scholarly journals Environmental interventions to support orientation and social engagement of people with Alzheimer’s disease

2021 ◽  
Vol 15 (4) ◽  
pp. 510-523
Author(s):  
Maria Carolina Dias de Azevedo ◽  
Helenice Charchat-Fichman ◽  
Vera Maria Marsicano Damazio

ABSTRACT The built environment can be a home to compensatory strategies aimed at increasing the independence of elderly people with Alzheimer’s disease, by mitigating the cognitive impairment caused by it. Objective: The aim of this study was to find out which interventions were performed in indoor environments and observe their impacts on the relief of behavioral symptoms related to the disorientation of elderly people with probable Alzheimer’s disease. Methods: A systematic review was carried out using the preferred reporting items for systematic review and meta-analyses criteria in the MEDLINE/PubMed database. Two researchers carried out the selection of the studies, following the same methodology. The third author contributed during the writing process and in the decision-making. Results: Of note, 375 studies were identified and 20 studies were included in this systematic review. The identified interventions were classified into environmental communications and environmental characteristics. Conclusions: Environmental communications had positive results in guiding and reducing agitation. In contrast, while reducing behavioral symptoms related to orientation, environmental characteristics showed improvements mainly in social engagement and functional capacity.

2021 ◽  
Vol 79 (5) ◽  
pp. 447-456
Author(s):  
Dayanne Christine Borges Mendonça ◽  
Denise Rodrigues Fernandes ◽  
Salma Soleman Hernandez ◽  
Fernando Diákson Gontijo Soares ◽  
Karina de Figueiredo ◽  
...  

ABSTRACT Background: Neuropsychiatric symptoms are disorders frequently seen in Alzheimer's disease. These symptoms contribute to reduction of brain reserve capacity and, in addition, they present unfavorable implications, such as: poor prognosis for the disease, increased functional decline, increased burden on the caregiver and institutionalization. This scenario makes neuropsychiatric symptoms one of the biggest problems in Alzheimer's disease, and gives rise to a need for treatments focused on improving these symptoms. Sow progress in drug trials has led to interest in exploring non-pharmacological measures for improving the neuropsychiatric symptoms of Alzheimer's disease, such as physical exercise. Objective: To ascertain the effect of exercise on the neuropsychiatric symptoms of Alzheimer's disease and its implications. Methods: This was a systematic review of effective longitudinal research, conducted by searching for articles in the PubMed, Web of Science, CINAHL and Scopus electronic databases, from 2009 to 2019. Studies in which the sample consisted of elderly people aged 65 years old or over with a diagnosis of Alzheimer's disease were included. Initially 334 articles were identified. After exclusions, 21 articles remained to be read in full. From these, five articles fitted the eligibility criteria, and a further two articles were added through manual searches in the references of the articles found. Results: Out of the seven articles analyzed in this review, five studies revealed that physical exercise had a positive effect on the neuropsychiatric symptoms of Alzheimer's disease. Conclusion: This systematic review indicated that physical exercise is a favorable non-pharmacological means for attenuating the neuropsychiatric symptoms of elderly people with Alzheimer's disease, with special attention to aerobic exercises.


Life ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 750
Author(s):  
Manuel Glauco Carbone ◽  
Giovanni Pagni ◽  
Claudia Tagliarini ◽  
Donatella Marazziti ◽  
Nunzio Pomara

The processing of the amyloid precursor protein (APP) is a critical event in the formation of amyloid plaques. Platelets contain most of the enzymatic machinery required for APP processing and correlates of intracerebral abnormalities have been demonstrated in platelets of patients with AD. The goal of the present paper was to analyze studies exploring platelet APP metabolism in Alzheimer’s disease patients trying to assess potential reliable peripheral biomarkers, to offer new therapeutic solutions and to understand the pathophysiology of the AD. According to the PRISMA guidelines, we performed a systematic review through the PubMed database up to June 2020 with the search terms: “((((((APP) OR Amyloid Precursor Protein) OR AbetaPP) OR Beta Amyloid) OR Amyloid Beta) OR APP-processing) AND platelet”. Thirty-two studies were included in this systematic review. The papers included are analytic observational studies, namely twenty-nine cross sectional studies and three longitudinal studies, specifically prospective cohort study. The studies converge in an almost unitary way in affirming that subjects with AD show changes in APP processing compared to healthy age-matched controls. However, the problem of the specificity and sensitivity of these biomarkers is still at issue and would deserve to be deepened in future studies.


2021 ◽  
Author(s):  
R. Ossenkoppele ◽  
E.H. Singleton ◽  
C. Groot ◽  
Anke A. Dijkstra ◽  
Willem S. Eikelboom ◽  
...  

ABSTRACTImportanceThe behavioral variant of Alzheimer’s disease (bvAD) is characterized by early and predominant behavioral deficits caused by AD pathology. This AD phenotype is insufficiently understood and lacks standardized clinical criteria, limiting reliability and reproducibility of diagnosis and scientific reporting.ObjectiveTo perform a systematic review and meta-analysis of the bvAD literature, and use the outcomes to propose provisional research criteria for this syndrome.Data sourcesA systematic literature search in PubMed/Medline and Web-of-Science databases (from inception through April 7th, 2021, performed in duplicate) led to the assessment of 83 studies, including 13 suitable for meta-analysis.Study selectionStudies reporting on behavioral, neuropsychological or neuroimaging features in bvAD, and, when available, providing comparisons with “typical” amnestic-predominant AD (tAD) or behavorial variant frontotemporal dementia (bvFTD).Data extraction and synthesisWe performed random-effects meta-analyses on group-level study results of clinical data, and systematically reviewed the neuroimaging literature.Main outcome and measuresBehavioral symptoms (neuropsychiatric symptoms and bvFTD core clinical criteria), cognitive function (global cognition, episodic memory and executive functioning) and neuroimaging features (structural MRI, [18F]FDG-PET, perfusion SPECT, amyloid-PET and tau-PET).ResultsData were collected for 591 patients with bvAD. There was moderate-to-substantial heterogeneity and moderate risk of bias across studies. bvAD showed more severe behavioral symptoms compared to tAD (standardized mean difference [SMD, 95% confidence interval]: 1.16[0.74–1.59], p<0.001), and a trend towards less severe behavioral symptoms compared to bvFTD (SMD:-0.22[-0.47–0.04], p=0.10). Meta-analyses of cognitive data indicated worse executive performance in bvAD versus tAD (SMD:-1.03[-1.74–-0.32], p<0.01), but not compared to bvFTD (SMD:-0.61[-1.75–0.53], p=0.29). bvAD showed a trend towards worse memory performance compared to bvFTD (SMD:-1.31[-2.75–0.14], p=0.08), but did not differ from tAD (SMD:0.43[-0.46–1.33], p=0.34). The neuroimaging literature revealed two distinct bvAD neuroimaging-phenotypes: an “AD-like” posterior-predominant pattern and a “bvFTD-like” anterior-predominant pattern, with the former being more prevalent.Conclusions and relevanceOur data indicate that bvAD is clinically most similar to bvFTD, while it shares most pathophysiological features with tAD. Based on these insights, we propose provisional research criteria for bvAD aimed at improving the consistency and reliability of future research and aiding the clinical assessment of this AD phenotype.KEY POINTSQuestionHow does the behavioral variant of Alzheimer’s disease (bvAD) relate to typical AD (tAD) and to behavioral variant frontotemporal dementia (bvFTD) in terms of clinical presentation and neuroimaging signatures?FindingsIn this systematic review and meta-analysis, we found that, at time of diagnosis, bvAD showed more severe neuropsychiatric symptoms and other behavioral deficits compared to tAD. Two distinct neuroimaging phenotypes were observed across reported bvAD cases: an “AD-like” posterior-predominant pattern and a “bvFTD-like” anterior-predominant pattern, with the posterior-predominant neuroimaging phenotype being the most prevalent across reported bvAD cases.MeaningbvAD is clinically most reminiscent of bvFTD, while it shares most pathophysiological features with tAD. The provisional research criteria are aimed at improving the consistency and reliability of future research, and potentially aid in the clinical assessment of bvAD.


Author(s):  
Roja Rahimi ◽  
Shekoufeh Nikfar ◽  
Masoud Sadeghi ◽  
Mohammad Abdollahi ◽  
Reza Heidary Moghaddam ◽  
...  

Background: It has been found that there is a link between hypertension and elevated risk of Alzheimer’s disease (AD). Herein, a meta-analysis based on randomized clinical trials (RCTs) was used to assess the effect of antihypertensive drugs on cognition and behavioral symptoms of AD patients. Method: The three databases – PubMed/Medline, Scopus, and Cochrane Library- were searched up to March 2020. The quality of the studies included in the meta-analysis was evaluated by the Jadad score. Clinical Global Impression of Change (CGIC) included in two studies, Mini-Mental State Examination (MMSE) included in three studies, and Neuropsychiatric Inventory (NPI) in three studies were the main outcomes in this systematic review. Results: Out of 1506 studies retrieved in the databases, 5 RCTs included and analyzed in the meta-analysis. The pooled mean differences of CGIC, MMSE, and NPI in patients with AD receiving antihypertensive drugs compared to placebo was -1.76 with (95% CI = -2.66 to -0.86; P=0.0001), 0.74 (95% CI = 0.20 to 1.28; P= 0.007), and -9.49 (95% CI = -19.76 to 0.79; P = 0.07), respectively. Conclusion: The findings of the present meta-analysis show that antihypertensive drugs may improve cognition and behavioral symptoms of patients with AD. However, more well-designed RCTs with similar drugs are needed to achieve more conclusive results.


2019 ◽  
Author(s):  
Clemens Kruse ◽  
Britney Larson ◽  
Reagan Wilkinson ◽  
Roger Samson ◽  
Taylor Castillo

BACKGROUND Incidence of AD continues to increase, making it the most common cause of dementia and the sixth-leading cause of death in the United States. 2018 numbers are expected to double by 2030. OBJECTIVE We examined the benefits of utilizing technology to identify and detect Alzheimer’s disease in the diagnostic process. METHODS We searched PubMed and CINAHL using key terms and filters to identify 30 articles for review. We analyzed these articles and reported them in accordance with the PRISMA guidelines. RESULTS We identified 11 technologies used in the detection of Alzheimer’s disease: 66% of which used some form of MIR. Functional, structural, and 7T magnetic resonance imaging were all used with structural being the most prevalent. CONCLUSIONS MRI is the best form of current technology being used in the detection of Alzheimer’s disease. MRI is a noninvasive approach that provides highly accurate results in the diagnostic process of Alzheimer’s disease.


Processes ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1071
Author(s):  
Lucia Billeci ◽  
Asia Badolato ◽  
Lorenzo Bachi ◽  
Alessandro Tonacci

Alzheimer’s disease is notoriously the most common cause of dementia in the elderly, affecting an increasing number of people. Although widespread, its causes and progression modalities are complex and still not fully understood. Through neuroimaging techniques, such as diffusion Magnetic Resonance (MR), more sophisticated and specific studies of the disease can be performed, offering a valuable tool for both its diagnosis and early detection. However, processing large quantities of medical images is not an easy task, and researchers have turned their attention towards machine learning, a set of computer algorithms that automatically adapt their output towards the intended goal. In this paper, a systematic review of recent machine learning applications on diffusion tensor imaging studies of Alzheimer’s disease is presented, highlighting the fundamental aspects of each work and reporting their performance score. A few examined studies also include mild cognitive impairment in the classification problem, while others combine diffusion data with other sources, like structural magnetic resonance imaging (MRI) (multimodal analysis). The findings of the retrieved works suggest a promising role for machine learning in evaluating effective classification features, like fractional anisotropy, and in possibly performing on different image modalities with higher accuracy.


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