scholarly journals Systematic Review on Resting-State EEG for Alzheimer’s Disease Diagnosis and Progression Assessment

2018 ◽  
Vol 2018 ◽  
pp. 1-26 ◽  
Author(s):  
Raymundo Cassani ◽  
Mar Estarellas ◽  
Rodrigo San-Martin ◽  
Francisco J. Fraga ◽  
Tiago H. Falk
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Resting State ◽  
Neurodegenerative Disorder ◽  
Disease Diagnosis ◽  
Bibliographic Databases ◽  
Journal Articles

Alzheimer’s disease (AD) is a neurodegenerative disorder that accounts for nearly 70% of the more than 46 million dementia cases estimated worldwide. Although there is no cure for AD, early diagnosis and an accurate characterization of the disease progression can improve the quality of life of AD patients and their caregivers. Currently, AD diagnosis is carried out using standardized mental status examinations, which are commonly assisted by expensive neuroimaging scans and invasive laboratory tests, thus rendering the diagnosis time consuming and costly. Notwithstanding, over the last decade, electroencephalography (EEG) has emerged as a noninvasive alternative technique for the study of AD, competing with more expensive neuroimaging tools, such as MRI and PET. This paper reports on the results of a systematic review on the utilization of resting-state EEG signals for AD diagnosis and progression assessment. Recent journal articles obtained from four major bibliographic databases were analyzed. A total of 112 journal articles published from January 2010 to February 2018 were meticulously reviewed, and relevant aspects of these papers were compared across articles to provide a general overview of the research on this noninvasive AD diagnosis technique. Finally, recommendations for future studies with resting-state EEG were presented to improve and facilitate the knowledge transfer among research groups.

scholarly journals A comparison of resting state EEG and structural MRI for classifying Alzheimer’s disease and mild cognitive impairment

2019 ◽  
Author(s):  
FR Farina ◽  
DD Emek-Savaş ◽  
L Rueda-Delgado ◽  
R Boyle ◽  
H Kiiski ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Resting State ◽  
Healthy Aging ◽  
Neurodegenerative Disorder ◽  
Low Cost ◽  
Structural Mri ◽  
Lower Accuracy

AbstractAlzheimer’s disease (AD) is a neurodegenerative disorder characterised by severe cognitive decline and loss of autonomy. AD is the leading cause of dementia. AD is preceded by mild cognitive impairment (MCI). By 2050, 68% of new dementia cases will occur in low- and middle-income countries. In the absence of objective biomarkers, psychological assessments are typically used to diagnose MCI and AD. However, these require specialist training and rely on subjective judgements. The need for low-cost, accessible and objective tools to aid AD and MCI diagnosis is therefore crucial. Electroencephalography (EEG) has potential as one such tool: it is relatively inexpensive (cf. magnetic resonance imaging; MRI) and is portable. In this study, we collected resting state EEG, structural MRI and rich neuropsychological data from older adults (55+ years) with AD, with MCI and from healthy controls (n~60 per group). Our goal was to evaluate the utility of EEG, relative to MRI, for the classification of MCI and AD. We also assessed the performance of combined EEG and behavioural (Mini-Mental State Examination; MMSE) and structural MRI classification models. Resting state EEG classified AD and HC participants with moderate accuracy (AROC=0.76), with lower accuracy when distinguishing MCI from HC participants (AROC=0.67). The addition of EEG data to MMSE scores had no additional value compared to MMSE alone. Structural MRI out-performed EEG (AD vs HC, AD vs MCI: AROCs=1.00; HC vs MCI: AROC=0.73). Resting state EEG does not appear to be a suitable tool for classifying AD. However, EEG classification accuracy was comparable to structural MRI when distinguishing MCI from healthy aging, although neither were sufficiently accurate to have clinical utility. This is the first direct comparison of EEG and MRI as classification tools in AD and MCI participants.

scholarly journals Assessment of Health-Related Quality of Life for Caregivers of Alzheimer’s Disease Patients

2016 ◽  
Vol 2016 ◽  
pp. 1-7 ◽  
Author(s):  
Maria I. Andreakou ◽  
Angelos A. Papadopoulos ◽  
Demosthenes B. Panagiotakos ◽  
Dimitris Niakas
Keyword(s):  
Quality Of Life ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Negative Correlation ◽  
Depressive Symptomatology ◽  
Neurodegenerative Disorder ◽  
Health Related Quality ◽  
Related Quality ◽  
Health Related

Background.Alzheimer’s disease (AD) dementia is a chronic neurodegenerative disorder that results in total cognitive impairment and functional decline. Family members are the most usual caregivers worldwide, resulting in a subsequent degradation of their quality of life.Methods.During November 2013–March 2014 in Athens, Greece, 155 AD patients’ family caregivers’ Health-Related Quality of Life and existence of depressive symptomatology were assessed.Results.A strong negative correlation between the dimensions of HRQoL and the scores of the depression scale was revealed. AD patients’ caregivers have a lower HRQoL almost in all dimensions compared to the Greek urban general population. The caregivers’ social role, the existence of emotional problems, and their mental health status led to this result. Furthermore significantly important differences in caregivers’ total HRQoL and depressive symptomatology were indicated in relation to their gender, hypertension existence, patient care frequency, cohabitation with the patient, disease aggravation, and economic status.Conclusions.Caring for relatives with AD strongly correlates with negative caregivers’ HRQoL scores and adversely affects their depressive symptomatology. This negative correlation is enhanced in the later stages of the disease, in greater frequency of care, through living with a patient, in poor financial status, and with the existence of a chronic illness.

Dance for People with Alzheimer’s Disease: A Systematic Review

2019 ◽  
Vol 16 (10) ◽  
pp. 919-933 ◽  
Author(s):  
Alicia Ruiz-Muelle ◽  
María Mar López-Rodríguez
Keyword(s):  
Quality Of Life ◽  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Clinical Trials ◽  
Cognitive Function ◽  
Dance Therapy ◽  
Randomized Clinical Trials ◽  
Future Research

Background: In recent years, several reviews have addressed the effectiveness of dance therapy in dementia, healthy older adults, or the elderly in general. However, reviews regarding the effect of this therapy exclusively on patients diagnosed with Alzheimer’s disease have not been found. Objective: The purpose of this study is to review the available literature describing clinical trials which explore the effects of dancing on psychological and physical outcomes, functionality, cognitive function, and quality of life in patients diagnosed with Alzheimer’s disease. In addition, this review aims to assess the quality of studies that perform dance therapy interventions in these patients. Methods: This study is a systematic review of randomized and non-randomized clinical trials regarding the effect of intervention including a dancing activity in people diagnosed with Alzheimer's disease. Results: In total, the evidence for this review rests on 12 studies with a total of 349 participants. The findings of this mini-review confirm the positive effect of dance therapy on physical and cognitive function, functionality, psychological outcomes, and quality of life in people with Alzheimer's disease. Conclusion: Most of the studies implementing dance as part of the therapeutic treatment has shown to improve or slow the worsening in the quality of life of patients with Alzheimer's disease and their caregivers. Future research focused on these patients should use a more exhaustive methodology and make a more detailed description of these kind of interventions.

scholarly journals Resting‐state network dysfunction in Alzheimer's disease: A systematic review and meta‐analysis

2017 ◽  
Vol 8 (1) ◽  
pp. 73-85 ◽  
Author(s):  
AmanPreet Badhwar ◽  
Angela Tam ◽  
Christian Dansereau ◽  
Pierre Orban ◽  
Felix Hoffstaedter ◽  
...  
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Resting State ◽  
Meta Analysis ◽  
Resting State Network

scholarly journals Analysis the Link between Periodontal Diseases and Alzheimer’s Disease: A Systematic Review

2021 ◽  
Vol 18 (17) ◽  
pp. 9312
Author(s):  
Leslie Borsa ◽  
Margaux Dubois ◽  
Guillaume Sacco ◽  
Laurence Lupi
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Periodontal Disease ◽  
Periodontal Diseases ◽  
Fold Increase ◽  
Assessment Tools ◽  
Cochrane Library ◽  
The Cochrane Library

The hypothesis of an infectious connection from the oro-pharyngeal sphere to the brain underlines the interest in analyzing the link between periodontal disease and Alzheimer’s disease. The aim of this systematic review was to examine the link between Alzheimer’s disease and periodontal disease in patients aged 65 and over. Databases (PubMed (MEDLINE), the Cochrane Library, and Embase) were analyzed for relevant references up to 21 June 2021. The authors independently selected the studies and extracted the data. The quality of included studies was checked using the National Institutes of Health’s quality assessment tools. Five studies were included. The selected studies described in their results an increase in F. nucleatum in Alzheimer’s disease patients (adjusted p = 0.02), and its incidence was linked to C. rectus and P. gingivalis (adjusted HR = 1.22 (1.04–1.43), p = 0.012) as well as A. naeslundii (crude HR = 2.0 (1.1–3.8)). The presence of periodontitis at baseline was associated with a six-fold increase in the rate of cognitive decline over a 6-month follow-up period (ADAS-Cog mean change = 2.9 ± 6.6). The current review suggests an association between periodontal disease and Alzheimer’s disease. The treatment of periodontal disease could be a way to explore Alzheimer’s disease prevention.

scholarly journals The Potential Benefits of Nanotechnology in Treating Alzheimer’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Tan Sook Ling ◽  
Shanthini Chandrasegaran ◽  
Low Zhi Xuan ◽  
Tong Li Suan ◽  
Elaine Elaine ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neurodegenerative Disorder ◽  
Amyloid Plaques ◽  
Disease Diagnosis ◽  
Drug Bioavailability ◽  
Potential Toxicity ◽  
Alternative Approach ◽  
Potential Benefits ◽  
The Brain

Alzheimer’s disease is a neurodegenerative disorder that is caused by the accumulation of beta-amyloid plaques in the brain. Currently, there is no definitive cure available to treat Alzheimer’s disease. The available medication in the market has the ability to only slow down its progression. However, nanotechnology has shown its superiority that can be applied for medical usage and it has a great potential in the therapy of Alzheimer’s disease, specifically in the disease diagnosis and providing an alternative approach to treat Alzheimer’s disease. This is done by increasing the efficiency of drug delivery by penetrating and overcoming the blood-brain barrier. Having said that, there are limitations that need to be further investigated and researched in order to minimize the adverse effects and potential toxicity and to improve drug bioavailability. The recent advances in the treatment of Alzheimer’s disease using nanotechnology include the regeneration of stem cells, nanomedicine, and neuroprotection. In this review, we will discuss the advancement of nanotechnology which helps in the diagnosis and treatment of neurodegenerative disorders such as Alzheimer’s disease as well as its challenges.

scholarly journals Resting-State Co-activation Patterns as Promising Candidates for Prediction of Alzheimer’s Disease in Aged Mice

2021 ◽  
Vol 14 ◽  
Author(s):  
Mohit H. Adhikari ◽  
Michaël E. Belloy ◽  
Annemie Van der Linden ◽  
Georgios A. Keliris ◽  
Marleen Verhoye
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Resting State ◽  
Neurodegenerative Disorder ◽  
Amyloid Β ◽  
Occurrence Rate ◽  
Seed Region ◽  
Periodic Patterns ◽  
Activation Patterns ◽  
Co Activation

Alzheimer’s disease (AD), a neurodegenerative disorder marked by accumulation of extracellular amyloid-β (Aβ) plaques leads to progressive loss of memory and cognitive function. Resting-state fMRI (RS-fMRI) studies have provided links between these two observations in terms of disruption of default mode and task-positive resting-state networks (RSNs). Important insights underlying these disruptions were recently obtained by investigating dynamic fluctuations in RS-fMRI signals in old TG2576 mice (a mouse model of amyloidosis) using a set of quasi-periodic patterns (QPP). QPPs represent repeating spatiotemporal patterns of neural activity of predefined temporal length. In this article, we used an alternative methodology of co-activation patterns (CAPs) that represent instantaneous and transient brain configurations that are likely contributors to the emergence of commonly observed RSNs and QPPs. We followed a recently published approach for obtaining CAPs that divided all time frames, instead of those corresponding to supra-threshold activations of a seed region as done traditionally, to extract CAPs from RS-fMRI recordings in 10 TG2576 female mice and eight wild type littermates at 18 months of age. Subsequently, we matched the CAPs from the two groups using the Hungarian method and compared the temporal (duration, occurrence rate) and the spatial (lateralization of significantly co-activated and co-deactivated voxels) properties of matched CAPs. We found robust differences in the spatial components of matched CAPs. Finally, we used supervised learning to train a classifier using either the temporal or the spatial component of CAPs to distinguish the transgenic mice from the WT. We found that while duration and occurrence rates of all CAPs performed the classification with significantly higher accuracy than the chance-level, blood oxygen level-dependent (BOLD) signals of significantly activated voxels from individual CAPs turned out to be a significantly better predictive feature demonstrating a near-perfect classification accuracy. Our results demonstrate resting-state co-activation patterns are a promising candidate in the development of a diagnostic, and potentially, prognostic RS-fMRI biomarker of AD.

scholarly journals Relations between subjective well-being and Alzheimer’s disease: A systematic review

2020 ◽  
Vol 14 (2) ◽  
pp. 153-158 ◽  
Author(s):  
Fernanda Panage Moura ◽  
Amer Cavalheiro Hamdan
Keyword(s):  
Systematic Review ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Methodological Quality ◽  
Positive Emotions ◽  
Well Being ◽  
The Elderly ◽  
Quality Level ◽  
Subjective Well Being

ABSTRACT. Subjective Well-Being (SWB) is determined by the degree of satisfaction with one's own life and the intensity/frequency with which we experience negative and positive emotions. Current studies indicate that SWB is beneficial for health. Objective: The aim of this systematic review was to analyze the methodological quality of published articles on SWB in people with Alzheimer’s disease (AD). Methods: The keywords “Well-Being” and “Alzheimer” were used. Inclusion criteria were a) articles with a sample of the elderly population; b) empirical articles; c) articles published between 2014 and 2019. Analysis of the selected articles was performed using the Downs and Black Checklist. Results: 13 articles were selected for further analysis. The results showed that only one of the articles reached a high methodological quality level. The other articles had an average level, ranging from 46% to 67%, of total protocol compliance. Conclusion: The studies analyzed had a medium level of methodological quality. It is important to improve the methodological quality of studies on SWB in people with AD.

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