Mild cognitive impairment: focus on diagnosis

Higher-Level Executive Functions in Healthy Elderly and Mild Cognitive Impairment: A Systematic Review

Mild Cognitive Impairment (MCI) is a clinical syndrome characterized by a moderate decline in one or more cognitive functions with a preserved autonomy in daily life activities. MCI exhibits cognitive, behavioral, psychological symptoms. The executive functions (EFs) are key functions for everyday life and physical and mental health and allow for the behavior to adapt to external changes. Higher-level executive functions develop from basic EFs (inhibition, working memory, attentional control, and cognitive flexibility). They are planning, reasoning, problem solving, and fluid intelligence (Gf). This systematic review investigates the relationship between higher-level executive functions and healthy and pathological aging, assuming the role of executive functions deficits as a predictor of cognitive decline. The systematic review was conducted according to the PRISMA Statement. A total of 73 studies were identified. The results indicate that 65.8% of the studies confirm significant EFs alterations in MCI (56.8% planning, 50% reasoning, 100% problem solving, 71.4% fluid intelligence). These results seem to highlight a strong prevalence of higher-level executive functions deficits in MCI elderly than in healthy elderly.

A correlativity study of plasma APL1β28 and clusterin levels with MMSE/MoCA/CASI in aMCI patients

Amnestic mild cognitive impairment (aMCI) is a sub-clinical condition characterized by memory deficits that are not severe enough to affect daily functioning. Here we investigated two potential biomarkers found in the cerebrospinal fluid of AD patients, APLP1-derived Aβ-like peptides 28 (APL1β28) and clusterin plasma levels, in terms of their relationship to cognitive function, as reflected in the Mini-Mental State Examination (MMSE), the Montreal Cognitive Assessment (MoCA) and the Cognitive Assessment Screening Instrument (CASI) in aMCI patients. Forty-seven aMCI patients and thirty-five age- and gender-matched healthy adult controls were recruited for this study. Using the ELISA method, we found that the mean concentrations of both APL1β28 and clusterin were not significantly different between the control and aMCI groups. The APL1β28 levels were positively correlated with clusterin and that both were negatively correlated with the MMSE scores of the aMCI patients. Clusterin levels were negatively correlated with the MoCA and CASI scores of the aMCI patients. Using multivariate analysis, the correlation between clusterin and MMSE/MoCA/CASI was independent of other AD risk factors including age, education, sex, body mass index and ApoE genotype. The data presented here demonstrate that plasma clusterin levels reflect cognitive function in aMCI patients.

Enhancing prospective memory in mild cognitive impairment: The role of enactment

INTRODUCTION

Prospective memory (PM) is a fundamental requirement for independent living which might be prematurely compromised in the neurodegenerative process, namely in mild cognitive impairment (MCI), a typical prodromal Alzheimer's disease (AD) phase. Most encoding manipulations that typically enhance learning in healthy adults are of minimal benefit to AD patients. However, there is some indication that these can display a recall advantage when encoding is accompanied by the physical enactment of the material. The aim of this study was to explore the potential benefits of enactment at encoding and cue-action relatedness on memory for intentions in MCI patients and healthy controls using a behavioral PM experimental paradigm.

METHOD

We report findings examining the influence of enactment at encoding for PM performance in MCI patients and age- and education-matched controls using a laboratory-based PM task with a factorial independent design.

RESULTS

PM performance was consistently superior when physical enactment was used at encoding and when target-action pairs were strongly associated. Importantly, these beneficial effects were cumulative and observable across both a healthy and a cognitively impaired lifespan as well as evident in the perceived subjective difficulty in performing the task.

CONCLUSIONS

The identified beneficial effects of enacted encoding and semantic relatedness have unveiled the potential contribution of this encoding technique to optimize attentional demands through an adaptive allocation of strategic resources. We discuss our findings with respect to their potential impact on developing strategies to improve PM in AD sufferers.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

Background

Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test.

Results

Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5.

Conclusions

When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing.

Clinical presentation of prodromal frontotemporal dementia

BACKGROUND

Misrecognition of symptoms in the early stages of frontotemporal dementia (FTD) frequently contributes to diagnostic delay. Three frameworks have been proposed for the clinical identification of prodromal FTD: (1) cognitive profiling, (2) the presence of behavioral/psychiatric symptoms in the absence of memory complaints, and (3) a combined approach of cognitive, behavioral, and neuroimaging features.

OBJECTIVE

To evaluate current conceptual frameworks for the clinical recognition of prodromal FTD with current empirical evidence.

METHOD

We performed a comprehensive PsychINFO and MEDLINE database search to identify articles investigating the prodromal symptoms of FTD.

CONCLUSIONS

The 3 frameworks capture important aspects of the clinical picture of prodromal FTD but require further refinement. The prodromal stage of FTD is characterized by both cognitive and behavioral features. Diagnostic accuracy will likely be improved by considering a combination of cognitive and behavioral features, because some features overlap with prodromes for Alzheimer's disease and vascular dementia.

Verbal learning and memory deficits in Mild Cognitive Impairment

Criteria for amnestic MCI rely on the use of delayed recall tasks to establish the presence of memory impairment. This study applied the California Verbal Learning Test to detail memory performance in MCI patients (n=70), as compared to control subjects (n=92) and AD patients (n=21). Learning across the 5 trials was different among the 3 groups. Learning strategy was also different, the MCI group showing less semantic clustering than the control group. However, both MCI patients and controls could benefit from semantic cueing. This study showed that beyond consolidation deficits, MCI patients have marked difficulties in acquisition and recall strategies.

Mild cognitive impairment: deficits in cognitive domains other than memory

Patients with mild cognitive impairment (MCI) typically present with memory complaints, but may have mild deficits in other cognitive domains. We compared the neuropsychological profiles of a series of consecutive MCI patients (n = 116) with a control group of healthy elderly subjects (n = 63). The presence of a memory deficit on delayed recall was consistent in the MCI sample, as it was an inclusion criterion in the study. Impairment on immediate recall was present in 62.6% of the patients on paragraph recall of the logical memory test and in 63.1% of the patients on the word paired-associate learning test. Remarkably, patients with MCI frequently had deficits in cognitive domains beyond memory. As much as 68.7% of the patients had deficits in temporal orientation, 30.2% had deficits in semantic fluency, 33.7% in the Token test, 23.4% in calculation, and 23.9% in motor initiative. If detailed neuropsychological testing is performed, the majority of MCI patients will have deficits in cognitive domains other than memory.

Multiple cognitive deficits in amnestic mild cognitive impairment

OBJECTIVE

To determine if more widespread cognitive deficits are present in a narrowly defined group of patients with the amnestic form of mild cognitive impairment (MCI).

METHODS

From a larger sample of patients clinically diagnosed as meeting the criteria of Petersen et al. for amnestic MCI, we selected 22 subjects who had Clinical Dementia Rating scores of zero on all domains besides memory and orientation. These MCI subjects with presumably isolated memory impairments were compared to 35 age-matched normal controls and 33 very mild Alzheimer's disease (AD) patients on a battery of neuropsychological tests.

RESULT

In addition to the expected deficits in episodic memory, the amnestic MCI group performed less well than the controls but better than the AD group on design fluency, category fluency, a set shifting task and the Stroop interference condition. Over half the amnestic MCI group (vs. none of the normal controls) scored at least 1 standard deviation below control means on 4 or more of the nonmemory cognitive tasks.

CONCLUSIONS

Isolated memory impairment may be fairly uncommon in clinically diagnosed amnestic MCI patients, even when the criteria for amnestic MCI are fairly narrow. Additional cognitive impairments are likely to include fluency and executive functioning. These more diffuse deficits argue for comprehensive cognitive assessments, even when the patient and family are reporting only memory decline, and are consistent with the increase in attention paid to the heterogeneity of MCI.