The Mini-Addenbrooke's Cognitive Examination: a new assessment tool for dementia.

BACKGROUND/AIMS: We developed and validated the Mini-Addenbrooke's Cognitive Examination (M-ACE) in dementia patients. Comparisons were also made with the Mini Mental State Examination (MMSE). METHOD: The M-ACE was developed using Mokken scaling analysis in 117 dementia patients [behavioural variant frontotemporal dementia (bvFTD), n = 25; primary progressive aphasia (PPA), n = 49; Alzheimer's disease (AD), n = 34; corticobasal syndrome (CBS), n = 9] and validated in an independent sample of 164 dementia patients (bvFTD, n = 23; PPA, n = 82; AD, n = 38; CBS, n = 21) and 78 controls, who also completed the MMSE. RESULTS: The M-ACE consists of 5 items with a maximum score of 30. Two cut-offs were identified: (1) ≤25/30 has both high sensitivity and specificity, and (2) ≤21/30 is almost certainly a score to have come from a dementia patient regardless of the clinical setting. The M-ACE is more sensitive than the MMSE and is less likely to have ceiling effects. CONCLUSION: The M-ACE is a brief and sensitive cognitive screening tool for dementia. Two cut-offs (25 or 21) are recommended.This work was supported by funding to Forefront, a collaborative research group dedicated to the study of frontotemporal dementia and motor neurone disease, by the National Health and Medical Research council (NHMRC) of Australia program grant (1037746) and the Australian Research Council (ARC) Centre of Excellence in Cognition and Its Disorders Memory Node (CE110001021). S.H. is supported by the Graham Linford Fellowship from the Motor Neurone Disease Research Institute of Australia. S.M. is supported by Alzheimer Scotland (PhD Studentship). F.L. is supported by an Australian Postgraduate Award (PhD Scholarship). K.D. is supported by NIHR Cambridge Biomedical Research Centre. S.A. is supported by the NIHR Biomedical Research Centre, Oxford. C.R.B. is supported by a Clinician Scientist Fellowship from the Medical Research Council (MR/K010395/1). J.B.R. is supported by the Wellcome Trust (088324), Medical Research Council, McDonnell Foundation and the NIHR (Cambridge Biomedical Research Centre and Biomedical Research Unit in Dementia). E.M. is supported by the NHMRC Early Career Fellowship (1016399) and Alzheimer Association USA. J.R.H. is supported by an ARC Federation Fellowship (FF0776229).This is the final version of the article. It first appeared from Karger via http://dx.doi.org/10.1159/00036604

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guessing. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as patient-specific biomarker trends. The submission system remains open via the website https://tadpole.grand-challenge.org, while code for submissions is being collated by TADPOLE SHARE: https://tadpole-share.github.io/. Our work suggests that current prediction algorithms are accurate for biomarkers related to clinical diagnosis and ventricle volume, opening up the possibility of cohort refinement in clinical trials for Alzheimer's disease

Non-parametric item response theory applications in the assessment of dementia

This thesis sought to address the application of non-parametric item response theory (NIRT) to cognitive and functional assessment in dementia. Performance on psychometric tests is key to diagnosis and monitoring of dementia. NIRT can be used to improve the psychometric properties of tests used in dementia assessment in multiple ways: confirming an underlying unidimensional structure, establishing formal item hierarchical patterns of decline, increasing insight by examining item parameters such as difficulty and discrimination, and creating shorter tests. From a NIRT approach item difficulty refers to the ease with which an item is endorsed. Discrimination is an index of how well an item can differentiate between patients of varying levels of severity. Firstly I carried out a systematic review to identify applications of both parametric and non-parametric IRT to measures assessing global cognitive functioning in people with dementia. This review demonstrated that IRT can increase the interpretive power of cognitive assessment scales and confirmed the limited number of IRT analyses of cognitive scales in dementia populations. This thesis extended this approach by applying Mokken scaling analysis to commonly used measures of current cognitive ability (Addenbrooke’s Cognitive Examination-Revised (ACE-R)) and of premorbid cognitive ability (National Adult Reading Test (NART)). Differential item functioning (DIF) by diagnosis identified slight variations in the patterns of hierarchical decline in the ACE-R. These disease-specific sequences of decline could serve as an adjunct to diagnosis, for example where learning a name and address is a more difficult task than being orientated in time, late onset Alzheimer’s disease is a more probable diagnosis than mixed Alzheimer’s and vascular dementia. These analyses also allowed key items to be identified which can be used to create briefer scales (mini-ACE and Mini-NART) which have good psychometric properties. These scales are clinically relevant, comprising highly discriminatory, invariantly ordered items. They also allow sensitive measurement and adaptive testing and can reduce test administration time and patient stress. Impairment of functional abilities represents a crucial component of dementia diagnosis with performance on these functional tasks predictive of overall disease. A second aspect of this thesis, therefore, was the application of Mokken scaling analyses to measures of functional decline in dementia, specifically the Lawton Instrumental Activities of Daily Living (IADL) scale and Physical Self-Maintenance Scale (PSMS). While gender DIF was observed for several items, implying the likelihood of equal responses from men and women is not equal a generally consistent pattern of impairment in functional ability was observed across different types of dementia

Use of aggregation functions in decision making

A key component of many decision making processes is the aggregation step, whereby a set of numbers is summarised with a single representative value. This research showed that aggregation functions can provide a mathematical formalism to deal with issues like vagueness and uncertainty, which arise naturally in various decision contexts

Methods to assess changes in human brain structure across the lifecourse

Human brain structure can be measured across the lifecourse (“in vivo”) with magnetic resonance imaging (MRI). MRI data are often used to create “atlases” and statistical models of brain structure across the lifecourse. These methods may define how brain structure changes through life and support diagnoses of increasingly common, yet still fatal, age-related neurodegenerative diseases. As diseases such as Alzheimer’s (AD) cast an ever growing shadow over our ageing population, it is vitally important to robustly define changes which are normal for age and those which are pathological. This work therefore assessed existing MR brain image data, atlases, and statistical models. These assessments led me to propose novel methods for accurately defining the distributions and boundaries of normal ageing and pathological brain structure. A systematic review found that there were fewer than 100 appropriately tested normal subjects aged ≥60 years openly available worldwide. These subjects did not have the range of MRI sequences required to effectively characterise the features of brain ageing. The majority of brain image atlases identified in this review were found to contain data from few or no subjects aged ≥60 years and were in a limited range of MRI sequences. All of these atlases were created with parametric (mean-based) statistics that require the assumptions of equal variance and Gaussian distributions. When these assumptions are not met, mean-based atlases and models may not well represent the distributions and boundaries of brain structure. I tested these assumptions and found that they were not met in whole brain, subregional, and voxel-based models of ~580 subjects from across the lifecourse (0- 90 years). I then implemented novel whole brain, subregional, and voxel-based statistics, e.g. percentile rank atlases and nonparametric effect size estimates. The equivalent parametric statistics led to errors in classification and inflated effects by up to 45% in normal ageing-AD comparisons. I conclude that more MR brain image data, age appropriate atlases, and nonparametric statistical models are needed to define the true limits of normal brain structure. Accurate definition of these limits will ultimately improve diagnoses, treatment, and outcome of neurodegenerative disease

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

Meaning Behind the Metrics of Misery: Understanding Prevalence Estimates of Poor Mental Health in Two Samples of Older Rural Indonesians

Background: Late life is typically accompanied by unique physical and mental health challenges. Fewer older people are diagnosed with mood or anxiety-specific disorders than their younger counterparts. However, older people score more highly than younger people on symptom screens indicating high levels of clinically relevant depressive, anxiety, and nonspecific psychological distress symptoms which cause high morbidity, mortality, disability, and poor quality of life. The unique presentation of late life psychiatric syndromes, such as depression and anxiety, remain largely unaddressed in existing psychiatric nosology and measurement techniques, as do depictions of depression and anxiety across diverse cultural contexts. Very few studies exist investigating either the descriptive epidemiology of depression and anxiety among older adults living in low-middle income countries (LMIC) or the unique challenges of mental health measurement in LMIC contexts. This dissertation contributes to this developing evidence base by providing a critical analysis of point prevalence estimates of depression, anxiety, and nonspecific psychological distress (distress) symptoms in two samples of Indonesian rural older persons. Methods: We enumerated greater than or equal to 60-year-olds in 12 Indonesian rural villages as part of the Ageing in Rural Indonesia Study in 2015/16 (N=2526; sample 1). We re-enumerated two of the 12 villages surveyed in 2015 in 2017 (N=536; sample 2). Depressive and distress symptoms were each measured using three scales: PHQ-8/9, CES-D, GDS, and K6, DQ5 and SRQ-20 respectively. Anxiety symptoms were evaluated with the GAD-7. Classical Test Theory and Item Response Theory were used to investigate the psychometric properties of symptom screens. We also undertook mixed effects modelling and Moderated Nonlinear Factor Analysis to identify sources of variability in prevalence estimates. Results: Commonly used cut points of short symptom screens used to approximate diagnostic depressive disorders produced estimates that typically lacked comparability (e.g., sample 2 point-prevalence 3.2%-39.9%). Psychometric analysis further identified mental health scales with better (PHQ-8/9, GAD-7, K6, DQ5) and poorer (GDS, SRQ) construct validity. Sources of variability in point prevalence estimates of depression, anxiety and distress symptoms were identified, and related to study design, cognitive ability, marital status, financial means, level of social support, lifestyle, and health related status. Pervasive non-invariance was identified in participant responses to scale items related to gender, literacy, and ethnicity. However, when modelled, measurement non-invariance did not substantially modify means. Females, respondents with lower literacy levels, and Batak and Sundanese sample villages had significantly higher levels of depression, anxiety, and distress symptoms. Conclusion: The practice of using existing mental health symptom screens combined with commonly used cut points as proxies for depression and anxiety in older rural Indonesians and other diverse populations should be avoided. Rigorous psychometric and diagnostic validation evidence should be ascertained. In the interim, better performing symptom screening tools (i.e., PHQ-8/9, GAD-7, K6, DQ5) may be used as measures of continuous symptom severity. Future research should focus on evaluating the distinctive and overlapping features of mental ill-health in specific subpopulations of Indonesians

Proceedings of The Multi-Agent Logics, Languages, and Organisations Federated Workshops (MALLOW 2010)

http://ceur-ws.org/Vol-627/allproceedings.pdfInternational audienceMALLOW-2010 is a third edition of a series initiated in 2007 in Durham, and pursued in 2009 in Turin. The objective, as initially stated, is to "provide a venue where: the cost of participation was minimum; participants were able to attend various workshops, so fostering collaboration and cross-fertilization; there was a friendly atmosphere and plenty of time for networking, by maximizing the time participants spent together"