Incidence of mild cognitive impairment and dementia in Parkinson's disease: The Parkinson's disease cognitive impairment study

Background: Cognitive impairment in Parkinson's disease (PD) includes a spectrum varying from Mild Cognitive Impairment (PD-MCI) to PD Dementia (PDD). The main aim of the present study is to evaluate the incidence of PD-MCI, its rate of progression to dementia, and to identify demographic and clinical characteristics which predict cognitive impairment in PD patients. Methods: PD patients from a large hospital-based cohort who underwent at least two comprehensive neuropsychological evaluations were retrospectively enrolled in the study. PD-MCI and PDD were diagnosed according to the Movement Disorder Society criteria. Incidence rates of PD-MCI and PDD were estimated. Clinical and demographic factors predicting PD-MCI and dementia were evaluated using Cox proportional hazard model. Results: Out of 139 enrolled PD patients, 84 were classified with normal cognition (PD-NC), while 55 (39.6%) fulfilled the diagnosis of PD-MCI at baseline. At follow-up (mean follow-up 23.5 ± 10.3 months) 28 (33.3%) of the 84 PD-NC at baseline developed MCI and 4 (4.8%) converted to PDD. The incidence rate of PD-MCI was 184.0/1000 pyar (95% CI 124.7-262.3). At multivariate analysis a negative association between education and MCI development at follow-up was observed (HR 0.37, 95% CI 0.15-0.89; p = 0.03). The incidence rate of dementia was 24.3/1000 pyar (95% CI 7.7-58.5). Out of 55 PD-MCI patients at baseline, 14 (25.4%) converted to PDD, giving an incidence rate of 123.5/1000 pyar (95% CI 70.3-202.2). A five time increased risk of PDD was found in PD patients with MCI at baseline (RR 5.09, 95% CI 1.60-21.4). Conclusion: Our study supports the relevant role of PD-MCI in predicting PDD and underlines the importance of education in reducing the risk of cognitive impairment

Adding Recognition Discriminability Index to the Delayed Recall Is Useful to Predict Conversion from Mild Cognitive Impairment to Alzheimer's Disease in the Alzheimer's Disease Neuroimaging Initiative

Background: Ongoing research is focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to Alzheimer's disease (AD). We investigated whether recognition memory tasks in combination with delayed recall measure of episodic memory and CSF biomarkers can predict MCI to AD conversion at 24-month follow-up. Methods: A total of 397 amnestic-MCI subjects from Alzheimer's disease Neuroimaging Initiative were included. Logistic regression modeling was done to assess the predictive value of all RAVLT measures, risk factors such as age, sex, education, APOE genotype, and CSF biomarkers for progression to AD. Estimating adjusted odds ratios was used to determine which variables would produce an optimal predictive model, and whether adding tests of interaction between the RAVLT Delayed Recall and recognition measures (traditional score and d-prime) would improve prediction of the conversion from a-MCI to AD. Results: 112 (28.2%) subjects developed dementia and 285 (71.8%) subjects did not. Of the all included variables, CSF Aβ1-42 levels, RAVLT Delayed Recall, and the combination of RAVLT Delayed Recall and d-prime were predictive of progression to AD (χ2 = 38.23, df = 14, p < 0.001). Conclusions: The combination of RAVLT Delayed Recall and d-prime measures may be predictor of conversion from MCI to AD in the ADNI cohort, especially in combination with amyloid biomarkers. A predictive model to help identify individuals at-risk for dementia should include not only traditional episodic memory measures (delayed recall or recognition), but also additional variables (d-prime) that allow the homogenization of the assessment procedures in the diagnosis of MCI.Fil: Russo, María Julieta. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Campos, Jorge. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; ArgentinaFil: Vázquez, Silvia. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; ArgentinaFil: Sevlever, Gustavo. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Allegri, Ricardo Francisco. Fundación para la Lucha Contra las Enfermedades Neurológicas de la Infancia. Instituto de Investigaciones Neurológicas "Raúl Carrea"; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Executive functions in the elderly with Mild Cognitive Impairment: a systematic review on motor and cognitive inhibition, conflict control and cognitive flexibility

Background: Mild Cognitive Impairment (MCI) is a syndrome characterised by mild cognitive decline, on one or more domains, but which does not compromise daily functions. Several studies have investigated the relationship between MCI and deficit in executive functions (EFs) but, unlike robust evidence in the mnestic domain, the nature of executive deficits in the MCI population remains uncertain. Objectives: This systematic review aims to evaluate EFs in patients with MCI, considering inhibition (motor and cognitive), conflict control and cognitive flexibility. Method: The databases used for the search were PUBMED, PsycINFO, PsycARTICLES and MEDLINE. Eligibility criteria: use of specific paradigms for EFs assessment ("Wisconsin Card Sorting Test", "Stroop Task", "Go/No-Go Task", "Flanker Task"); age over 65, studies published in English. Exclusion criteria: presence of dementia; psychiatric disorders; stroke; cranial trauma; inclusion of participants with MCI in groups with healthy elderly or those with dementia. Results: Fifty-five studies were selected, namely: Stroop Task (N=30), WCST (N=14), Go/No-Go (N=9), Flanker Task (N=2). Results have shown in people with MCI deficits in all the EFs considered. Conclusions: The results of this review support the applicability of the four experimental tasks examined for the study of EFs in people with MCI. These paradigms are useful in research, diagnosis and therapeutic purposes, allowing obtaining an articulated EFs profile that can compromise the daily life in elderly. These EFs are not generally evaluated by standard assessment of MCI, but their evaluation can lead to a better knowledge of MCI and help in the diagnosis and treatment

A comparison of magnetic resonance imaging and neuropsychological examination in the diagnostic distinction of Alzheimer’s disease and behavioral variant frontotemporal dementia

The clinical distinction between Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) remains challenging and largely dependent on the experience of the clinician. This study investigates whether objective machine learning algorithms using supportive neuroimaging and neuropsychological clinical features can aid the distinction between both diseases. Retrospective neuroimaging and neuropsychological data of 166 participants (54 AD; 55 bvFTD; 57 healthy controls) was analyzed via a Naïve Bayes classification model. A subgroup of patients (n = 22) had pathologically-confirmed diagnoses. Results show that a combination of gray matter atrophy and neuropsychological features allowed a correct classification of 61.47% of cases at clinical presentation. More importantly, there was a clear dissociation between imaging and neuropsychological features, with the latter having the greater diagnostic accuracy (respectively 51.38 vs. 62.39%). These findings indicate that, at presentation, machine learning classification of bvFTD and AD is mostly based on cognitive and not imaging features. This clearly highlights the urgent need to develop better biomarkers for both diseases, but also emphasizes the value of machine learning in determining the predictive diagnostic features in neurodegeneration

Does empirically derived classification of individuals with subjective cognitive complaints predict dementia?

Background: Early identification of mild cognitive impairment (MCI) in people reporting subjective cognitive complaints (SCC) and the study of progression of cognitive decline are important issues in dementia research. This paper examines whether empirically derived procedures predict progression from MCI to dementia. (2) Methods: At baseline, 192 participants with SCC were diagnosed according to clinical criteria as cognitively unimpaired (70), single-domain amnestic MCI (65), multiple-domain amnestic MCI (33) and multiple-domain non-amnestic MCI (24). A two-stage hierarchical cluster analysis was performed for empirical classification. Categorical regression analysis was then used to assess the predictive value of the clusters obtained. Participants were re-assessed after 36 months. (3) Results: Participants were grouped into four empirically derived clusters: Cluster 1, similar to multiple-domain amnestic MCI; Cluster 2, characterized by subjective cognitive decline (SCD) but with low scores in language and working memory; Cluster 3, with specific deterioration in episodic memory, similar to single-domain amnestic MCI; and Cluster 4, with SCD but with scores above the mean in all domains. The majority of participants who progressed to dementia were included in Cluster 1. (4) Conclusions: Cluster analysis differentiated between MCI and SCD in a sample of people with SCC and empirical criteria were more closely associated with progression to dementia than standard criteria.This work was financially supported by the Spanish Directorate General of Scientific and Technical Research (Project PSI2014- 55316-C3-1-R) and by the Galician Government (Consellería de Cultura, Educación e Ordenación Universitaria; axudas para a consolidación e Estruturación de unidades de investigación competitivas do Sistema universitario de Galicia; GRC (GI-1807-USC); Ref: ED431-2017/27) through FEDER fundsS

Comprometimento cognitivo leve: rastreio cognitivo ou avaliação neuropsicológica?

OBJECTIVE: To describe the neuropsychological profile of mild cognitive impairment subtypes (amnestic, non-amnestic and multiple-domain) of a clinical sample. We further address the diagnostic properties of the Mini-Mental State Examination and the Cambridge Cognitive Examination for the identification of the different mild cognitive impairment subtypes in clinical practice. METHOD: Cross-sectional clinical and neuropsychological evaluation of 249 elderly patients attending a memory clinic at a university hospital in Sao Paulo, Brazil. RESULTS: The performance of patients with mild cognitive impairment was heterogeneous across the different subtests of the neuropsychological battery, with a trend towards an overall worse performance for amnestic (particularly multiple domain) mild cognitive impairment as compared to non-amnestic subtypes. Screening tests for dementia (Mini-Mental State Examination and Cambridge Cognitive Examination) adequately discriminated cases of mild Alzheimer's disease from controls, but they were not accurate to discriminate patients with mild cognitive impairment (all subtypes) from control subjects. CONCLUSIONS: The discrimination of mild cognitive impairment subtypes was possible only with the aid of a comprehensive neuropsychological assessment. It is necessary to develop new strategies for mild cognitive impairment screening in clinical practice.OBJETIVO: Descrever o perfil neuropsicológico dos subtipos de comprometimento cognitivo leve, amnéstico, não-amnéstico e múltiplos domínios, de uma amostra clínica. Além disto, avaliou-se as propriedades diagnósticas do Mini-exame do Estado Mental e do Cambridge Cognitive Examination na identificação dos diferentes subtipos de comprometimento cognitivo leve na prática clínica. MÉTODO: Avaliação clínica e neuropsicológica transversal de 249 idosos em uma clínica de memória de um hospital universitário em São Paulo, Brasil. RESULTADOS: Testes de rastreio para demência (Mini-exame do Estado Mental e Cambridge Cognitive Examination) identificam corretamente casos de doença de Alzheimer leve, mas não apresentam boa acurácia para diferenciar os diversos subtipos de comprometimento cognitivo leve. A performance dos sujeitos portadores de comprometimento cognitivo leve foi heterogênea nos diferentes testes da bateria neuropsicológica, com uma tendência a uma pior performance global nos pacientes com o subtipo amnéstico (especialmente os com envolvimento de múltiplos domínios cognitivos) em relação ao comprometimento cognitivo leve não-amnéstico. CONCLUSÕES: A discriminação dos diferentes subtipos de comprometimento cognitivo leve foi possível somente a partir de uma avaliação neuropsicológica detalhada. Desta maneira, é necessário o desenvolvimento de novas estratégias de rastreio para esta condição na prática clínica

An examination of working memory in subtle and mild cognitive impairment

Mild cognitive impairment (MCI) is abnormal cognitive decline that may be indicative of an insidious process such as dementia. Individuals with MCI are largely independent in their daily functioning but are at risk of further decline. To more deeply understand the working memory deficits associated with age-related cognitive decline, Lamar and colleagues developed a working memory task with no discontinuation rule: the Backwards Digit Task (BDT). Prior BDT research has demonstrated that individuals with mild cognitive impairment have lower overall scores on this task, and that different subtypes of MCI are more prone to certain errors. Research has not been done to examine if individuals with different MCI subtypes perform differently on individual trials. This current study examined the variability in any- and serial-order sequencing difficulty in the 5-span BDT trials across different levels of cognitive impairment (i.e., cognitively normal, subtle cognitive impairment, amnestic MCI, and mixed/dysexecutive MCI). Results indicated that the mixed/dysexecutive MCI group had significantly lower serial-order sequencing difficulty on all trials and lower any-order sequencing difficulty on trials 15 and 17. A positive effect of education was seen on trials 15, 20, and 21 when utilizing serial-order sequencing difficulty. Furthermore, more capture and transposition errors were made in the mixed/dysexecutive MCI group. These results highlight the diagnostic utility of process approach data collection in differentiating MCI subtypes. Additional implications for future clinical practice and research are discussed