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Article ; Online: Organisational aspects and assessment practices of Australian memory clinics

Perminder S Sachdev / Inga Mehrani / Nicole A Kochan / Min Yee Ong / John D Crawford

BMJ Open, Vol 11, Iss

an Australian Dementia Network (ADNeT) Survey

2021 Volume 2

Abstract: Objectives Conducting a national survey of clinicians and administrators from specialised dementia assessment services (memory clinics) in Australia to examine their current organisational aspects and assessment procedures and inform clinical tool ... ...

Abstract	Objectives Conducting a national survey of clinicians and administrators from specialised dementia assessment services (memory clinics) in Australia to examine their current organisational aspects and assessment procedures and inform clinical tool harmonisation as part of the Australian Dementia Network—memory clinics project.Design A cross-sectional survey.Setting Public and private memory clinics across Australia.Participants 150 individual clinicians completed the survey between May and August 2019. Responses could be given anonymously. Most clinics were publicly funded services (83.2%) and in metropolitan regions (70.9%).Outcome measures Descriptive data on organisational aspects of memory clinics (eg, waiting times, staffing); the three most commonly used assessment tools per assessment type (eg, self-report) and cognitive domain (eg, attention).Results Since the last national survey in 2009, the number of memory clinics across Australia has increased substantially but considerable variability has remained with respect to funding structure, staffing and assessment procedures. The average clinic employed 2.4 effective full-time staff (range 0.14–14.0). The reported waiting time for an initial assessment ranged from 1 week to 12 months with a median of 7 weeks. While most clinics (97%) offered follow-up assessments for their clients, only a few (31%) offered any form of cognitive intervention. We identified over 100 different cognitive assessment tools that were used at least ‘sometimes’, with widespread use of well-established core screening tools and a subset of common neuropsychological tests.Conclusion This paper presents a current snapshot of Australian memory clinics, showing considerable heterogeneity with some common core elements. These results will inform the development of national memory clinic guidelines. Furthermore, our data make a valuable contribution to the international comparison of clinical practice standards and advocate for greater harmonisation to ensure high-quality dementia care.
Keywords	Medicine ; R
Subject code	820
Language	English
Publishing date	2021-02-01T00:00:00Z
Publisher	BMJ Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Association of adherence to the Australian Dietary Guidelines with cognitive performance and cognitive decline in the Sydney Memory and Ageing Study

Xi Chen / Zhixin Liu / Perminder S. Sachdev / Nicole A. Kochan / Henry Brodaty / Fiona O'Leary

Journal of Nutritional Science, Vol

a longitudinal analysis

2021 Volume 10

Abstract: This study investigated associations of adherence to the Australian Dietary Guidelines (ADG) with cognitive performance and cognitive decline over 6 years. We used longitudinal data from the Sydney Memory and Aging Study comprising 1037 community- ... ...

Abstract	This study investigated associations of adherence to the Australian Dietary Guidelines (ADG) with cognitive performance and cognitive decline over 6 years. We used longitudinal data from the Sydney Memory and Aging Study comprising 1037 community-dwelling non-demented participants aged 70–90 years. Dietary intake was assessed at baseline using the Dietary Questionnaire for Epidemiological Studies Version 2. Adherence to the ADG was scored using the Dietary Guideline Index 2013 (DGI-2013). Cognition was assessed using neuropsychological tests in six cognitive domains and global cognition at baseline and 2, 4 and 6 years later. Linear mixed models analysed the association between adherence to the ADG and cognitive function and cognitive decline over 6 years. Results indicated that overall adherence to the ADG was suboptimal (DGI-2013 mean score 43⋅8 with a standard deviation of 10⋅1; median score 44, range 12–73 with an interquartile range of 7). The percent of participants attaining recommended serves for the five food groups were 30⋅2 % for fruits, 11⋅2 % for vegetables, 54⋅6 % for cereals, 28⋅9 % for meat and alternatives and 2⋅1 % for dairy consumption. Adherence to the ADG was not associated with overall global cognition over 6 years (β = 0⋅000; 95 % CI: −0⋅007, 0⋅007; P = 0⋅95). Neither were DGI-2013 scores associated with change in global cognitive performance over 6 years (β = 0⋅002; 95 % CI: −0⋅002, 0⋅005; P = 0⋅41) nor in any individual cognitive domains. In conclusion, adherence to the ADG was not associated with cognitive health over time in this longitudinal analysis of older Australians. Future research is needed to provide evidence to support specific dietary guidelines for neurocognitive health among Australian older adults.
Keywords	Cognitive health ; Diet quality ; Dietary Guide Index ; Food consumption ; Nutrition epidemiology ; Nutrition. Foods and food supply ; TX341-641 ; Medicine ; R
Subject code	120
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Cambridge University Press
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Risk factors for falls in community-dwelling older people with mild cognitive impairment

Thanwarat Chantanachai / Morag E. Taylor / Stephen R. Lord / Jasmine Menant / Kim Delbaere / Perminder S. Sachdev / Nicole A. Kochan / Henry Brodaty / Daina L. Sturnieks

PeerJ, Vol 10, p e

a prospective one-year study

2022 Volume 13484

Abstract: Objective Mild cognitive impairment (MCI) is considered an intermediate stage between normal cognitive function and dementia. Fall risk is increased in this group, but there is limited literature exploring specific fall risk factors that may be addressed ...

Abstract	Objective Mild cognitive impairment (MCI) is considered an intermediate stage between normal cognitive function and dementia. Fall risk is increased in this group, but there is limited literature exploring specific fall risk factors that may be addressed in fall prevention strategies. The aim of this study was to examine risk factors for falls in older people with MCI, focusing on cognitive, psychological and physical factors. Methods Participants (n = 266, 45% women) were community-dwelling older people aged 70–90 years who met the criteria for MCI. Cognitive, psychological, sensorimotor and physical assessments, physical activity levels, medication use, general health and disability were ascertained at baseline. Falls were monitored prospectively for 12 months. Results During follow-up, 106 (40%) participants reported one or more falls. Poorer visual contrast sensitivity, increased postural sway, lower levels of weekly walking activity, higher levels of depressive symptoms and psychotropic medication use were significantly associated with faller status (≥1 falls) in univariable analyses. Of these factors, poor visual contrast sensitivity, increased postural sway and psychotropic medication use were found to be significant independent predictors of falls in multivariable analysis while controlling for age and sex. No measures of cognitive function were associated with falls. Conclusions Poor visual contrast sensitivity, impaired balance and psychotropic medication use predicted falls in community-dwelling people with MCI. These risk factors may be amenable to intervention, so these factors could be carefully considered in fall prevention programs for this population.
Keywords	Accidental falls ; Aged ; Cognitive dysfunction ; Postural balance ; Psychotropic drugs ; Vision disorders ; Medicine ; R ; Biology (General) ; QH301-705.5
Subject code	150
Language	English
Publishing date	2022-05-01T00:00:00Z
Publisher	PeerJ Inc.
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A comparison of machine learning methods for survival analysis of high-dimensional clinical data for dementia prediction

Annette Spooner / Emily Chen / Arcot Sowmya / Perminder Sachdev / Nicole A. Kochan / Julian Trollor / Henry Brodaty

Scientific Reports, Vol 10, Iss 1, Pp 1-

2020 Volume 10

Abstract: Abstract Data collected from clinical trials and cohort studies, such as dementia studies, are often high-dimensional, censored, heterogeneous and contain missing information, presenting challenges to traditional statistical analysis. There is an urgent ... ...

Abstract	Abstract Data collected from clinical trials and cohort studies, such as dementia studies, are often high-dimensional, censored, heterogeneous and contain missing information, presenting challenges to traditional statistical analysis. There is an urgent need for methods that can overcome these challenges to model this complex data. At present there is no cure for dementia and no treatment that can successfully change the course of the disease. Machine learning models that can predict the time until a patient develops dementia are important tools in helping understand dementia risks and can give more accurate results than traditional statistical methods when modelling high-dimensional, heterogeneous, clinical data. This work compares the performance and stability of ten machine learning algorithms, combined with eight feature selection methods, capable of performing survival analysis of high-dimensional, heterogeneous, clinical data. We developed models that predict survival to dementia using baseline data from two different studies. The Sydney Memory and Ageing Study (MAS) is a longitudinal cohort study of 1037 participants, aged 70–90 years, that aims to determine the effects of ageing on cognition. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is a longitudinal study aimed at identifying biomarkers for the early detection and tracking of Alzheimer's disease. Using the concordance index as a measure of performance, our models achieve maximum performance values of 0.82 for MAS and 0.93 For ADNI.
Keywords	Medicine ; R ; Science ; Q
Subject code	310
Language	English
Publishing date	2020-11-01T00:00:00Z
Publisher	Nature Portfolio
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Participant and informant memory-specific cognitive complaints predict future decline and incident dementia

Katya Numbers / John D Crawford / Nicole A Kochan / Brian Draper / Perminder S Sachdev / Henry Brodaty

PLoS ONE, Vol 15, Iss 5, p e

Findings from the Sydney Memory and Ageing Study.

2020 Volume 0232961

Abstract: Subjective Cognitive Complaints (SCCs) may represent one of the earliest stages of preclinical dementia. The objective of the present study was to extend previous work by our group to examine the relationship between participant-reported and informant- ... ...

Abstract	Subjective Cognitive Complaints (SCCs) may represent one of the earliest stages of preclinical dementia. The objective of the present study was to extend previous work by our group to examine the relationship between participant-reported and informant-reported memory and non-memory SCCs, cognitive decline and incident dementia, over a six-year period. Participants were 873 community dwelling older adults (Mage = 78.65, SD = 4.79) without dementia and 843 informants (close friends or family) from the Sydney Memory and Ageing Study. Comprehensive neuropsychological testing and diagnostic assessments were carried out at baseline and biennially for six years. Linear mixed models and Cox proportional hazard models were performed to determine the association of SCCs, rate of cognitive decline and risk of incident dementia, controlling demographics and covariates of mood and personality. Participant and informant memory-specific SCCs were associated with rate of global cognitive decline; for individual cognitive domains, participant memory SCCs predicted decline for language, while informant memory SCCs predicted decline for executive function and memory. Odds of incident dementia were associated with baseline participant memory SCCs and informant memory and non-memory SCCs in partially adjusted models. In fully adjusted models, only informant SCCs were associated with increased risk of incident dementia. Self-reported memory-specific cognitive complaints are associated with decline in global cognition over 6-years and may be predictive of incident dementia, particularly if the individual is depressed or anxious and has increased neuroticism or decreased openness. Further, if and where possible, informants should be sought and asked to report on their perceptions of the individual's memory ability and any memory-specific changes that they have noticed as these increase the index of diagnostic suspicion.
Keywords	Medicine ; R ; Science ; Q
Subject code	120
Language	English
Publishing date	2020-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Is intraindividual reaction time variability an independent cognitive predictor of mortality in old age? Findings from the Sydney Memory and Ageing Study.

Nicole A Kochan / David Bunce / Sarah Pont / John D Crawford / Henry Brodaty / Perminder S Sachdev

PLoS ONE, Vol 12, Iss 8, p e

2017 Volume 0181719

Abstract: Intraindividual variability of reaction time (IIVRT), a proposed cognitive marker of neurobiological disturbance, increases in old age, and has been associated with dementia and mortality. The extent to which IIVRT is an independent predictor of ... ...

Abstract	Intraindividual variability of reaction time (IIVRT), a proposed cognitive marker of neurobiological disturbance, increases in old age, and has been associated with dementia and mortality. The extent to which IIVRT is an independent predictor of mortality, however, is unclear. This study investigated the association of IIVRT and all-cause mortality while accounting for cognitive level, incident dementia and biomedical risk factors in 861 participants aged 70-90 from the Sydney Memory and Ageing Study. Participants completed two computerised reaction time (RT) tasks (76 trials in total) at baseline, and comprehensive medical and neuropsychological assessments every 2 years. Composite RT measures were derived from the two tasks-the mean RT and the IIVRT measure computed from the intraindividual standard deviation of the RTs (with age and time-on-task effects partialled out). Consensus dementia diagnoses were made by an expert panel of clinicians using clinical criteria, and mortality data were obtained from a state registry. Cox proportional hazards models estimated the association of IIVRT and mean RT with survival time over 8 years during which 191 (22.2%) participants died. Greater IIVRT but not mean RT significantly predicted survival time after adjusting for age, sex, global cognition score, cardiovascular risk index and apolipoprotein ɛ4 status. After excluding incident dementia cases, the association of IIVRT with mortality changed very little. Our findings suggest that greater IIVRT uniquely predicts shorter time to death and that lower global cognition and prodromal dementia in older individuals do not explain this relationship.
Keywords	Medicine ; R ; Science ; Q
Subject code	310
Language	English
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The association of regional white matter lesions with cognition in a community-based cohort of older individuals

Jiyang Jiang / Matthew Paradise / Tao Liu / Nicola J. Armstrong / Wanlin Zhu / Nicole A. Kochan / Henry Brodaty / Perminder S. Sachdev / Wei Wen

NeuroImage: Clinical, Vol 19, Iss , Pp 14-

2018 Volume 21

Abstract: Emerging evidence from lesion-symptom mapping (LSM) studies suggested that regional white matter lesions (WML) on strategic white matter (WM) fiber tracts are significantly associated with specific cognitive domains, independent of global WML burden. ... ...

Abstract	Emerging evidence from lesion-symptom mapping (LSM) studies suggested that regional white matter lesions (WML) on strategic white matter (WM) fiber tracts are significantly associated with specific cognitive domains, independent of global WML burden. However, previous LSM investigations were mostly carried out in disease cohorts, with little evidence from community-based older individuals, making findings difficult to generalize. Moreover, most LSM studies applied a threshold to the probabilistic atlas, leading to the loss of information and threshold-dependent findings. Furthermore, it is still unclear whether associations between regional WML and cognition are independent of global grey matter (GM) and WM volumes, which have also been linked to cognition. In the current study, we undertook a region of interest (ROI) LSM study to examine the relationship between regional WML on strategic WM tracts and cognitive performance in a large community-based cohort of older individuals (N = 461; 70–90 years). WML were extracted using a publicly available pipeline, UBO Detector (https://cheba.unsw.edu.au/group/neuroimaging-pipeline). Mapping of WML to the Johns Hopkins University WM atlas was undertaken using an automated TOolbox for Probabilistic MApping of Lesions (TOPMAL), which we introduce here, and is implemented in UBO Detector. The results show that different patterns of brain structural volumes in the ageing brain were associated with different cognitive domains. Regional WML were associated with processing speed, executive function, and global cognition, independent of total GM, WM and WML volumes. Moreover, regional WML explained more variance in executive function, compared to total GM, WM and WML volumes. The current study highlights the importance of studying regional WML in age-related cognitive decline. Keywords: White matter lesions, Strategic white matter fiber tracts, Cognitive performance, Neuropsychological assessments, Community-dwelling older individuals
Keywords	Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurology. Diseases of the nervous system ; RC346-429
Language	English
Publishing date	2018-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Novel ThickNet features for the discrimination of amnestic MCI subtypes

Pradeep Reddy Raamana / Wei Wen / Nicole A. Kochan / Henry Brodaty / Perminder S. Sachdev / Lei Wang / Mirza Faisal Beg

NeuroImage: Clinical, Vol 6, Iss C, Pp 284-

2014 Volume 295

Abstract: Background: Amnestic mild cognitive impairment (aMCI) is considered to be a transitional stage between healthy aging and Alzheimer's disease (AD), and consists of two subtypes: single-domain aMCI (sd-aMCI) and multi-domain aMCI (md-aMCI). Individuals ... ...

Abstract	Background: Amnestic mild cognitive impairment (aMCI) is considered to be a transitional stage between healthy aging and Alzheimer's disease (AD), and consists of two subtypes: single-domain aMCI (sd-aMCI) and multi-domain aMCI (md-aMCI). Individuals with md-aMCI are found to exhibit higher risk of conversion to AD. Accurate discrimination among aMCI subtypes (sd- or md-aMCI) and controls could assist in predicting future decline. Methods: We apply our novel thickness network (ThickNet) features to discriminate md-aMCI from healthy controls (NC). ThickNet features are extracted from the properties of a graph constructed from inter-regional co-variation of cortical thickness. We fuse these ThickNet features using multiple kernel learning to form a composite classifier. We apply the proposed ThickNet classifier to discriminate between md-aMCI and NC, sd-aMCI and NC and; and also between sd-aMCI and md-aMCI, using baseline T1 MR scans from the Sydney Memory and Ageing Study. Results: ThickNet classifier achieved an area under curve (AUC) of 0.74, with 70% sensitivity and 69% specificity in discriminating md-aMCI from healthy controls. The same classifier resulted in AUC = 0.67 and 0.67 for sd-aMCI/NC and sd-aMCI/md-aMCI classification experiments respectively. Conclusions: The proposed ThickNet classifier demonstrated potential for discriminating md-aMCI from controls, and in discriminating sd-aMCI from md-aMCI, using cortical features from baseline MRI scan alone. Use of the proposed novel ThickNet features demonstrates significant improvements over previous experiments using cortical thickness alone. This result may offer the possibility of early detection of Alzheimer's disease via improved discrimination of aMCI subtypes.
Keywords	Mild cognitive impairment ; Cortical thickness ; Network ; ThickNet ; Early detection ; Alzheimer ; Computer applications to medicine. Medical informatics ; R858-859.7 ; Neurology. Diseases of the nervous system ; RC346-429
Subject code	006
Language	English
Publishing date	2014-01-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Microstructural white matter changes, not hippocampal atrophy, detect early amnestic mild cognitive impairment.

Lin Zhuang / Perminder S Sachdev / Julian N Trollor / Simone Reppermund / Nicole A Kochan / Henry Brodaty / Wei Wen

PLoS ONE, Vol 8, Iss 3, p e

2013 Volume 58887

Abstract: Alzheimer's disease (AD) is generally considered to be characterized by pathology in gray matter of the brain, but convergent evidence suggests that white matter degradation also plays a vital role in its pathogenesis. The evolution of white matter ... ...

Abstract	Alzheimer's disease (AD) is generally considered to be characterized by pathology in gray matter of the brain, but convergent evidence suggests that white matter degradation also plays a vital role in its pathogenesis. The evolution of white matter deterioration and its relationship with gray matter atrophy remains elusive in amnestic mild cognitive impairment (aMCI), a prodromal stage of AD.We studied 155 cognitively normal (CN) and 27 'late' aMCI individuals with stable diagnosis over 2 years, and 39 'early' aMCI individuals who had converted from CN to aMCI at 2-year follow up. Diffusion tensor imaging (DTI) tractography was used to reconstruct six white matter tracts three limbic tracts critical for episodic memory function - the fornix, the parahippocampal cingulum, and the uncinate fasciculus; two cortico-cortical association fiber tracts - superior longitudinal fasciculus and inferior longitudinal fasciculus; and one projection fiber tract - corticospinal tract. Microstructural integrity as measured by fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AxD) was assessed for these tracts.Compared with CN, late aMCI had lower white matter integrity in the fornix, the parahippocampal cingulum, and the uncinate fasciculus, while early aMCI showed white matter damage in the fornix. In addition, fornical measures were correlated with hippocampal atrophy in late aMCI, whereas abnormality of the fornix in early aMCI occurred in the absence of hippocampal atrophy and did not correlate with hippocampal volumes.Limbic white matter tracts are preferentially affected in the early stages of cognitive dysfunction. Microstructural degradation of the fornix preceding hippocampal atrophy may serve as a novel imaging marker for aMCI at an early stage.
Keywords	Medicine ; R ; Science ; Q
Subject code	616
Language	English
Publishing date	2013-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Impact of load-related neural processes on feature binding in visuospatial working memory.

Nicole A Kochan / Michael Valenzuela / Melissa J Slavin / Stacey McCraw / Perminder S Sachdev / Michael Breakspear

PLoS ONE, Vol 6, Iss 8, p e

2011 Volume 23960

Abstract: Background The capacity of visual working memory (WM) is substantially limited and only a fraction of what we see is maintained as a temporary trace. The process of binding visual features has been proposed as an adaptive means of minimising information ... ...

Abstract	Background The capacity of visual working memory (WM) is substantially limited and only a fraction of what we see is maintained as a temporary trace. The process of binding visual features has been proposed as an adaptive means of minimising information demands on WM. However the neural mechanisms underlying this process, and its modulation by task and load effects, are not well understood. Objective To investigate the neural correlates of feature binding and its modulation by WM load during the sequential phases of encoding, maintenance and retrieval. Methods and findings 18 young healthy participants performed a visuospatial WM task with independent factors of load and feature conjunction (object identity and position) in an event-related functional MRI study. During stimulus encoding, load-invariant conjunction-related activity was observed in left prefrontal cortex and left hippocampus. During maintenance, greater activity for task demands of feature conjunction versus single features, and for increased load was observed in left-sided regions of the superior occipital cortex, precuneus and superior frontal cortex. Where these effects were expressed in overlapping cortical regions, their combined effect was additive. During retrieval, however, an interaction of load and feature conjunction was observed. This modulation of feature conjunction activity under increased load was expressed through greater deactivation in medial structures identified as part of the default mode network. Conclusions and significance The relationship between memory load and feature binding qualitatively differed through each phase of the WM task. Of particular interest was the interaction of these factors observed within regions of the default mode network during retrieval which we interpret as suggesting that at low loads, binding processes may be 'automatic' but at higher loads it becomes a resource-intensive process leading to disengagement of activity in this network. These findings provide new insights into how feature binding operates within the capacity-limited WM system.
Keywords	Medicine ; R ; Science ; Q
Subject code	150
Language	English
Publishing date	2011-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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