural magnetic resonance imaging (MRI) scans could best distinguish four types of dementia, Alzheimer's disease, frontotemporal dementia, vascular dementia, and dementia with Lewy bodies, and control subjects. We extracted an extensive set of features quantifying volumetric and morphometric characteristics from T1 images, and vascular characteristics from FLAIR images. Classification was performed using a multi-class classifier based on Disease State Index methodology. The classifier provided continuous probability indices for each disease to support clinical decision making. A dataset of 504 individuals was used for evaluation. The cross-validated classification accuracy was 70.6% and balanced accuracy was 69.1% for the five disease groups using only automatically determined MRI features. Vascular dementia patients could be detected with high sensitivity (96%) using features from FLAIR images. Controls (sensitivity 82%) and Alzheimer's disease patients (sensitivity 74%) could be accurately classified using T1-based features, whereas the most difficult group was the dementia with Lewy bodies (sensitivity 32%). These results were notable better than the classification accuracies obtained with visual MRI ratings (accuracy 44.6%, balanced accuracy 51.6%). Different quantification methods provided complementary information, and consequently, the best results were obtained by utilizing several quantification methods. The results prove that automatic quantification methods and computerized decision support methods are feasible for clinical practice and provide comprehensive information that may help clinicians in the diagnosis making.