Staging dementia from symptom profiles on a care partner website

Repetitive Behaviors in Alzheimer's Disease: A Systematic Review and Meta-Analysis

BACKGROUND

Repetitive behaviors (RBs) are a well-known symptom of Alzheimer's disease (AD); however, they have been little studied and have not been the subject of any specific literature review.

OBJECTIVE

To conduct a systematic review of all studies to document RBs in AD.

METHODS

An extensive literature search combining five databases and a meta-analysis were conducted to investigate the frequency, nature, and cognitive correlates of RBs in AD.

RESULTS

Ten studies were included in the review. Seven studies out of ten investigated the frequency of RBs in patients with AD, which ranged from 52.3% to 87%. A meta-analysis showed an overall frequency of 66.3% (95% CI: 55.5; 77.1) of patients exhibiting RBs in AD, but important heterogeneity was observed between studies. Three studies investigated the predominant nature of RBs in AD. Verbal RBs, complex behavioral stereotypies, and simple motor stereotypies have been identified to different degrees depending on the level of dementia. Most verbal RBs are underpinned by episodic memory impairment, while simple motor stereotypies and complex behavioral stereotypies are mostly underpinned by executive dysfunction.

CONCLUSIONS

The current review seems to suggest that there are two types of mechanisms underpinning RBs involved in AD. The first is observed especially in the mild stages of the disease and is mediated by episodic memory impairment. The second occurs later and is mediated by executive impairment. Additional studies should be conducted to improve the knowledge about RBs in AD and thus improve their management.Systematic review registration number: PROSPERO 2022: CRD42022310027.

Patterns of Symptom Tracking by Caregivers and Patients With Dementia and Mild Cognitive Impairment: Cross-sectional Study

Background

Individuals with dementia and mild cognitive impairment (MCI) experience a wide variety of symptoms and challenges that trouble them. To address this heterogeneity, numerous standardized tests are used for diagnosis and prognosis. myGoalNav Dementia is a web-based tool that allows individuals with impairments and their caregivers to identify and track outcomes of greatest importance to them, which may be a less arbitrary and more sensitive way of capturing meaningful change.

Objective

We aim to explore the most frequent and important symptoms and challenges reported by caregivers and people with dementia and MCI and how this varies according to disease severity.

Methods

This cross-sectional study involved 3909 web-based myGoalNav users (mostly caregivers of people with dementia or MCI) who completed symptom profiles between 2006 and 2019. To make a symptom profile, users selected their most personally meaningful or troublesome dementia-related symptoms to track over time. Users were also asked to rank their chosen symptoms from least to most important, which we called the symptom potency. As the stage of disease for these web-based users was unknown, we applied a supervised staging algorithm, previously trained on clinician-derived data, to classify each profile into 1 of 4 stages: MCI and mild, moderate, and severe dementia. Across these stages, we compared symptom tracking frequency, symptom potency, and the relationship between frequency and potency.

Results

Applying the staging algorithm to the 3909 user profiles resulted in 917 (23.46%) MCI, 1596 (40.83%) mild dementia, 514 (13.15%) moderate dementia, and 882 (22.56%) severe dementia profiles. We found that the most frequent symptoms in MCI and mild dementia profiles were similar and comprised early hallmarks of dementia (eg, recent memory and language difficulty). As the stage increased to moderate and severe, the most frequent symptoms were characteristic of loss of independent function (eg, incontinence) and behavioral problems (eg, aggression). The most potent symptoms were similar between stages and generally reflected disruptions in everyday life (eg, problems with hobbies or games, travel, and looking after grandchildren). Symptom frequency was negatively correlated with potency at all stages, and the strength of this relationship increased with increasing disease severity.

Conclusions

Our results emphasize the importance of patient-centricity in MCI and dementia studies and illustrate the valuable real-world evidence that can be collected with digital tools. Here, the most frequent symptoms across the stages reflected our understanding of the typical disease progression. However, the symptoms that were ranked as most personally important by users were generally among the least frequently selected. Through individualization, patient-centered instruments such as myGoalNav can complement standardized measures by capturing these infrequent but potent outcomes.

Development of a symptom menu to facilitate Goal Attainment Scaling in adults with Down syndrome-associated Alzheimer's disease: a qualitative study to identify meaningful symptoms

Background

As life expectancy of people with Down syndrome (DS) increases, so does the risk of Alzheimer’s disease (AD). Identifying symptoms and tracking disease progression is especially challenging whenever levels of function vary before the onset of dementia. Goal Attainment Scaling (GAS), an individualized patient-reported outcome, can aid in monitoring disease progression and treatment effectiveness in adults with DS. Here, with clinical input, a validated dementia symptom menu was revised to facilitate GAS in adults living with Down Syndrome-associated Alzheimer’s disease (DS-AD).

Methods

Four clinicians with expertise in DS-AD and ten caregivers of adults living with DS-AD participated in semi-structured interviews to review the menu. Each participant reviewed 9–15 goal areas to assess their clarity and comprehensiveness. Responses were systematically and independently coded by two researchers as ‘clear’, ‘modify’, ‘remove’ or ‘new’. Caregivers were encouraged to suggest additional items and recommend changes to clarify items.

Results

Median caregiver age was 65 years (range 54–77). Most were female (9/10) with ≥15 years of education (10/10). Adults with DS-AD had a median age of 58 years (range 52–61) and either a formal diagnosis (6/10) or clinical suspicion (4/10) of dementia. The initial symptom menu consisted of 67 symptoms each with 2–12 descriptors (589 total). The clinicians’ adaptation yielded 58 symptoms each with 4–17 descriptors (580 total). Of these 580 descriptors, caregivers identified 37 (6%) as unclear; these were reworded, and one goal area (4 descriptors) was removed. A further 47 descriptors and one goal area were added to include caregiver-identified concepts. The final menu contained 58 goal areas, each with 7–17 descriptors (623 total).

Conclusions

A comprehensive symptom menu for adults living with DS-AD was developed to facilitate GAS. Incorporating expert clinician opinion and input from caregivers of adults with DS-AD identified meaningful items that incorporate patient/caregiver perspectives.

Use of Patient-Reported Symptoms from an Online Symptom Tracking Tool for Dementia Severity Staging: Development and Validation of a Machine Learning Approach

BACKGROUND

SymptomGuide Dementia (DGI Clinical Inc) is a publicly available online symptom tracking tool to support caregivers of persons living with dementia. The value of such data are enhanced when the specific dementia stage is identified.

OBJECTIVE

We aimed to develop a supervised machine learning algorithm to classify dementia stages based on tracked symptoms.

METHODS

We employed clinical data from 717 people from 3 sources: (1) a memory clinic; (2) long-term care; and (3) an open-label trial of donepezil in vascular and mixed dementia (VASPECT). Symptoms were captured with SymptomGuide Dementia. A clinician classified participants into 4 groups using either the Functional Assessment Staging Test or the Global Deterioration Scale as mild cognitive impairment, mild dementia, moderate dementia, or severe dementia. Individualized symptom profiles from the pooled data were used to train machine learning models to predict dementia severity. Models trained with 6 different machine learning algorithms were compared using nested cross-validation to identify the best performing model. Model performance was assessed using measures of balanced accuracy, precision, recall, Cohen κ, area under the receiver operating characteristic curve (AUROC), and area under the precision-recall curve (AUPRC). The best performing algorithm was used to train a model optimized for balanced accuracy.

RESULTS

The study population was mostly female (424/717, 59.1%), older adults (mean 77.3 years, SD 10.6, range 40-100) with mild to moderate dementia (332/717, 46.3%). Age, duration of symptoms, 37 unique dementia symptoms, and 10 symptom-derived variables were used to distinguish dementia stages. A model trained with a support vector machine learning algorithm using a one-versus-rest approach showed the best performance. The correct dementia stage was identified with 83% balanced accuracy (Cohen κ=0.81, AUPRC 0.91, AUROC 0.96). The best performance was seen when classifying severe dementia (AUROC 0.99).

CONCLUSIONS

A supervised machine learning algorithm exhibited excellent performance in identifying dementia stages based on dementia symptoms reported in an online environment. This novel dementia staging algorithm can be used to describe dementia stage based on user-reported symptoms. This type of symptom recording offers real-world data that reflect important symptoms in people with dementia.

Communicating with library patrons and people with dementia: Tracing an ethic of care in professional communication guidelines

In both library reference work and dementia care, communication between personnel and service recipients can be both complex and complicated. Professionals in both fields have therefore developed protocols and standards to assist personnel in handling these interactions. In this article we detail an exploratory comparative study that used an ethic of care framework to compare prominent guidelines for reference librarians (American Library Association’s Reference and User Services Association’s Guidelines for behavioral performance of reference and information service providers) with guidelines for workers in long-term dementia care settings (the National Institute for Health and Care Excellence’s Guideline on supporting people with dementia and their carers in health and social care). We explored how both sets of Guidelines frame the act of communication as a combination of regulated procedure and empathetic discourse to determine how the similarities among and differences between these two guidelines provide useful insights into each other. Our examination was structured using an ethic of care lens, which emphasizes the importance of interpersonal relationships, reciprocity, and empathetic benevolence. Using specific phrases in each set of Guidelines that align with and are evidence of Tronto’s four moral principles of care, we ultimately discovered, in both sets of Guidelines, an underlying ethic of care: a repeated insistence upon embedding procedures within behaviour that manifests attentiveness, responsibility, responsiveness, and competence.

Staging dementia based on caregiver reported patient symptoms: Implications from a latent class analysis

Background

Tailoring interventions to the needs of caregivers is an important feature of successful caregiver support programs. To improve cost-effectiveness, group tailoring based on the stage of dementia could be a good alternative. However, existing staging strategies mostly depend on trained professionals.

Objective

This study aims to stage dementia based on caregiver reported symptoms of persons with dementia.

Methods

Latent class analysis was used. The classes derived were then mapped with disease duration to define the stages. Logistic regression with receiver operating characteristic curve was used to generate the optimal cut-offs.

Results

Latent class analysis suggested a 4-class solution, these four classes were named as early (25.9%), mild (25.2%), moderate (16.7%) and severe stage (32.3%). The stages based on the cut-offs generated achieved an overall accuracy of 90.8% compared to stages derived from latent class analysis.

Conclusion

The current study confirmed that caregiver reported patient symptoms could be used to classify persons with dementia into different stages. The new staging strategy is a good complement of existing dementia clinical assessment tools in terms of better supporting informal caregivers.

Characterizing the symptom of misplacing objects in people with dementia: findings from an online tracking tool

OBJECTIVES

Misplacing objects is often reported as a clinically important symptom in dementia. Here we explored misplacing objects in relation to dementia type and stage in an online sample of individuals with dementia and their caregivers.

METHODS

Participants were recruited from www.dementiaguide.com, a web-based tracker for common dementia symptoms. Users provided information about symptoms that they selected as important for monitoring. We analysed cross-sectional data from respondents who tracked at least three symptoms, which allowed for staging dementia severity.

RESULTS

Of 2,775 users with three-plus symptoms, 787 (28%) identified misplacing objects for symptom tracking. Misplacing objects was monitored by users across all stages of dementia, but was more prevalent in mild and severe dementia. Three common clinical subtypes of misplacing were investigated: lost & found (forgetting the location of items), hidden away (hiding items so others would not find them), and odd places (putting items in usual spots). Of the 787, 96% targeted lost & found, the most frequent type. Odd places (targeted in 56%) significantly increased with dementia severity (p < 0.001). Misplacing objects was most strongly associated with the symptoms of interaction with strangers (OR 4.60, 95% CI: 3.20-6.62), reading (3.68: 2.86-4.73), shopping (3.55: 2.73-4.61) and travel/vacationing (3.31: 2.54-4.31).

CONCLUSIONS

Misplacing objects was most often selected for tracking in mild and severe stages of dementia. As disease advances, misplacing more often reflects odd placement of objects rather than their simple loss. Misplacing objects may be a clinically important therapeutic target for improving patients' quality of life and lessening caregiver burden.

The Symptoms Targeted for Monitoring in a Web-Based Tracking Tool by Caregivers of People With Dementia and Agitation: Cross-Sectional Study

BACKGROUND

In people with dementia, neuropsychiatric symptoms (NPSs), especially agitation, are associated with worse quality of life and caregiver burden. As NPSs may vary with illness severity, knowledge of how people with dementia and their caregivers describe and rate the importance of agitation symptoms can improve the understanding of the clinical meaningfulness of the manifestations of agitation. The internet provides new opportunities to better understand patient experiences, as patients and caregivers increasingly look to Web-based platforms as a means of managing symptoms.

OBJECTIVE

The aim of this study was to examine Web-based reports from a dementia symptom website to better understand the symptoms of agitation and explore how they are being targeted for monitoring by caregivers of people with dementia.

METHODS

The Dementia Guide website hosts a Web-based database used by caregivers (97%) and people with dementia (3%). From its 61 dementia symptoms, users can select relevant symptoms that they deem important to monitor or track the effects of treatment. We employed a staging algorithm to determine if individuals had mild cognitive impairment (MCI) or mild, moderate, or severe dementia. Agitation was defined using terms consistent with the International Psychogeriatrics Association's provisional consensus definition. We compared the proportion of people with NPSs and agitation across stages of dementia severity and studied how many agitation-defining descriptors were selected, and how often they occurred, by stage.

RESULTS

As of March 2017, 4121 people had used the tracking tool, of whom 2577 provided sufficient data to allow disease severity staging. NPSs were tracked by 2127/2577 (82.54%) and agitation by 1898/2577 (73.65%). The proportion in whom agitation was tracked increased with increasing cognitive impairment: 68.5% (491/717) in people with MCI, and 72.50% (754/1040), 73.3% (378/516), and 90.5% (275/304) in mild, moderate, and severe dementia, respectively (χ²₃=54.9; P<.001). The number of NPS and agitation descriptors selected also increased with severity (median number of NPSs=1, 2, 2, and 3 for MCI, mild, moderate, and severe dementia, respectively, Kruskal-Wallis H Test H₃=250.47; P<.001; median number of agitation descriptors=1, 2, 3, and 4, H₃=146.11; P<.001).

CONCLUSIONS

NPSs and agitation are common targets for tracking over the course of dementia and appear more frequently with increasing disease severity. These common and distressing symptoms represent clinically meaningful targets in treating people with dementia.

Exploration of verbal repetition in people with dementia using an online symptom-tracking tool

BACKGROUND

Online tools can be used by people with dementia and their caregivers to self-identify and track troubling symptoms, such as verbal repetition. We aimed to explore verbal repetition behaviors in people with dementia.

METHODS

Participants were recruited via an online resource for people with dementia and their caregivers. Respondents were instructed to complete information about symptoms that are most important to them for tracking over time. In this cross-sectional study, we analyzed data pertaining to individuals with dementia who had at least three symptoms selected for tracking.

RESULTS

Of the 3,573 participants who began a user profile, 1,707 fulfilled criteria for analysis. Verbal repetition was identified as a treatment target in 807 respondents (47.3%). Verbal repetition was more frequent in individuals with mild dementia compared to those with moderate and severe dementia (57.2% vs. 36.0% and 39.9%, p < 0.01) and in those with Alzheimer's disease versus other dementias (65.2% vs. 29.7%, p < 0.001). Repetitive questioning was the most frequent type of verbal repetition (90.5% of individuals with verbal repetition). Verbal repetition was most strongly associated with difficulties operating gadgets/appliances (OR 3.65, 95%CI: 2.82-4.72), lack of interest and/or initiative (3.52: 2.84-4.36), misplacing or losing objects (3.25: 2.64-4.01), and lack of attention and/or concentration (2.62: 2.12-3.26).

CONCLUSIONS

Verbal repetition is a common symptom in people at all stages of dementia but is most commonly targeted for monitoring and treatment effects in its mild stage. Much research is required to further elucidate the underlying mechanisms and the effect of different treatment strategies.

Neuropsychiatric symptom clusters targeted for treatment at earlier versus later stages of dementia

OBJECTIVE

To characterize clusters of neuropsychiatric symptoms targeted for tracking the disease course in people with dementia, in relation to stage.

METHODS

Baseline symptoms from 2922 subjects from two datasets (one clinic based, one online) were aggregated. Common neuropsychiatric symptoms identified by patients/carers as targets of treatment using a dementia SymptomGuide™ were selected. The Global Deterioration Scale was used for clinic staging, and an artificial neural network algorithm, for staging online subjects. Symptom clusters were detected using multiple correspondence analysis and connectivity graph analysis based on relative risk (RR). In a connectivity graph, each pair of nodes (representing symptoms) is connected if their co-occurrence is statistically significant; direction is indicated as positive if RR > 1 and negative otherwise.

RESULTS

Neuropsychiatric symptoms were targeted for treatment in 1072 patients (37%). Agitation (37%) and sleep disturbances (28%) were most common symptoms. One cluster (in people with cognitive impairment, no dementia (CIND) or mild dementia) showed significant co-occurrence of anxiety and restlessness; decreased initiative was chiefly seen in isolation. A second cluster (in moderate/severe dementia) was defined by significant co-occurrence of delusions and hallucinations with sleep disturbances; in these subjects, decreased initiative was related to aggression.

CONCLUSIONS

Two analytical methods identified neuropsychiatric symptom clusters targeted to track the disease course. In CIND/mild dementia, a profile of decreased initiative distinct from depression suggests possible executive dysfunction. In moderate/severe dementia, targets more reflected psychotic symptoms. Visual data displays allow the relationships between multiple symptoms to be considered simultaneously, which commonly is how they present in patients.

Assessing cognition and function in Alzheimer's disease clinical trials: do we have the right tools?

Several lines of evidence from Alzheimer's disease (AD) research continue to support the notion that the biological changes associated with AD are occurring possibly several decades before an individual will experience the cognitive and functional changes associated with the disease. The National Institute on Aging-Alzheimer's Association revised criteria for AD provided a framework for this new thinking. As a result of this growing understanding, several research efforts have launched or will be launching large secondary prevention trials in AD. These and other efforts have clearly demonstrated a need for better measures of cognitive and functional change in people with the earliest changes associated with AD. Recent draft guidance from the US Food and Drug Administration further elevated the importance of cognitive and functional assessments in early stage clinical trials by proposing that even in the pre-symptomatic stages of the disease, approval will be contingent on demonstrating clinical meaningfulness. The Alzheimer's Association's Research Roundtable addressed these issues at its fall meeting October 28-29, 2013, in Washington, D.C. The focus of the discussion included the need for improved cognitive and functional outcome measures for clinical of participants with preclinical AD and those diagnosed with Mild Cognitive Impairment due to AD.

Can a novel web-based computer test predict poor simulated driving performance? a pilot study with healthy and cognitive-impaired participants

Background

Driving a car is a complex instrumental activity of daily living and driving performance is very sensitive to cognitive impairment. The assessment of driving-relevant cognition in older drivers is challenging and requires reliable and valid tests with good sensitivity and specificity to predict safe driving. Driving simulators can be used to test fitness to drive. Several studies have found strong correlation between driving simulator performance and on-the-road driving. However, access to driving simulators is restricted to specialists and simulators are too expensive, large, and complex to allow easy access to older drivers or physicians advising them. An easily accessible, Web-based, cognitive screening test could offer a solution to this problem. The World Wide Web allows easy dissemination of the test software and implementation of the scoring algorithm on a central server, allowing generation of a dynamically growing database with normative values and ensures that all users have access to the same up-to-date normative values.

Objective

In this pilot study, we present the novel Web-based Bern Cognitive Screening Test (wBCST) and investigate whether it can predict poor simulated driving performance in healthy and cognitive-impaired participants.

Methods

The wBCST performance and simulated driving performance have been analyzed in 26 healthy younger and 44 healthy older participants as well as in 10 older participants with cognitive impairment. Correlations between the two tests were calculated. Also, simulated driving performance was used to group the participants into good performers (n=70) and poor performers (n=10). A receiver-operating characteristic analysis was calculated to determine sensitivity and specificity of the wBCST in predicting simulated driving performance.

Results

The mean wBCST score of the participants with poor simulated driving performance was reduced by 52%, compared to participants with good simulated driving performance (P<.001). The area under the receiver-operating characteristic curve was 0.80 with a 95% confidence interval 0.68-0.92.

Conclusions

When selecting a 75% test score as the cutoff, the novel test has 83% sensitivity, 70% specificity, and 81% efficiency, which are good values for a screening test. Overall, in this pilot study, the novel Web-based computer test appears to be a promising tool for supporting clinicians in fitness-to-drive assessments of older drivers. The Web-based distribution and scoring on a central computer will facilitate further evaluation of the novel test setup. We expect that in the near future, Web-based computer tests will become a valid and reliable tool for clinicians, for example, when assessing fitness to drive in older drivers.