Promoting Independence in Dementia (PRIDE): protocol for a feasibility randomised controlled trial

ObjectivesTo understand whether interventions are effective, we need to know whether the interventions are delivered as planned (with fidelity) and engaged with. To measure fidelity and engagement effectively, high‐quality measures are needed. We outline a five‐step method which can be used to develop quality measures of fidelity and engagement for complex health interventions. We provide examples from a fidelity study conducted within an evaluation of an intervention aimed to increase independence in dementia.MethodsWe propose five steps that can be systematically used to develop fidelity checklists for researchers, providers, and participants to measure fidelity and engagement. These steps include the following: (1) reviewing previous measures, (2) analysing intervention components and developing a framework outlining the content of the intervention, (3) developing fidelity checklists and coding guidelines, (4) obtaining feedback about the content and wording of checklists and guidelines, and (5) piloting and refining checklists and coding guidelines to assess and improve reliability.ResultsThree fidelity checklists that can be used reliably were developed to measure fidelity of and engagement with, the Promoting Independence in Dementia (PRIDE) intervention. As these measures were designed to be used by researchers, providers, and participants, we developed two versions of the checklists: one for participants and one for researchers and providers.ConclusionsThe five steps that we propose can be used to develop psychometrically robust and implementable measures of fidelity and engagement for complex health interventions that can be used by different target audiences. By considering quality when developing measures, we can be more confident in the interpretation of intervention outcomes drawn from fidelity and engagement studies. Statement of contribution What is already known on the subject? Fidelity and engagement can be measured using a range of methods, such as observation and self‐report.Studies seldom report psychometric and implementation qualities of fidelity measures. What does this study add? A method for developing fidelity and engagement measures for complex health interventions.Guidance on how to consider quality when developing fidelity and engagement measures.

The Informant AD8 Can Discriminate Patients with Dementia From Healthy Control Participants in an Asian Older Cohort

Application of AD-8 to screen very mild dementia in Taiwan

Introduction: To assess cognitive impairment, self-awareness is an important issue. The Ascertain Dementia 8 questionnaire (AD8) is a brief observation checklist for detecting mild cognitive impairment (MCI) and dementia. After analyzing the reliability and validity of a self-reported Japanese version of the AD8 (AD8-J), we compared self- and informant-reported versions of the AD8-J. Methods: A total of 93 community residents aged 75 years or older living in Wakuya, Northern Japan, agreed to participate in this study; 35 were rated as Clinical Dementia Rating (CDR) 0 (healthy), 46 as CDR 0.5 (defined herein as MCI), and 12 as CDR 1 or above (dementia, confirmed by the DSM-IV). We examined the reliability and validity using a receiver operating characteristic (ROC) curve. We analyzed the differences between self-reported and informant-reported AD8-J using a repeated measures ANOVA. Results: The self-reported AD8-J showed a satisfactory reliability (i.e., Cronbach coefficient, α = 0.71; Guttman split half method coefficient = 0.60). For CDR 0 vs. CDR 0.5 or above, the area under the ROC curve was 0.74 and the cutoff score was 1/2, with a sensitivity of 70.7% and a specificity of 65.7%. Analysis of the subscores of AD8 suggested that, from the early stage of dementia, the subjects showed a subjective decline in memory and interest in hobbies/activities, as well as problems with judgment. Conclusion: It is suggested that the self-reported AD8-J was effective in detecting MCI and dementia. We could use it for detecting MCI and dementia, including in those living alone, in the primary health checkup.

Background and PurposeAlthough the clock drawing test (CDT) is a widely used cognitive screening instrument, there have been inconsistent findings regarding its utility with various scoring systems in patients with mild cognitive impairment (MCI) or dementia. The present study aimed to identify whether patients with MCI or dementia exhibited impairment on the CDT using three different scoring systems, and to determine which scoring system is more useful for detecting MCI and mild dementia.MethodsPatients with amnestic mild cognitive impairment (aMCI), vascular mild cognitive impairment (VaMCI), mild Alzheimer's disease (AD), mild vascular dementia (VaD), and cognitively normal older adults (CN) were included. All participants were administered the CDT, the Korean-Mini Mental State Examination (K-MMSE), and the Clinical Dementia Rating scale. The CDT was scored using the 3-, 5-, and 15-point scoring systems.ResultsOn all three scoring systems, all patient groups demonstrated significantly lower scores than the CN. However, while there were no significant differences among patients with aMCI, VaMCI, and AD, those with VaD exhibited the lowest scores. Area under the Receiver Operating Characteristic curves revealed that the three CDT scoring systems were comparable with the K-MMSE in differentiating aMCI, VaMCI, and VaD from CN. In differentiating AD from CN, however, the CDT using the 15-point scoring system demonstrated the most comparable discriminability with K-MMSE.ConclusionsThe results demonstrated that the CDT is a useful cognitive screening tool that is comparable with the Mini-Mental State Examination, and that simple CDT scoring systems are sufficient for differentiating patients with MCI and mild dementia from CN.

IntroductionDementia is a chronic and progressive neurological condition characterised by cognitive and functional impairment. It is often associated with multimorbidity and imposes a significant economic burden on healthcare systems and families, especially in low-income and middle-income countries. In Peru, where dementia cases are increasing rapidly, timely detection and referral for diagnosis is crucial. This protocol is part of the IMPACT Salud project in Peru. Here, we focus on a specific component aimed at validating an mHealth tool for the detection of cognitive and functional impairment and assessing its cost-effectiveness. We will also assess changes in cognitive and functional impairment as well as health economic outcomes over 1 year.Methods and analysisThis observational study will be conducted in four geographically diverse regions of Peru. Community health workers are expected to contact approximately 32 000 participants (≥60 years) to apply an mHealth-enabled tool that includes cognitive and functional instruments: Ascertain Dementia 8, Peruvian version of Rowland Universal Dementia Assessment Scale and Pfeffer Functional Activities Questionnaire. From this large sample, we aim to find 3600 participants and their study partners to enrol and interview at baseline regarding sociodemographic characteristics, lifestyles, comorbidities and health economic data including resource use, costs and health-related quality of life (HR-QoL). Psychologists, blind to previous results, will assess dementia stage of the participants using an abbreviated Clinical Dementia Rating (CDR) scale. At 6-month follow-up, participants will complete a brief health economics questionnaire on resource use, costs and HR-QoL. To validate the accuracy of the detection tool, a subsample of 600 participants who completed the baseline will undergo a gold-standard clinical neuropsychological assessment. This subsample will participate in a 12-month follow-up, including health economics, cognitive and functional impairment tests and the CDR scale. Results will be analysed and presented by cognitive status, site, sex and multimorbidity profile. Finally, data from all stages and external sources will inform a decision model to implement a cost-effectiveness analysis of the detection tool at the national level.Ethics and disseminationThe study received ethics approval in Peru (Universidad Peruana Cayetano Heredia: CONSTANCIA-CIEI-378-33-23) and in the UK (Imperial College London: ICREC/SETREC reference number 6647445). Informed consent will be obtained from participants and their study partners, considering the participant’s capacity to consent. For illiterate participants, consent will be obtained through a witnessed procedure involving study partners, with a fingerprint obtained instead of a signature. The results will be disseminated through conferences, published articles, public presentations (particularly to those involved in dementia care) and presentations or meetings with local health authorities.

Several studies have reported changes in the corpus callosum (CC) in Alzheimer's disease. However, the involved region differed according to the study population and study group. Using deep learning technology, we ensured accurate analysis of the CC in Alzheimer's disease. We used the Open Access Series of Imaging Studies (OASIS) dataset to investigate changes in the CC. The individuals were divided into three groups using the Clinical Dementia Rating (CDR); 94 normal controls (NC) were not demented (NC group, CDR = 0), 56 individuals had very mild dementia (VMD group, CDR = 0.5), and 17 individuals were defined as having mild and moderate dementia (MD group, CDR = 1 or 2). Deep learning technology using a convolutional neural network organized in a U-net architecture was used to segment the CC in the midsagittal plane. Total CC length and regional magnetic resonance imaging (MRI) measurements of the CC were made. The total CC length was negatively associated with cognitive function. (beta = -0.139, p = 0.022) Among MRI measurements of the CC, the height of the anterior third (beta = 0.038, p <0.0001) and width of the body (beta = 0.077, p = 0.001) and the height (beta = 0.065, p = 0.001) and area of the splenium (beta = 0.059, p = 0.027) were associated with cognitive function. To distinguish MD from NC and VMD, the receiver operating characteristic analyses of these MRI measurements showed areas under the curves of 0.65-0.74. (total CC length = 0.705, height of the anterior third = 0.735, width of the body = 0.714, height of the splenium = 0.703, area of the splenium = 0.649). Among MRI measurements, total CC length, the height of the anterior third and width of the body, and the height and area of the splenium were associated with cognitive decline. They had fair diagnostic validity in distinguishing MD from NC and VMD.

The high burden of dementia and Alzheimer's disease (AD) increases substantially as disease progresses. Characterizing early patterns of health care utilization among patients who develop cognitive impairment may deepen our understanding of early disease trajectory and potentially facilitate timely diagnosis and management. Describe clinical characteristics, healthcare utilization, and costs in early-stage dementia by disease severity and amyloid-β status before enrollment in an observational study (GERAS-US). Consented patients' GERAS-US data were linked to available five-years of Medicare claims history before GERAS-US enrollment. Clinical characteristics, comorbidity, and pre-/post-diagnosis healthcare use and costs were assessed. Continuous and categorical variables were compared between severity and amyloid-status cohorts using t-test and Chi-square statistics; linear regression models were used to compare cost and utilization measures after adjusting for differences in patients' observation time. Relative likelihood of observed diagnoses, comorbidity, and prescription drug use among cohorts were presented as OR and 90% confidence interval (CI). Of 174 patients clinically diagnosed with early dementia (mild cognitive impairment (MCI): 101; mild dementia (MILD): 73), 55% were amyloid-positive. Memory loss was more likely in MILD versus MCI (OR:1.85, 90% CI 1.10-3.09) and in amyloid-positive versus amyloid-negative cohorts (OR:1.98, 90% CI 1.19-3.29). Mean annual healthcare costs after cognitive impairment/dementia diagnosis were significantly higher for MILD versus MCI ($1191 versus $712, p = 0.067) and amyloid-negative versus amyloid-positive ($1281 versus $701, p = 0.034). Diabetes was more prevalent in MILD and amyloid-negative cohorts. Comorbidity and economic burden increased in earliest stages of MCI and MILD and were higher in patients who were amyloid-negative.

Association between clinical dementia rating and clinical outcomes in Alzheimer's disease

BackgroundAlzheimer disease (AD) is a degenerative progressive brain disorder where symptoms of dementia and cognitive impairment intensify over time. Numerous factors exist that may or may not be related to the lifestyle of a patient that result in a higher risk for AD. Diagnosing the disorder in its beginning period is important, and several techniques are used to diagnose AD. A number of studies have been conducted on the detection and diagnosis of AD. This paper reports the empirical study performed on the longitudinal-based magnetic resonance imaging (MRI) Open Access Series of Brain Imaging dataset. Furthermore, the study highlights several factors that influence the prediction of AD.ObjectiveThis study aimed to correlate the effect of various factors such as age, gender, education, and socioeconomic background of patients with the development of AD. The effect of patient-related factors on the severity of AD was assessed on the basis of MRI features, Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR), estimated total intracranial volume (eTIV), normalized whole brain volume (nWBV), and Atlas Scaling Factor (ASF).MethodsIn this study, we attempted to establish the role of longitudinal MRI in an exploratory data analysis (EDA) of AD patients. EDA was performed on the dataset of 150 patients for 343 MRI sessions (mean age 77.01 [SD 7.64] years). The T1-weighted MRI of each subject on a 1.5-Tesla Vision (Siemens) scanner was used for image acquisition. Scores of three features, MMSE, CDR, and ASF, were used to characterize the AD patients included in this study. We assessed the role of various features (ie, age, gender, education, socioeconomic status, MMSE, CDR, eTIV, nWBV, and ASF) on the prognosis of AD.ResultsThe analysis further establishes the role of gender in the prevalence and development of AD in older people. Moreover, a considerable relationship has been observed between education and socioeconomic position on the progression of AD. Also, outliers and linearity of each feature were determined to rule out the extreme values in measuring the skewness. The differences in nWBV between CDR=0 (nondemented), CDR=0.5 (very mild dementia), and CDR=1 (mild dementia) are significant (ie, P&lt;.01).ConclusionsA substantial correlation has been observed between the pattern and other related features of longitudinal MRI data that can significantly assist in the diagnosis and determination of AD in older patients.

Reading the Mind in the Eyes: A Population-Based Study of Social Cognition in Older Adults

PHENOCONVERSION FROM ASYMPTOMATIC TO MINIMALLY SYMPTOMATIC FTLD: PRELIMINARY DATA IN THE LEFFTDS COHORT

Many elderly people with cognitive dysfunction may observe a decrease in their health levels and quality of life (QOL). The basic concept of QOL consists of several categories including physical functions and mental health. The QOL domain that is most important for elderly people is physical health and, to a lesser extent, psychological health, social relationships, and/ or the environment. Our aim was to explore the relationships between the subjective measure of QOL, an abbreviated version of the World Health Organization Quality of Life (WHOQOL-BREF) scale, and the objective measure of impairment, Clinical Dementia Rating (CDR), among elderly people in a community. Totally, 178 community dwellers aged 75 years and above agreed to participate and completed the WHOQOL-BREF; 66 (32 males, 34 females) scored a CDR of 0 (healthy), 86 (33, 53) scored a CDR of 0.5 (questionable dementia or very mild dementia), and 26 (12, 14) scored a CDR of 1 and above (dementia). According to Pearson’s correlation coefficient analysis (significance level, p < 0.05), the physical domain of the WHOQOL-BREF had significant statistical negative correlations with all CDR subscales. The CDR subscale of memory impairment had a significant statistical negative correlation with the WHOQOL-BREF subscales of the physical (r = -0.151, p = 0.044) and psychological (r = -0.232, p < 0.002) domains. The CDR subscale of home and hobbies impairment had significant statistical negative correlations with all WHOQOL-BREF subscales including the physical (r = -0.226, p = 0.002), psychological (r = -0.226, p = 0.002), social (r = -0.167, p = 0.026), and environmental (r = -0.204, p = 0.006) domains. Patients with very mild dementia may confuse cognitive impairment and physical disabilities. In the future, we need to systematically combine memory clinics and all departments related to the elderly for the successful early detection and rehabilitation of, and long-term care for, dementia.

In this report, the results of a household survey were used to examine the prevalence of very mild and mild dementia in Chinese older persons in Hong Kong. The study adopted a two-phase design. At Phase 1, 6100 subjects were screened using the Cantonese version of the Mini-mental State Examination (MMSE) and a short memory inventory. At Phase 2, 2073 subjects were screened positive and 737 were evaluated by psychiatrists. Clinical Dementia Rating (CDR) and cognitive assessment were used for diagnosis of dementia. Very mild dementia (VMD) was defined as a global CDR of 0.5, with memory and non-memory subscale scores of 0.5 or more. Mild dementia was classified for subjects with a CDR of 1. The overall prevalence of VMD and mild dementia for persons aged 70 years or above was 8.5% (95%CI: 7.4-9.6) and 8.9% (95%CI: 7.8-10.0) respectively. Among subjects with clinical dementia, 84.6% had mild (CDR1) dementia. Logistic regression analyses revealed that older age, lower educational level and significant cerebrovascular risk factors were risk factors for dementia, while regular physical exercise was a protective factor for dementia. A sizable proportion of community-living subjects suffered from milder forms of dementia. They represent a high risk for early intervention to reduce potential physical and psychiatric morbidity.

The original version of the Clinical Dementia Rating (CDR) scale correlates with other dementia rating scales, and predicts nursing home (NH) admission and death. To validate the extended components of the scale, we analyzed data from subjects participating in a community-based study of dementia. The extended CDR scale also correlated with measures of dementia severity and NH residence. "Profound" and "terminal" stages predicted shortened survival. The extended CDR scale should be useful in studies of the later stages of dementia.