Risk Factors for Rapid Cognitive Decline in Alzheimer’s Disease

2017 ◽  
Vol 7 (5) ◽  
pp. 770-776
Author(s):  
Myung Chul Kim ◽  
Eun Hye Jeong ◽  
Hyun Keun Lee ◽  
Young Kyu Park
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rapid Cognitive Decline

scholarly journals Differential effects of risk factors on the cognitive trajectory of early- and late-onset Alzheimer’s disease

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Jaeho Kim ◽  
Sook-Young Woo ◽  
Seonwoo Kim ◽  
Hyemin Jang ◽  
Junpyo Kim ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Function ◽  
Cognitive Decline ◽  
Late Onset ◽  
Low Education ◽  
Rapid Cognitive Decline ◽  
Function Language ◽  
The Impact

Abstract Background Although few studies have shown that risk factors for Alzheimer’s disease (AD) are associated with cognitive decline in AD, not much is known whether the impact of risk factors differs between early-onset AD (EOAD, symptom onset < 65 years of age) versus late-onset AD (LOAD). Therefore, we evaluated whether the impact of Alzheimer’s disease (AD) risk factors on cognitive trajectories differ in EOAD and LOAD. Methods We followed-up 193 EOAD and 476 LOAD patients without known autosomal dominant AD mutation for 32.3 ± 23.2 months. Mixed-effects model analyses were performed to evaluate the effects of APOE ε4, low education, hypertension, diabetes, dyslipidemia, and obesity on cognitive trajectories. Results APOE ε4 carriers showed slower cognitive decline in general cognitive function, language, and memory domains than APOE ε4 carriers in EOAD but not in LOAD. Although patients with low education showed slower cognitive decline than patients with high education in both EOAD and LOAD, the effect was stronger in EOAD, specifically in frontal-executive function. Patients with hypertension showed faster cognitive decline than did patients without hypertension in frontal-executive and general cognitive function in LOAD but not in EOAD. Patients with obesity showed slower decline in general cognitive function than non-obese patients in EOAD but not in LOAD. Conclusions Known risk factors for AD were associated with slower cognitive decline in EOAD but rapid cognitive decline in LOAD.

scholarly journals Role of nurses in addressing modifiable risk factors for early Alzheimer's disease and mild cognitive impairment

2020 ◽  
Vol 29 (8) ◽  
pp. 460-469 ◽  
Author(s):  
Kevin Hope
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Cognitive Decline ◽  
Health Professionals ◽  
Current Evidence ◽  
Modifiable Risk Factors ◽  
Early Alzheimer’S Disease

A multidisciplinary advisory group of health professionals involved in dementia care assessed the current evidence base regarding modifiable risk factors (MRFs) for early Alzheimer's disease and mild cognitive impairment. Based on evidence from the published literature and clinical experience, MRFs in four areas were identified where there is evidence to support interventions that may help delay cognitive decline or reduce the risk of developing Alzheimer's disease: medical (eg cardiovascular risk factors), psychosocial (eg depression, anxiety, social isolation), lifestyle (eg lack of physical activity, smoking) and nutrition (eg poor diet, lack of micronutrients). Practical guidance on how health professionals, but in particular nurses, may actively seek to address these MRFs in clinical practice was also developed. Nurses are at the forefront of patient care and, as such, are ideally placed to offer advice to patients that may proactively help mitigate the risks of cognitive decline and the development of Alzheimer's disease.

Consensus-based recommendations for the management of rapid cognitive decline due to Alzheimer's disease

2017 ◽  
Vol 13 (5) ◽  
pp. 592-597 ◽  
Author(s):  
Jianping Jia ◽  
Serge Gauthier ◽  
Sarah Pallotta ◽  
Yong Ji ◽  
Wenshi Wei ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rapid Cognitive Decline

scholarly journals Predictors of rapid cognitive decline in Alzheimer's disease: results from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of ageing

2011 ◽  
Vol 24 (2) ◽  
pp. 197-204 ◽  
Author(s):  
Alessandro Sona ◽  
Ping Zhang ◽  
David Ames ◽  
Ashley I. Bush ◽  
Nicola T. Lautenschlager ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rating Scale ◽  
Cognitive Status ◽  
Imaging Biomarkers ◽  
Clinical Dementia Rating ◽  
Factors Associated ◽  
Biological Variables ◽  
Rapid Cognitive Decline

ABSTRACTBackground: The AIBL study, which commenced in November 2006, is a two-center prospective study of a cohort of 1112 volunteers aged 60+. The cohort includes 211 patients meeting NINCDS-ADRDA criteria for Alzheimer's disease (AD) (180 probable and 31 possible). We aimed to identify factors associated with rapid cognitive decline over 18 months in this cohort of AD patients.Methods: We defined rapid cognitive decline as a drop of 6 points or more on the Mini-Mental State Examination (MMSE) between baseline and 18-month follow-up. Analyses were also conducted with a threshold of 4, 5, 7 and 8 points, as well as with and without subjects who had died or were too severely affected to be interviewed at 18 months and after, both including and excluding subjects whose AD diagnosis was “possible” AD. We sought correlations between rapid cognitive decline and demographic, clinical and biological variables.Results: Of the 211 AD patients recruited at baseline, we had available data for 156 (73.9%) patients at 18 months. Fifty-one patients were considered rapid cognitive decliners (32.7%). A higher Clinical Dementia Rating scale (CDR) and higher CDR “sum of boxes” score at baseline were the major predictors of rapid cognitive decline in this population. Furthermore, using logistic regression model analysis, patients treated with a cholinesterase inhibitor (CheI) had a higher risk of being rapid cognitive decliners, as did males and those of younger age.Conclusions: Almost one third of patients satisfying established research criteria for AD experienced rapid cognitive decline. Worse baseline functional and cognitive status and treatment with a CheI were the major factors associated with rapid cognitive decline over 18 months in this population.

scholarly journals Exploratory Data Analysis in a Six-Year Longitudinal Study in Healthy Brain Aging

2019 ◽  
Author(s):  
Jaime Gómez-Ramírez ◽  
Marina Ávila Villanueva ◽  
Belén Frades Payo ◽  
Teodoro del Ser Quijano ◽  
Meritxell Valentí Soler ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Data Analysis ◽  
Cognitive Decline ◽  
Exploratory Data Analysis ◽  
Brain Aging ◽  
Wide Range ◽  
Exploratory Data ◽  
Longitudinal Dataset

AbstractAlzheimer’s Disease (AD) is a complex, multifactorial and comorbid condition. The asymptomatic behavior in early stages of the disease is a paramount obstacle to formulate a preclinical and predictive model of AD. Not surprisingly, the AD drug approval rate is one of the lowest in the industry, an exiguous 0.4%. The identification of risk factors, preferably obtained by the subject herself, is sorely needed given that the incidence of Alzheimer’s disease grows exponentially with age [Ferri et al., 2005], [Ganguli and Rodriguez, 2011].During the last 7 years, researchers at Proyecto Vallecas have collected information about the project’s volunteers, aged 70 or more. The Proyecto Vallecas dataset includes information about a wide range of factors including magnetic resonance imaging, genetic, demographic, socioeconomic, cognitive performance, subjective memory complaints, neuropsychiatric disorders, cardiovascular, sleep, diet, physical exercise and self assessed quality of life. The subjects in each visit were diagnosed as healthy, mild cognitive impairment (MCI) or dementia.In this study we perform Exploratory Data Analysis to summarize the main characteristics of this unique longitudinal dataset. The objective is to characterize the evolution of the collected features over time and most importantly, how their dynamics are related to cognitive decline. We show that the longitudinal dataset of Proyecto Vallecas, if conveniently exploited, holds promise to identifying either factors promoting healthy aging and risk factors related to cognitive decline.

scholarly journals The Pathology of Rapid Cognitive Decline in Clinically Diagnosed Alzheimer’s Disease

2019 ◽  
Vol 70 (4) ◽  
pp. 983-993 ◽  
Author(s):  
Christin Nance ◽  
Aaron Ritter ◽  
Justin B. Miller ◽  
Brittany Lapin ◽  
Sarah J. Banks
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Decline ◽  
Rapid Cognitive Decline
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