BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disorder where pathophysiological changes begin decades before the onset of clinical symptoms. Analysis of brain atrophy patterns using structural MRI and multivariate data analysis are an effective tool in identifying patients with subjective cognitive decline (SCD) at higher risk of progression to AD dementia. Atrophy patterns obtained from models trained to classify advanced AD versus normal subjects, may not be optimal for subjects at an early stage, like SCD. In this study, we compared the accuracy of the SCD progression prediction using the 'severity index' generated using a standard classification model trained on patients with AD dementia versus a new model trained on β-amyloid (Aβ) positive patients with amnestic mild cognitive impairment (aMCI). METHODS: We used structural MRI data of 504 patients from the Swedish BioFINDER-1 study cohort (cognitively normal (CN), Aβ-negative = 220; SCD, Aβ positive and negative = 139; aMCI, Aβ-positive = 106; AD dementia = 39). We applied multivariate data analysis to create two predictive models trained to discriminate CN individuals from either individuals with Aβ positive aMCI or AD dementia. Models were applied to individuals with SCD to classify their atrophy patterns as either high-risk "disease-like" or low-risk "CN-like". Clinical trajectory and model accuracy were evaluated using 8 years of longitudinal data. RESULTS: In predicting progression from SCD to MCI or dementia, the standard, dementia-based model, reached 100% specificity but only 10.6% sensitivity, while the new, aMCI-based model, reached 72.3% sensitivity and 60.9% specificity. The aMCI-based model was superior in predicting progression from SCD to MCI or dementia, reaching a higher receiver operating characteristic area under curve (AUC = 0.72; P = 0.037) in comparison with the dementia-based model (AUC = 0.57). CONCLUSION: When predicting conversion from SCD to MCI or dementia using structural MRI data, prediction models based on individuals with milder levels of atrophy (i.e. aMCI) may offer superior clinical value compared to standard dementia-based models.

• Keywords
• Alzheimer’s disease, Atrophy patterns, Multivariate analysis, Structural MRI, Subjective cognitive decline,
• MeSH
• Alzheimer Disease diagnostic imaging   pathology   MeSH
• Atrophy * pathology   MeSH
• Dementia * diagnostic imaging   pathology   MeSH
• Cognitive Dysfunction * diagnostic imaging   pathology   diagnosis   MeSH
• Cohort Studies MeSH
• Middle Aged MeSH
• Humans MeSH
• Magnetic Resonance Imaging * methods   MeSH
• Brain * pathology   diagnostic imaging   MeSH
• Neuropsychological Tests MeSH
• Disease Progression * MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

We here posit that measurements of midlife cognition can be instructive in understanding cognitive disorders. Even though molecular events signal possible onset of cognitive disorders decades prior to their clinical diagnoses, cognition and its possible early changes in midlife remain poorly understood. We characterize midlife cognition in a cognitively healthy population-based sample using the Cogstate Brief Battery and test for associations with cardiovascular, adiposity-related, lifestyle-associated, and psychosocial variables. Learning and working memory showed significant variability and vulnerability to psychosocial influences in midlife. Furthermore, midlife aging significantly and progressively increased prevalence of suboptimal cognitive performance. Our findings suggest that physiological changes in cognition, measured with simple tests suitable for use in everyday clinical setting, may signal already in midlife the first clinical manifestations of the presymptomatic biologically defined cognitive disorders. This pilot study calls for longitudinal studies investigating midlife cognition to identify clinical correlates of biologically defined cognitive disorders.

• Keywords
• cognitive disorders, cognitive performance, midlife cognition, psychosocial variables, quality of life, suboptimal cognition,
• Publication type
• Journal Article MeSH

OBJECTIVES: The aim of this data paper is to provide the data set of a sub-analysis of the DEMDATA study data. In the DEMDATA study, epidemiological data on the prevalence and severity of dementia, as well as functioning, behavioral problems and other health related factors in residents living in Austrian and Czech nursing homes were collected. The DEMDATA project further provides information on relatives' perception of the life Quality of residents, care team burden as well as environmental factors. Participating nursing homes were randomly drawn and stratified. Inclusion criteria for participation were that the resident was living permanently in the institution and that he/she and/or a legal representative (where relevant) had signed an informed consent. DATA DESCRIPTION: This paper provides data of cognitive, functional and behavioral assessments as well as other health related information of 1085 residents living in Austrian and Czech nursing homes. For each resident, several measurements on his or her cognitive, functional, and behavioral status are available. Also further health-related factors such as quality of life, pain, numbers of falls and hospital stays are provided.

• Keywords
• Austria, Czech Republic, Dementia, Epidemiological data, Nursing homes,
• MeSH
• Dementia epidemiology   psychology   MeSH
• Homes for the Aged * MeSH
• Quality of Life psychology   MeSH
• Humans MeSH
• Nursing Homes * MeSH
• Prevalence MeSH
• Cross-Sectional Studies MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Mental Status and Dementia Tests statistics & numerical data   MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Geographicals
• Czech Republic epidemiology   MeSH
• Austria epidemiology   MeSH

BACKGROUND: This paper provides a first comparative exploratory analysis of our findings from DEMDATA, a collaborative project between Austria and the Czech Republic. Analysed here are data from the residents and the environment assessment protocol. METHODS: In a cross sectional study design, residents from randomly drawn and stratified nursing homes were investigated using a common study protocol. RESULTS: From a total resident pool of 1666 persons, 1085 (571 in Austria, 514 in the Czech Republic) persons signed a consent form and participated in the data collection. More than 70% of residents assessed were female and the population was on average 85 years old. A discrepancy between the presence of a medical diagnosis in the charts of the residents and the results of cognitive testing was found. In Austria, 85.2%, in the Czech Republic 53.0% of residents had cognitive impairment. In Austria 80.0%, and in the Czech Republic 56.7% had behavioural problems. With respect to pain, 44.8% in Austria, and 51.5% in the Czech Republic had mild to severe pain. 78.4% of Austrian and 74.5% of the residents had problems with mobility and both populations were in danger of malnutrition. CONCLUSIONS: Most of the prevalence rates are comparable with previous studies also using direct resident assessment. Variations in prevalence rates seem to result mainly from the assessment technique (direct cognitive testing vs. medical chart review). The high prevalence rates for dementia, behavioural symptoms, pain and malnutrition indicate an immediate call for attention to further research and practice development.

• Keywords
• Dementia prevalence, Malnutrition, Nursing home, Pain, Prevalence of behavioural symptoms,
• MeSH
• Behavioral Symptoms diagnosis   epidemiology   MeSH
• Pain diagnosis   epidemiology   MeSH
• Dementia diagnosis   epidemiology   MeSH
• Homes for the Aged trends   MeSH
• Cognitive Dysfunction diagnosis   epidemiology   MeSH
• Humans MeSH
• Random Allocation MeSH
• Mobility Limitation * MeSH
• Nursing Homes trends   MeSH
• Prevalence MeSH
• Cross-Sectional Studies MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Czech Republic epidemiology   MeSH
• Austria epidemiology   MeSH

BACKGROUND: The organization of long-term care is one of the main challenges of public health and health policies in Europe and worldwide, especially in terms of care concepts for people with dementia. In Austria and the Czech Republic the majority of elderly institutionalized persons with dementia are cared for in nursing homes. It is however unclear, how many persons living in nursing homes in Austria and in the Czech Republic are suffering from cognitive impairment and dementia. In addition, basic information on the nutritional status, the status of mobility and the medication prescription patterns are often missing. To facilitate new effective and evidenced based care concepts, basic epidemiological data are in urgent need. Thus, DEMDATA was initiated to provide important basic data on persons living in nursing homes in Austria and the Czech Republic for future care planning. METHODS: DEMDATA is a multicentre mixed methods cross-sectional study. Stratified and randomly drawn nursing homes in Austria and the Czech Republic are surveyed. The study protocol used in both study centres assesses four different domains: a) Resident, b) Care team, c) Relative and d) Environmental Factors. Resident's data include among others health status, cognition, dementia, mobility, nutrition, behavioural symptoms, pain intensity and quality of life. A minimum of 500 residents per country are included into the study (N = 1000 residents). The care team is asked about the use of the person-centred care and their burden. The relatives are asked about the number of visits and proxy-rate the quality of life of their family member. All staff employed in the nursing homes, all residents and relatives can voluntary take part in the study. The environmental factors include among others the organisational category of the nursing home, number of residents, number of rooms, social activities and the care concept. The project started in March 2016 and will be concluded in February 2018. DISCUSSION: DEMDATA will provide important epidemiological data on four different nursing home domains in Austria and the Czech Republic, with a focus on the prevalence of dementia in this population. Thereby supplying decision and policy makers with important foundation for future care planning.

• Keywords
• Database, Health parameters, Nursing homes, dementia,
• MeSH
• Behavioral Symptoms psychology   therapy   MeSH
• Dementia epidemiology   psychology   therapy   MeSH
• Long-Term Care organization & administration   MeSH
• Homes for the Aged statistics & numerical data   MeSH
• Institutionalization MeSH
• Cognition Disorders psychology   therapy   MeSH
• Quality of Life MeSH
• Physicians statistics & numerical data   MeSH
• Humans MeSH
• Patient-Centered Care MeSH
• Nursing Homes statistics & numerical data   MeSH
• Cross-Sectional Studies MeSH
• Surveys and Questionnaires MeSH
• Family psychology   MeSH
• Aged MeSH
• Check Tag
• Humans MeSH
• Male MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Multicenter Study MeSH
• Geographicals
• Czech Republic epidemiology   MeSH
• Austria epidemiology   MeSH

The authors compared the risk for subjective cognitive impairment (SCI) between carriers of the apolipoprotein E ε4 (APOE ε4) allele (cases) and APOE ε4 noncarriers (controls). SCI was assessed by a validated self-reported questionnaire. The authors used multivariable logistic regression analyses to compute odds ratios and 95% confidence intervals adjusted for age, sex, education, and marital status. Data were available on 114 participants (83 women; 47 APOE ε4 carriers; mean age, 69 years). The risk for SCI was significantly higher among cases than controls, particularly for those 70 years of age and older. These findings should be considered preliminary until confirmed by a prospective cohort study.

• MeSH
• Alleles MeSH
• Apolipoproteins E genetics   MeSH
• Adult MeSH
• Genetic Predisposition to Disease * MeSH
• Genotype MeSH
• Cognition Disorders genetics   MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Neuropsychological Tests MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Aging psychology   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Young Adult MeSH
• Male MeSH
• Aged, 80 and over MeSH
• Aged MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Apolipoproteins E MeSH