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.

scholarly journals Parkinson's disease mild cognitive impairment classifications and neurobehavioral symptoms clarification letter

2018 ◽  
Vol 30 (9) ◽  
pp. 1417-1417
Author(s):  
Richard Camicioli ◽  
Kirstie Mcdermott
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Conversion Rate ◽  
Cognitive Domain ◽  
Targeted Interventions ◽  
Conversion Rates ◽  
Incident Cases

We thank Ms. Horne et al. for the clarification of our misquoting of their paper (Wood et al., 2016). They clarify that 21% of their overall sample of patients with Parkinson's disease (PD-MCI) converted to dementia in over four years, which we erroneously attributed to the mild cognitive impairment (MCI) group in our discussion (McDermott et al., 2017). This was virtually identical to our overall conversion rate of 20%. Their conversion rate of patients with PD-MCI, as defined by two cognitive tests impaired (1.5 SD) within a single cognitive domain, was 51%, whereas the conversion rate was 38% when the PD-MCI group included patients with impairment within and between cognitive domains. Their conversion rates are similar to our rate of 42% (as defined with 1.5 SD impairment within or across domains) and the rate of 39% in a study with five-years of follow-up of incident cases (Pedersen et al., 2017). Our overall conversion occurred over a slightly shorter time span. In addition to conversion rates, all the studies acknowledge that some patients can revert to normal cognitive status, which varies based on classification criteria and length of follow-up. Comparable conversion across studies using similar criteria is reassuring and can encourage planning of targeted interventions (Hoogland et al., 2017).

scholarly journals Correlation of MRI Visual Scales with Neuropsychological Profile in Mild Cognitive Impairment of Parkinson’s Disease

2017 ◽  
Vol 2017 ◽  
pp. 1-6 ◽  
Author(s):  
Luiz Felipe Vasconcellos ◽  
João Santos Pereira ◽  
Marcelo Adachi ◽  
Denise Greca ◽  
Manuela Cruz ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Verbal Learning ◽  
Stroop Test ◽  
Memory Test ◽  
Cognitive Domain ◽  
Cortical Atrophy ◽  
Neuropsychological Profile

Few studies have evaluated magnetic resonance imaging (MRI) visual scales in Parkinson’s disease-Mild Cognitive Impairment (PD-MCI). We selected 79 PD patients and 92 controls (CO) to perform neurologic and neuropsychological evaluation. Brain MRI was performed to evaluate the following scales: Global Cortical Atrophy (GCA), Fazekas, and medial temporal atrophy (MTA). The analysis revealed that both PD groups (amnestic and nonamnestic) showed worse performance on several tests when compared to CO. Memory, executive function, and attention impairment were more severe in amnestic PD-MCI group. Overall analysis of frequency of MRI visual scales by MCI subtype did not reveal any statistically significant result. Statistically significant inverse correlation was observed between GCA scale and Mini-Mental Status Examination (MMSE), Montreal Cognitive Assessment (MoCA), semantic verbal fluency, Stroop test, figure memory test, trail making test (TMT) B, and Rey Auditory Verbal Learning Test (RAVLT). The MTA scale correlated with Stroop test and Fazekas scale with figure memory test, digit span, and Stroop test according to the subgroup evaluated. Visual scales by MRI in MCI should be evaluated by cognitive domain and might be more useful in more severely impaired MCI or dementia patients.

Olfaction and taste in Parkinson’s disease: the association with mild cognitive impairment and the single cognitive domain dysfunction

2019 ◽  
Vol 126 (5) ◽  
pp. 585-595 ◽  
Author(s):  
Maria Paola Cecchini ◽  
Angela Federico ◽  
Alice Zanini ◽  
Elisa Mantovani ◽  
Carla Masala ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Domain

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.

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.

Sign in / Sign up

Export Citation Format

Share Document