The Montreal Cognitive Assessment: Is It Suitable for Identifying Mild Cognitive Impairment in Parkinson's Disease?

Screening for Cognitive Impairment in Movement Disorders: Comparison of the Montreal Cognitive Assessment and Quick Mild Cognitive Impairment Screen in Parkinson's Disease and Lewy Body Dementia

Background

The Montreal Cognitive Assessment (MoCA) is recommended by the Movement Disorder Society for cognitive testing in movement disorders including Parkinson's disease (PD) and lewy body dementia. Few studies have compared cognitive screening instruments in these diseases, which overlap clinically.

Objective

To compare the MoCA and Quick Mild Cognitive Impairment (Qmci) screen in this population.

Methods

Patients attending memory and movement disorder clinics associated with a university hospital had the MoCA and Qmci screen performed and diagnostic accuracy compared with the area under the receiver operating characteristic curve (AUC). Duration and severity of movement disorders was assessed using the Unified PD Rating Scale (UPDRS).

Results

In total, 133 assessments were available, median age 74±5. Median education was 11±4 years and 65% were male. Median total UPDRS score was 37±26. Median Qmci screen was 51±27, median MoCA was 19±10. There were statistically significant differences in test scores between those with subjective symptoms but normal cognition, mild cognitive impairment (MCI) and dementia (p < 0.001). The Qmci screen had significantly greater accuracy differentiating normal cognition from MCI versus the MoCA (AUC 0.90 versus 0.72, p = 0.01). Both instruments had similar accuracy in identifying cognitive impairment and separating MCI from dementia. The median administration time for the Qmci screen and MoCA were 5.19 and 9.24 minutes (p < 0.001), respectively.

Conclusions

Both the MoCA and Qmci screen have good to excellent accuracy in a population with movement disorders experiencing cognitive symptoms. The Qmci screen was significantly more accurate for those with early symptoms and had a shorter administration time.

Achieving trust in health-behavior-change artificial intelligence apps (HBC-AIApp) development: a multi-perspective guide

OBJECTIVE

Trust determines the success of Health-Behavior-Change Artificial Intelligence Apps (HBC-AIApp). Developers of such apps need theory-based practical methods that can guide them in achieving such trust. Our study aimed to develop a comprehensive conceptual model and development process that can guide developers how to build HBC-AIApp in order to support trust creation among the app's users.

METHODS

We apply a multi-disciplinary approach where medical informatics, human-centered design, and holistic health methods are integrated to address the trust challenge in HBC-AIApps. The integration extends a conceptual model of trust in AI developed by Jermutus et al., whose properties guide the extension of the IDEAS (integrate, design, assess, and share) HBC-App development process.

RESULTS

The HBC-AIApp framework consists of three main blocks: (1) system development methods that study the users' complex reality, hence, their perceptions, needs, goals and environment; (2) mediators and other stakeholders who are important for developing and operating the HBC-AIApp, boundary objects that examine users' activities via the HBC-AIApp; and (3) the HBC-AIApp's structural components, AI logic, and physical implementation. These blocks come together to provide the extended conceptual model of trust in HBC-AIApps and the extended IDEAS process.

DISCUSSION

The developed HBC-AIApp framework drew from our own experience in developing trust in HBC-AIApp. Further research will focus on studying the application of the proposed comprehensive HBC-AIApp development framework and whether applying it supports trust creation in such apps.

Early identification of subjective cognitive functional decline among patients with Parkinson's disease: a longitudinal pilot study

Practical methods for early identification of Parkinson's disease (PD) mild cognitive impairment (PD-MCI) through changes in real-life daily functioning are scarce. The aim of the study was to examine whether the cognitive functional (CF) feature, comprising of seven self-reported Movement Disorder Society's (MDS) Unified Parkinson's Disease Rating Scale (UPDRS) items, predicts PD patients' cognitive functional status after a year. We conducted a 1-year follow-up of 34 PD patients (50-78 year; 70.6% men) suspected of MCI using the following measures: the MDS-UPDRS, UPDRS-CF feature, Beck Depression Inventory (BDI), Montreal Cognitive Assessment (MoCA), Trail Making Test (TMT), Parkinson's Disease Cognitive Functional Rating Scale (PD-CFRS), and Daily Living Questionnaire (DLQ). The first and second UPDRS-CF feature scores, and additional measures at the 1-year follow-up significantly correlated. Hierarchical regression revealed that the initial MoCA, TMT, and BDI scores predicted the second UPDRS-CF, and the first UPDRS-CF predicted 31% of the second PD-CFRS score variance. Depression moderated the relationship between the first UPDRS-CF score and the DLQ Part A. These results suggest practical, self-reported, daily functional markers for identifying gradual decline in PD patients. They consider the patients' heterogeneity, underlying cognitive pathology, and implications on daily functioning, health, and well-being.

Regression-Based Normative Data for the Montreal Cognitive Assessment (MoCA) and Its Memory Index Score (MoCA-MIS) for Individuals Aged 18-91

(1) Background: There is a need for a brief assessment of cognitive function, both in patient care and scientific research, for which the Montreal Cognitive Assessment (MoCA) is a psychometrically reliable and valid tool. However, fine-grained normative data allowing for adjustment for age, education, and/or sex are lacking, especially for its Memory Index Score (MIS). (2) Methods: A total of 820 healthy individuals aged 18-91 (366 men) completed the Dutch MoCA (version 7.1), of whom 182 also completed the cued recall and recognition memory subtests enabling calculation of the MIS. Regression-based normative data were computed for the MoCA Total Score and MIS, following the data-handling procedure of the Advanced Neuropsychological Diagnostics Infrastructure (ANDI). (3) Results: Age, education level, and sex were significant predictors of the MoCA Total Score (Conditional R2 = 0.4, Marginal R2 = 0.12, restricted maximum likelihood (REML) criterion at convergence: 3470.1) and MIS (Marginal R2 = 0.14, REML criterion at convergence: 682.8). Percentile distributions are presented that allow for age, education and sex adjustment for the MoCA Total Score and the MIS. (4) Conclusions: We present normative data covering the full adult life span that can be used for the screening for overall cognitive deficits and memory impairment, not only in older people with or people at risk of neurodegenerative disease, but also in younger individuals with acquired brain injury, neurological disease, or non-neurological medical conditions.

Capturing Subjective Mild Cognitive Decline in Parkinson’s Disease

This study aimed to capture subjective daily functional cognitive decline among patients with Parkinson’s disease. Participants (40–79 y; 78 with Parkinson’s disease and 41 healthy matched controls) completed the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS), Parkinson’s Disease Cognitive Functional Rating Scale (CFRS), Daily Living Questionnaire (DLQ), and Time Organisation and Participation Scale (TOPS) questionnaires. Patients with Parkinson’s disease were divided into groups with or without suspected mild cognitive decline according to their scores on the Cognitive Functional (CF) feature, which is based on certain items of the MDS-UPDRS. Significant between-group differences were found in the DLQ and TOPS scores. Significant correlations were found among the questionnaire results, with specific DLQ and TOPS items accounting for 35% of the variance in the CF feature, which correlated with daily cognitive functional states. This study’s results are relevant for detecting subtle deficits in Parkinson’s disease patients suspected of mild cognitive decline, which can affect health and quality of life and relates to risk for later dementia.

Optimization of cognitive assessment in Parkinsonisms by applying artificial intelligence to a comprehensive screening test

The assessment of cognitive deficits is pivotal for diagnosis and management in patients with parkinsonisms. Low levels of correspondence are observed between evaluations assessed with screening cognitive tests in comparison with those assessed with in-depth neuropsychological batteries. A new tool, we named CoMDA (Cognition in Movement Disorders Assessment), was composed by merging Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Frontal Assessment Battery (FAB). In total, 500 patients (400 with Parkinson's disease, 41 with vascular parkinsonism, 31 with progressive supranuclear palsy, and 28 with multiple system atrophy) underwent CoMDA (level 1-L1) and in-depth neuropsychological battery (level 2-L2). Machine learning was developed to classify the CoMDA score and obtain an accurate prediction of the cognitive profile along three different classes: normal cognition (NC), mild cognitive impairment (MCI), and impaired cognition (IC). The classification accuracy of CoMDA, assessed by ROC analysis, was compared with MMSE, MoCA, and FAB. The area under the curve (AUC) of CoMDA was significantly higher than that of MMSE, MoCA and FAB (p < 0.0001, p = 0.028 and p = 0.0007, respectively). Among 15 different algorithmic methods, the Quadratic Discriminant Analysis algorithm (CoMDA-ML) showed higher overall-metrics performance levels in predictive performance. Considering L2 as a 3-level continuous feature, CoMDA-ML produces accurate and generalizable classifications: micro-average ROC curve, AUC = 0.81; and AUC = 0.85 for NC, 0.67 for MCI, and 0.83 for IC. CoMDA and COMDA-ML are reliable and time-sparing tools, accurate in classifying cognitive profile in parkinsonisms.This study has been registered on ClinicalTrials.gov (NCT04858893).

Internetwork Connectivity Predicts Cognitive Decline in Parkinson’s and Is Altered by Genetic Variants

In Parkinson’s disease (PD) functional changes in the brain occur years before significant cognitive symptoms manifest yet core large-scale networks that maintain cognition and predict future cognitive decline are poorly understood. The present study investigated internetwork functional connectivity of visual (VN), anterior and posterior default mode (aDMN, pDMN), left/right frontoparietal (LFPN, RFPN), and salience (SN) networks in 63 cognitively normal PD (PDCN) and 43 healthy controls who underwent resting-state functional MRI. The functional relevance of internetwork coupling topologies was tested by their correlations with baseline cognitive performance in each group and with 2-year cognitive changes in a PDCN subsample. To disentangle heterogeneity in neurocognitive functioning, we also studied whether α-synuclein (SNCA) and microtubule-associated protein tau (MAPT) variants alter internetwork connectivity and/or accelerate cognitive decline. We found that internetwork connectivity was largely preserved in PDCN, except for reduced pDMN-RFPN/LFPN couplings, which correlated with poorer baseline global cognition. Preserved internetwork couplings also correlated with domain-specific cognition but differently for the two groups. In PDCN, stronger positive internetwork coupling topologies correlated with better cognition at baseline, suggesting a compensatory mechanism arising from less effective deployment of networks that supported cognition in healthy controls. However, stronger positive internetwork coupling topologies typically predicted greater longitudinal decline in most cognitive domains, suggesting that they were surrogate markers of neuronal vulnerability. In this regard, stronger aDMN-SN, LFPN-SN, and/or LFPN-VN connectivity predicted longitudinal decline in attention, working memory, executive functioning, and visual cognition, which is a risk factor for dementia. Coupling strengths of some internetwork topologies were altered by genetic variants. PDCN carriers of the SNCA risk allele showed amplified anticorrelations between the SN and the VN/pDMN, which supported cognition in healthy controls, but strengthened pDMN-RFPN connectivity, which maintained visual memory longitudinally. PDCN carriers of the MAPT risk allele showed greater longitudinal decline in working memory and increased VN-LFPN connectivity, which in turn predicted greater decline in visuospatial processing. Collectively, the results suggest that cognition is maintained by functional reconfiguration of large-scale internetwork communications, which are partly altered by genetic risk factors and predict future domain-specific cognitive progression.

Patients' Self-Report and Handwriting Performance Features as Indicators for Suspected Mild Cognitive Impairment in Parkinson's Disease

Early identification of mild cognitive impairment (MCI) in Parkinson's disease (PD) patients can lessen emotional and physical complications. In this study, a cognitive functional (CF) feature using cognitive and daily living items of the Unified Parkinson's Disease Rating Scale served to define PD patients as suspected or not for MCI. The study aimed to compare objective handwriting performance measures with the perceived general functional abilities (PGF) of both groups, analyze correlations between handwriting performance measures and PGF for each group, and find out whether participants' general functional abilities, depression levels, and digitized handwriting measures predicted this CF feature. Seventy-eight participants diagnosed with PD by a neurologist (25 suspected for MCI based on the CF feature) completed the PGF as part of the Daily Living Questionnaire and wrote on a digitizer-affixed paper in the Computerized Penmanship Handwriting Evaluation Test. Results indicated significant group differences in PGF scores and handwriting stroke width, and significant medium correlations between PGF score, pen-stroke width, and the CF feature. Regression analyses indicated that PGF scores and mean stroke width accounted for 28% of the CF feature variance above age. Nuances of perceived daily functional abilities validated by objective measures may contribute to the early identification of suspected PD-MCI.

Gender Differences in State Anxiety Related to Daily Function Among Older Adults During the COVID-19 Pandemic: Questionnaire Study

BACKGROUND

The COVID-19 pandemic poses a challenge to people's day-to-day functioning and emotional and physical health, especially among older adults.

OBJECTIVE

The aim of this study is to analyze gender differences in state anxiety, daily functional self-actualization, and functional cognition as well as the relationships among those factors in older adults during the COVID-19 pandemic lockdown.

METHODS

We collected data on the web from a sample of 204 people (102 men and 102 women) aged 60 years and older. In addition to a demographic questionnaire, we used the State-Trait Personality Inventory to assess state anxiety, the Daily Functional Actualization questionnaire to evaluate daily functional self-actualization, and the Daily Living Questionnaire to measure functional cognition.

RESULTS

Significant gender differences were found for state anxiety (t₂₀₂=-2.36, P=.02); daily functional self-actualization (t₂₀₂=2.15, P=.03); and the functional cognition components: complex tasks (Z=-3.07, P=.002); cognitive symptoms that might be interfering (Z=-2.15, P=.028); executive functions (Z=-2.21, P=.024); and executive function monitoring (Z=-2.21, P=.027). Significant medium correlations were found between both state anxiety level and daily functional self-actualization (r=-0.62, P<.001) and functional cognition (r=0.37-0.40, P<.001). Gender predicted 3% of the variance in state anxiety level, while daily functional self-actualization predicted 41% and complex activities (Daily Living Questionnaire) predicted an additional 3% (F_3,200=58.01, P<.001).

CONCLUSIONS

In older adults, anxiety is associated with cognitive decline, which may harm daily functional abilities and lead to social isolation, loneliness, and decreased well-being. Self-awareness and knowledge of gender differences and relationships between common available resources of daily functional self-actualization and functional cognition with anxiety may be strengthening factors in crisis periods such as the COVID-19 pandemic.

On the importance of using local tests and local norms in the assessment of memory

The current study compared the assessment of memory with a translated story recall test and its original published norms and an equivalent local test with local norms. Analyses used data from 232 individuals with memory complaints who underwent neuropsychological evaluation at an outpatient memory clinic. One group of participants completed a translated test (N = 126) and another group completed a local test (N = 106). Additionally, participants completed tasks of word list recall, picture naming, and verbal fluency, all having local norms. The results showed that raw scores on the delayed story recall test, and on all other cognitive tasks, did not differ across groups, and the cross-task correlations were significant and similar in size in both groups. Yet, there was an interaction between group and standardized tests scores, whereby the standardized scores on the translated story recall test were equivalent to population mean, whereas all other scores fell below the mean. Conversion of raw scores to the original norms indicated that the performance of individuals with memory complaints was intact, while conversion of scores on a local test to local norms revealed the expected memory impairment. The findings highlight the importance of using local tests and local norms in the assessment of memory.

Dual-Task Effects During a Motor-Cognitive Task in Parkinson's Disease: Patterns of Prioritization and the Influence of Cognitive Status

People with Parkinson’s disease (PD) experience greater difficulties during dual task (DT) walking compared to healthy controls, but factors explaining the variance in DT costs remain largely unknown. Additionally, as cognitive impairments are common in PD it is important to understand whether cognitive status influences the strategies used during DT paradigms. The study aimed to (1) explore DT costs on gait and cognition during DT walking, (2) investigate factors associated with DT costs, and (3) to investigate to what extent patterns of DT costs and prioritization differed according to cognitive status. A total of 93 people with Parkinson’s disease were examined when walking in single and DT conditions. Information regarding demographics, PD severity, mobility, and cognitive and affective symptoms was collected, and an extensive neuropsychological test battery was used to classify whether participants had mild cognitive impairment (PD MCI) or not (PD non-MCI). Dual task costs were observed across all gait domains except asymmetry. Cognitive status was associated with DT costs on both gait and cognition. Nonmotor experiences of daily living were further associated with DT cost on cognition, and TUG-cog associated with DT cost on gait. People with PD MCI had larger DT costs on gait than PD non-MCI. Strategies differed according to cognitive status, whereby PD MCI used a posture-second strategy, and PD non-MCI used a posture-first strategy. Once verified in future studies, these results can inform clinicians and researchers when tailoring DT training paradigms to the specific characteristics of people with PD.

DailyCog: A Real-World Functional Cognitive Mobile Application for Evaluating Mild Cognitive Impairment (MCI) in Parkinson's Disease

Parkinson's disease (PD) is the second most common progressive neurodegenerative disorder affecting patient functioning and quality of life. Aside from the motor symptoms of PD, cognitive impairment may occur at early stages of PD and has a substantial impact on patient emotional and physical health. Detecting these early signs through actual daily functioning while the patient is still functionally independent is challenging. We developed DailyCog-a smartphone application for the detection of mild cognitive impairment. DailyCog includes an environment that simulates daily tasks, such as making a drink and shopping, as well as a self-report questionnaire related to daily events performed at home requiring executive functions and visual-spatial abilities, and psychomotor speed. We present the detailed design of DailyCog and discuss various considerations that influenced the design. We tested DailyCog on patients with mild cognitive impairment in PD. Our case study demonstrates how the markers we used coincide with the cognitive levels of the users. We present the outcome of our usability study that found that most users were able to use our app with ease, and provide details on how various features were used, along with some of the difficulties that were identified.