The Role of Affect and Cognition in Processing Messages about Early Diagnosis for Alzheimer’s Disease by Older People

Background: Social interaction is a lifestyle factor associated with a decreased risk of dementia in several studies. However, specific aspects of these social factors influencing dementia are unknown. This study aimed at evaluating the role of the distinct aspects of social support on the incidence of dementia in a community-based cohort of older people in Brazil. Methods: A total of 345 healthy and independent elderly subjects living in the community were followed by 12 years. Incident cases of dementia and probable Alzheimer's disease were defined by DSM-IV criteria and NINCDS-ADRDA criteria, respectively. Social variables evaluated were marital status, living arrangement, living children, living sibling, confidant and attending recreational groups. Sex, age, education, Mini-Mental State Examination (MMSE) score, depressive symptoms and family income were entered as co-variates in a Cox proportional hazard model. Results: The absence of confidant was the only social variable associated to higher risk of developing dementia (HR = 5.31; p < 0.001), even after adjustment for age (HR = 1.08; p = 0.048) and baseline MMSE score (HR = 0.79; p = 0.002). Conclusions: Our data suggest that to have a confidant could be an important lifestyle factor associated with dementia.

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Role of Myo-Inositol by Magnetic Resonance Spectroscopy in Early Diagnosis of Alzheimer’s Disease in APP/PS1 Transgenic Mice

Dementia and Geriatric Cognitive Disorders ◽

10.1159/000261646 ◽

2009 ◽

Vol 28 (6) ◽

pp. 558-566 ◽

Cited By ~ 43

Author(s):

Shuang-Qing Chen ◽

Pei-Jun Wang ◽

Gao-Jun Ten ◽

Wei Zhan ◽

Ming-Hua Li ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Magnetic Resonance ◽

Early Diagnosis ◽

Magnetic Resonance Spectroscopy ◽

Transgenic Mice ◽

Resonance Spectroscopy

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Human Development in the Context of Aging and Chronic Illness: The Role of Attachment in Alzheimer's Disease and Stroke

The International Journal of Aging and Human Development ◽

10.2190/wk4b-pgeh-84qp-jup7 ◽

1995 ◽

Vol 41 (2) ◽

pp. 133-150 ◽

Cited By ~ 24

Author(s):

Lore K. Wright ◽

Joanne V. Hickey ◽

Kathleen C. Buckwalter ◽

Elizabeth C. Clipp

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Chronic Illness ◽

Older People ◽

Human Development ◽

Family Members ◽

Attachment Behavior ◽

Course Of Illness

Does chronic illness in older people provide potentials for human development? To date, this question has not been adequately addressed by dynamic theorists of human development. In this article, two illness trajectories, Alzheimer's disease and stroke, are examined to illustrate emerging changes in human development over each course of illness and the increasing importance of attachment behavior among ill elders and their family members. It is argued that the phenomenon of attachment links ailing older people to their environment, and that attachment is vital if human development is to continue.

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Role of the oral microbiota in the development of Alzheimer’s disease

Vestnik of Saint Petersburg University Medicine ◽

10.21638/spbu11.2020.401 ◽

2020 ◽

Vol 15 (4) ◽

pp. 231-238

Author(s):

Natalia Gavrilova ◽

◽

Nikita Gladyshev ◽

Anna Kotrova ◽

Anastasiia Morozova ◽

...

Keyword(s):

Risk Factors ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Early Diagnosis ◽

Oral Microbiota ◽

Practical Application ◽

Pathophysiological Role ◽

The World ◽

Important Practical Application

Dementia and, in particular, Alzheimer’s disease (AD), affects millions of people around the world and its prevalence is steadily rising annually. Some risk factors for AD, such as age, cannot be modified, while others could possibly be corrected. In recent years, many studies are tackling the problem of the oral and gut microbiota as a provoking factor for AD and other neurodegenerative diseases, but their relationship and specific pathophysiological mechanisms remain understudied. The microbiota of the oral cavity can be of particular importance due to the specificity of microorganisms and their localization, as well as the possibility of provoking neuroinflammation, which requires further study. This review covers the specific features of the oral microbiota, current views on the pathophysiological role of the oral microbiota in the development of AD, as well as the beneficial role of probiotics. The study of this issue can have an important practical application both for the early diagnosis of AD, and for its further treatment.

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Early diagnosis of Alzheimer’s disease: the role of biomarkers including advanced EEG signal analysis. Report from the IFCN-sponsored panel of experts

Clinical Neurophysiology ◽

10.1016/j.clinph.2020.03.003 ◽

2020 ◽

Vol 131 (6) ◽

pp. 1287-1310 ◽

Cited By ~ 13

Author(s):

P.M. Rossini ◽

R. Di Iorio ◽

F. Vecchio ◽

M. Anfossi ◽

C. Babiloni ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Early Diagnosis ◽

Signal Analysis ◽

Eeg Signal ◽

Eeg Signal Analysis

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An insight into the role of Artificial Intelligence in the early diagnosis of Alzheimer’s disease

CNS & Neurological Disorders - Drug Targets ◽

10.2174/1871527320666210512014505 ◽

2021 ◽

Vol 20 ◽

Author(s):

Rohit Kumar Verma ◽

Manisha Pandey ◽

Pooja Chawla ◽

Hira Choudhury ◽

Jayashree Mayuren ◽

...

Keyword(s):

Artificial Intelligence ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Early Diagnosis ◽

Symptomatic Relief ◽

Large Data ◽

Successful Implementation ◽

Clinical Implementation ◽

Insight Into

Background: The complication of Alzheimer’s disease (AD) has made the development of its therapeutic a challenging task. Even after decades of research, we have achieved no more than a few years of symptomatic relief. The inability to diagnose the disease early is the foremost hurdle behind its treatment. Several studies have aimed to identify potential biomarkers that can be detected in body fluids (CSF, blood, urine, etc) or assessed by neuroimaging (i.e., PET and MRI). However, the clinical implementation of these biomarkers is incomplete as they cannot be validated. Method: To overcome the limitation, the use of artificial intelligence along with technical tools has been extensively investigated for AD diagnosis. For developing a promising artificial intelligence strategy that can diagnose AD early, it is critical to supervise neuropsychological outcomes and imaging-based readouts with a proper clinical review. Conclusion: Profound knowledge, a large data pool, and detailed investigations are required for the successful implementation of this tool. This review will enlighten various aspects of early diagnosis of AD using artificial intelligence.

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