scholarly journals Mapping Actuarial Criteria for Parkinson’s Disease-Mild Cognitive Impairment onto Data-Driven Cognitive Phenotypes

2021 ◽  
Vol 12 (1) ◽  
pp. 54
Author(s):  
Lauren E. Kenney ◽  
Adrianna M. Ratajska ◽  
Francesca V. Lopez ◽  
Catherine C. Price ◽  
Melissa J. Armstrong ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Neuropsychological Testing ◽  
Data Driven ◽  
Prevalence Rates ◽  
Cluster Analyses ◽  
Cluster Membership ◽  
Dementia Risk

Prevalence rates for mild cognitive impairment in Parkinson’s disease (PD-MCI) remain variable, obscuring the diagnosis’ predictive utility of greater dementia risk. A primary factor of this variability is inconsistent operationalization of normative cutoffs for cognitive impairment. We aimed to determine which cutoff was optimal for classifying individuals as PD-MCI by comparing classifications against data-driven PD cognitive phenotypes. Participants with idiopathic PD (n = 494; mean age 64.7 ± 9) completed comprehensive neuropsychological testing. Cluster analyses (K-means, Hierarchical) identified cognitive phenotypes using domain-specific composites. PD-MCI criteria were assessed using separate cutoffs (−1, −1.5, −2 SD) on ≥2 tests in a domain. Cutoffs were compared using PD-MCI prevalence rates, MCI subtype frequencies (single/multi-domain, executive function (EF)/non-EF impairment), and validity against the cluster-derived cognitive phenotypes (using chi-square tests/binary logistic regressions). Cluster analyses resulted in similar three-cluster solutions: Cognitively Average (n = 154), Low EF (n = 227), and Prominent EF/Memory Impairment (n = 113). The −1.5 SD cutoff produced the best model of cluster membership (PD-MCI classification accuracy = 87.9%) and resulted in the best alignment between PD-MCI classification and the empirical cognitive profile containing impairments associated with greater dementia risk. Similar to previous Alzheimer’s work, these findings highlight the utility of comparing empirical and actuarial approaches to establish concurrent validity of cognitive impairment in PD.

scholarly journals Response to “Parkinson's disease mild cognitive impairment classifications and neurobehavioral symptoms”

2018 ◽  
Vol 30 (9) ◽  
pp. 1415-1415
Author(s):  
Kyla-Louise Horne ◽  
Daniel J. Myall ◽  
Michael R. MacAskill ◽  
Tim J. Anderson ◽  
John C. Dalrymple-Alford
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Conversion Rate ◽  
Significant Risk ◽  
Cognitive Domain ◽  
Community Needs ◽  
Dementia Risk ◽  
Neurobehavioral Symptoms

A recent paper, “Parkinson's disease mild cognitive impairment classifications and neurobehavioral symptoms” (McDermott et al., 2017), provides an interesting comparison of the influence of different criteria for Parkinson's disease with mild cognitive impairment (PD-MCI) on progression to dementia (PDD). Unfortunately, McDermott et al. (2017) incorrectly stated that “only 21% of PD-MCI participants (identified with a 1.5 SD cut-off) converted to PDD within four years” (p.6) in our study (Wood et al., 2016). However, the important point made by Wood et al. (2016) was that the proportion of conversions to PDD was 51% when the PD-MCI diagnosis required a minimum of two 1.5 SD impairments within any single cognitive domain, whereas additional PD-MCI patients classified with one impairment at 1.5 SD in each of the two domains (but never two impairments in the same domain) had a non-significant risk of dementia relative to non-MCI patients (11% vs. 6% converted, respectively). Our PDD conversion rate was 38% when combining both 1.5 SD criteria (21/56 PD-MCI patients vs. 4/65 non-MCI patients converted); McDermott et al. (2017) found a 42% conversion rate over three years for similarly described PD-MCI patients (10/24 PD-MCI patients vs. 0/27 non-MCI patients converted). Our study was also part of a multinational study (n = 467) showing that PD-MCI has predictive validity beyond known demographic and PD-specific factors of influence (Hoogland et al., 2017). All three studies found that multiple cognitive domain impairments are common in PD-MCI. Nonetheless, the research community needs to clarify the association between PD-MCI subtypes and, especially, the optimal cognitive markers for dementia risk in PD patients.

Diagnostic and screening power of neuropsychological testing in detecting mild cognitive impairment in Parkinson’s disease

2013 ◽  
Vol 120 (4) ◽  
pp. 627-633 ◽  
Author(s):  
Roberta Biundo ◽  
Luca Weis ◽  
Manuela Pilleri ◽  
Silvia Facchini ◽  
Patrizia Formento-Dojot ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Neuropsychological Testing

scholarly journals Cognitive Profiles in Parkinson’s Disease and Their Relation to Dementia: A Data-Driven Approach

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Inga Liepelt-Scarfone ◽  
Susanne Gräber ◽  
Monika Fruhmann Berger ◽  
Anne Feseker ◽  
Gülsüm Baysal ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Hierarchical Cluster ◽  
Individual Performance ◽  
Data Driven ◽  
Data Sets ◽  
Cognitive Profiles ◽  
Cluster Analyses ◽  
Data Driven Approach

Parkinson’s disease is characterized by a substantial cognitive heterogeneity, which is apparent in different profiles and levels of severity. To date, a distinct clinical profile for patients with a potential risk of developing dementia still has to be identified. We introduce a data-driven approach to detect different cognitive profiles and stages. Comprehensive neuropsychological data sets from a cohort of 121 Parkinson’s disease patients with and without dementia were explored by a factor analysis to characterize different cognitive domains. Based on the factor scores that represent individual performance in each domain, hierarchical cluster analyses determined whether subgroups of Parkinson’s disease patients show varying cognitive profiles. A six-factor solution accounting for 65.2% of total variance fitted best to our data and revealed high internal consistencies (Cronbach’s alpha coefficients>0.6). The cluster analyses suggested two independent patient clusters with different cognitive profiles. They differed only in severity of cognitive impairment and self-reported limitation of activities of daily living function but not in motor performance, disease duration, or dopaminergic medication. Based on a data-driven approach, divers cognitive profiles were identified, which separated early and more advanced stages of cognitive impairment in Parkinson’s disease without dementia. Importantly, these profiles were independent of motor progression.

scholarly journals Retrospective Assessment of Movement Disorder Society Criteria for Mild Cognitive Impairment in Parkinson’s Disease

2015 ◽  
Vol 21 (2) ◽  
pp. 137-145 ◽  
Author(s):  
Andrea M. Loftus ◽  
Romola S. Bucks ◽  
Meghan Thomas ◽  
Robert Kane ◽  
Caitlin Timms ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Movement Disorder ◽  
Rating Scale ◽  
Neuropsychological Testing ◽  
Simulation Method ◽  
Movement Disorder Society

AbstractA Movement Disorder Society (MDS) taskforce recently proposed diagnostic criteria for Parkinson’s disease with features of mild cognitive impairment (PD-MCI). This study first examined the prevalence and nature of PD-MCI in a non-demented cohort using the MDS criteria. Using the generic Monte Carlo simulation method developed by Crawford and colleagues (2007), this study then estimated the base rate of the representative population who would demonstrate PD-MCI due to chance alone. A total of 104 participants with idiopathic PD underwent extensive motor and neuropsychological testing at baseline and 2 years later. The Unified Parkinson’s Disease Rating Scale (UPDRS) was used to assess motor symptoms of PD and a range of established neuropsychological tests was used to assess PD-MCI in accord with MDS criteria. In accord with MDS criteria, 38% of this cohort demonstrated PD-MCI at baseline and 48% at follow-up. Of the 36 participants in the multiple-domain PD-MCI subtype at time-1, 9 (25%) demonstrated no PD-MCI at follow up. Analysis revealed that approximately 13% of the representative population would demonstrate abnormally low scores for 2 of the 9 tests used, thereby meeting MDS criteria for PD-MCI. Clinicians and researchers need to approach a single diagnosis (i.e., based on one assessment) of PD-MCI with considerable caution. (JINS, 2015, 21, 137–145)

scholarly journals Influence of Different Cut-Off Values on the Diagnosis of Mild Cognitive Impairment in Parkinson's Disease

2011 ◽  
Vol 2011 ◽  
pp. 1-7 ◽  
Author(s):  
Inga Liepelt-Scarfone ◽  
Susanne Graeber ◽  
Anne Feseker ◽  
Gülsüm Baysal ◽  
Jana Godau ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Predictive Accuracy ◽  
Neuropsychological Testing ◽  
Population Based ◽  
Healthy Population ◽  
Increased Risk ◽  
Definition Of

Comparable to Alzheimer's disease, mild cognitive impairment in Parkinson's disease (PD-MCI) is associated with an increased risk for dementia. However different definitions of PD-MCI may have varying predictive accuracy for dementia. In a cohort of 101 nondemented Parkinson patients who underwent neuropsychological testing, the frequency of PD-MCI subjects and PD-MCI subtypes (i.e., amnestic/nonamnestic) was determined by use of varying healthy population-based cut-off values. We also investigated the association between defined PD-MCI groups and ADL scales. Varying cut-off values for the definition of PD-MCI were found to affect frequency of PD-MCI subjects (9.9%–92.1%) and, maybe more important, lead to a “shift” of proportion of detected PD-MCI subtypes especially within the amnestic single-domain subtype. Models using a strict cut-off value were significantly associated with lower ADL scores. Thus, the use of defined cut-off values for the definition of PD-MCI is highly relevant for comparison purposes. Strict cut-off values may have a higher predictive value for dementia.

Assessment of White Matter Lesions in Parkinson's Disease: Voxel-based Analysis and Tract-based Spatial Statistics Analysis of Parkinson's Disease with Mild Cognitive Impairment

2020 ◽  
Vol 17 (4) ◽  
pp. 480-486
Author(s):  
Wei Pu ◽  
Xudong Shen ◽  
Mingming Huang ◽  
Zhiqian Li ◽  
Xianchun Zeng ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
White Matter ◽  
Corpus Callosum ◽  
Fractional Anisotropy ◽  
Spatial Statistics ◽  
Diffusion Tensor ◽  
Tract Based Spatial Statistics

Objective: Application of diffusion tensor imaging (DTI) to explore the changes of FA value in patients with Parkinson's disease (PD) with mild cognitive impairment. Methods: 27 patients with PD were divided into PD with mild cognitive impairment (PD-MCI) group (n = 7) and PD group (n = 20). The original images were processed using voxel-based analysis (VBA) and tract-based spatial statistics (TBSS). Results: The average age of pd-mci group was longer than that of PD group, and the course of disease was longer than that of PD group. Compared with PD group, the voxel based analysis-fractional anisotropy (VBA-FA) values of PD-MCI group decreased in the following areas: bilateral frontal lobe, bilateral temporal lobe, bilateral parietal lobe, bilateral subthalamic nucleus, corpus callosum, and gyrus cingula. Tract-based spatial statistics-fractional anisotropy (TBSS-FA) values in PD-MCI group decreased in bilateral corticospinal tract, anterior cingulum, posterior cingulum, fornix tract, bilateral superior thalamic radiation, corpus callosum(genu, body and splenium), bilateral uncinate fasciculus, bilateral inferior longitudinal fasciculus, bilateral superior longitudinal fasciculus, bilateral superior fronto-occipital fasciculus, bilateral inferior fronto-occipital fasciculus, and bilateral parietal-occipital tracts. The mean age of onset in the PD-MCI group was greater than that in the PD group, and the disease course was longer than that in the PD group. Conclusion: DTI-based VBA and TBSS post-processing methods can detect abnormalities in multiple brain areas and white matter fiber tracts in PD-MCI patients. Impairment of multiple cerebral cortex and white matter fiber pathways may be an important causes of cognitive dysfunction in PD-MCI.

scholarly journals Donepezil for mild cognitive impairment in Parkinson’s disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kyoungwon Baik ◽  
Seon Myeong Kim ◽  
Jin Ho Jung ◽  
Yang Hyun Lee ◽  
Seok Jong Chung ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Treatment Group ◽  
Outcome Measures ◽  
Rating Scale ◽  
Secondary Outcome ◽  
Control Group ◽  
Significant Difference

AbstractWe investigated the efficacy of donepezil for mild cognitive impairment in Parkinson’s disease (PD-MCI). This was a prospective, non-randomized, open-label, two-arm study. Eighty PD-MCI patients were assigned to either a treatment or control group. The treatment group received donepezil for 48 weeks. The primary outcome measures were the Korean version of Mini-Mental State Exam and Montreal Cognitive Assessment scores. Secondary outcome measures were the Clinical Dementia Rating, Unified Parkinson’s Disease Rating Scale part III, Clinical Global Impression scores. Progression of dementia was assessed at 48-week. Comprehensive neuropsychological tests and electroencephalography (EEG) were performed at baseline and after 48 weeks. The spectral power ratio of the theta to beta2 band (TB2R) in the electroencephalogram was analyzed. There was no significant difference in the primary and secondary outcome measures between the two groups. However, the treatment group showed a significant decrease in TB2R at bilateral frontotemporoparietal channels compared to the control group. Although we could not demonstrate improvements in the cognitive functions, donepezil treatment had a modulatory effect on the EEG in PD-MCI patients. EEG might be a sensitive biomarker for detecting changes in PD-MCI after donepezil treatment.

Analyses of Visuospatial and Visuoperceptual Errors as Predictors of Dementia in Parkinson’s Disease Patients with Subjective Cognitive Decline and Mild Cognitive Impairment

2020 ◽  
pp. 1-11
Author(s):  
Iván Galtier ◽  
Antonieta Nieto ◽  
María Mata ◽  
Jesús N. Lorenzo ◽  
José Barroso
Keyword(s):  
Risk Factors ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Poor Performance ◽  
Subjective Cognitive Decline ◽  
Independent Risk Factors

ABSTRACT Objective: Subjective cognitive decline (SCD) and mild cognitive impairment (MCI) in Parkinson’s disease (PD) are considered as the risk factors for dementia (PDD). Posterior cortically based functions, such as visuospatial and visuoperceptual (VS-VP) processing, have been described as predictors of PDD. However, no investigations have focused on the qualitative analysis of the Judgment of Line Orientation Test (JLOT) and the Facial Recognition Test (FRT) in PD-SCD and PD-MCI. The aim of this work was to study the VS-VP errors in JLOT and FRT. Moreover, these variables are considered as predictors of PDD. Method: Forty-two PD patients and 19 controls were evaluated with a neuropsychological protocol. Patients were classified as PD-SCD and PD-MCI. Analyses of errors were conducted following the procedure described by Ska, Poissant, and Joanette (1990). Follow-up assessment was conducted to a mean of 7.5 years after the baseline. Results: PD-MCI patients showed a poor performance in JLOT and FRT total score and made a greater proportion of severe intraquadrant (QO2) and interquadrant errors (IQO). PD-SCD showed a poor performance in FRT and made mild errors in JLOT. PD-MCI and QO2/IQO errors were independent risk factors for PDD during the follow-up. Moreover, the combination of both PD-MCI diagnosis and QO2/IQO errors was associated with a greater risk. Conclusions: PD-MCI patients presented a greater alteration in VS-VP processing observable by the presence of severe misjudgments. PD-SCD patients also showed mild difficulties in VS-SP functions. Finally, QO2/IQO errors in PD-MCI are a useful predictor of PDD, more than PD-MCI diagnosis alone.

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