Apolipoprotein E Genotype and Cognitive Impairment in Community-Dwelling Black Older Adults

This study examined the prevalence of cognitive impairment among older adults in central Vietnam and the roles of communication (with or without communication devices) in the association between cognitive impairment and hearing loss. This cross-sectional study was performed on 725 randomly selected community-dwelling older adults aged ≥60 years from Thua Thien Hue province, Vietnam. Participants attended a face-to-face survey. Sociodemographic characteristics, social interaction with or without communication devices, health status and cognitive function using the Mini-Mental State Examination were reported. Ordinal logistic regression analysis was performed to quantify the association between hearing loss and cognitive function by frequency of communication with and without devices. Mild and severe cognitive impairment had prevalence rates of 23.6% and 19.3%, respectively. Cognitive impairment was more prevalent among older adults with hearing-loss, vision loss and difficulties with instrumental activities of daily living (IADL). The association between hearing loss and cognitive impairment was not significant when older adults had frequent communication with others using devices. This study presented the relatively high prevalence of cognitive impairment in community-dwelling older adults in Vietnam. Frequent communication using devices attenuated the association between hearing loss and cognitive impairment.

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Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment

Journal of Alzheimer s Disease ◽

10.3233/jad-201092 ◽

2021 ◽

pp. 1-15

Author(s):

Sung Hoon Kang ◽

Bo Kyoung Cheon ◽

Ji-Sun Kim ◽

Hyemin Jang ◽

Hee Jin Kim ◽

...

Keyword(s):

Machine Learning ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Apolipoprotein E ◽

Cross Validation ◽

Good Accuracy ◽

External Validation ◽

Amnestic Mild Cognitive Impairment ◽

Temporal Region ◽

Apolipoprotein E Genotype

Background: Amyloid (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is important for predicting conversion to Alzheimer’s disease. However, Aβ evaluation through amyloid positron emission tomography (PET) is limited due to high cost and safety issues. Objective: We therefore aimed to develop and validate prediction models of Aβ positivity for aMCI using optimal interpretable machine learning (ML) approaches utilizing multimodal markers. Methods: We recruited 529 aMCI patients from multiple centers who underwent Aβ PET. We trained ML algorithms using a training cohort (324 aMCI from Samsung medical center) with two-phase modelling: model 1 included age, gender, education, diabetes, hypertension, apolipoprotein E genotype, and neuropsychological test scores; model 2 included the same variables as model 1 with additional MRI features. We used four-fold cross-validation during the modelling and evaluated the models on an external validation cohort (187 aMCI from the other centers). Results: Model 1 showed good accuracy (area under the receiver operating characteristic curve [AUROC] 0.837) in cross-validation, and fair accuracy (AUROC 0.765) in external validation. Model 2 led to improvement in the prediction performance with good accuracy (AUROC 0.892) in cross validation compared to model 1. Apolipoprotein E genotype, delayed recall task scores, and interaction between cortical thickness in the temporal region and hippocampal volume were the most important predictors of Aβ positivity. Conclusion: Our results suggest that ML models are effective in predicting Aβ positivity at the individual level and could help the biomarker-guided diagnosis of prodromal AD.

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Exploring the Association between Multimorbidity and Cognitive Impairment in Older Adults Living in the Community: A Review of the Literature

Home Health Care Management & Practice ◽

10.1177/10848223211030468 ◽

2021 ◽

pp. 108482232110304

Author(s):

Grace F. Wittenberg ◽

Michelle A. McKay ◽

Melissa O’Connor

Keyword(s):

Older Adults ◽

Cognitive Impairment ◽

Assessment Tool ◽

Adult Population ◽

Home Health ◽

Adverse Outcomes ◽

Community Dwelling ◽

Cognitive Screening ◽

Review Of The Literature ◽

Increased Risk

Two-thirds of older adults have multimorbidity (MM), or co-occurrence of two or more medical conditions. Mild cognitive impairment (CI) is found in almost 20% of older adults and can lead to further cognitive decline and increased mortality. Older adults with MM are the primary users of home health care services and are at high risk for CI development; however, there is no validated cognitive screening tool used to assess the level of CI in home health users. Given the prevalence of MM and CI in the home health setting, we conducted a review of the literature to understand this association. Due to the absence of literature on CI in home health users, the review focused on the association of MM and CI in community-dwelling older adults. Search terms included home health, older adults, cognitive impairment, and multimorbidity and were applied to the databases PubMed, CINAHL, and PsychInfo leading to eight studies eligible for review. Results show CI is associated with MM in older adults of increasing age, among minorities, and in older adults with lower levels of education. Heart disease was the most prevalent disease associated with increased CI. Sleep disorders, hypertension, arthritis, and hyperlipidemia were also significantly associated with increased CI. The presence of MM and CI was associated with increased risk for death among older adults. Further research and attention are needed regarding the use and development of a validated cognitive assessment tool for home health users to decrease adverse outcomes in the older adult population.

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A Modified CAIDE Risk Score as a Screening Tool for Cognitive Impairment in Older Adults

Journal of Alzheimer s Disease ◽

10.3233/jad-210269 ◽

2021 ◽

pp. 1-14

Author(s):

Magdalena I. Tolea ◽

Jaeyeong Heo ◽

Stephanie Chrisphonte ◽

James E. Galvin

Keyword(s):

Risk Factors ◽

Older Adults ◽

Cognitive Impairment ◽

Risk Score ◽

Clinical Sample ◽

Community Sample ◽

Community Dwelling ◽

Cognitive Testing ◽

Risk Scores ◽

Predictive Values

Background: Although an efficacious dementia-risk score system, Cardiovascular Risk Factors, Aging, and Dementia (CAIDE) was derived using midlife risk factors in a population with low educational attainment that does not reflect today’s US population, and requires laboratory biomarkers, which are not always available. Objective: Develop and validate a modified CAIDE (mCAIDE) system and test its ability to predict presence, severity, and etiology of cognitive impairment in older adults. Methods: Population consisted of 449 participants in dementia research (N = 230; community sample; 67.9±10.0 years old, 29.6%male, 13.7±4.1 years education) or receiving dementia clinical services (N = 219; clinical sample; 74.3±9.8 years old, 50.2%male, 15.5±2.6 years education). The mCAIDE, which includes self-reported and performance-based rather than blood-derived measures, was developed in the community sample and tested in the independent clinical sample. Validity against Framingham, Hachinski, and CAIDE risk scores was assessed. Results: Higher mCAIDE quartiles were associated with lower performance on global and domain-specific cognitive tests. Each one-point increase in mCAIDE increased the odds of mild cognitive impairment (MCI) by up to 65%, those of AD by 69%, and those for non-AD dementia by > 85%, with highest scores in cases with vascular etiologies. Being in the highest mCAIDE risk group improved ability to discriminate dementia from MCI and controls and MCI from controls, with a cut-off of ≥7 points offering the highest sensitivity, specificity, and positive and negative predictive values. Conclusion: mCAIDE is a robust indicator of cognitive impairment in community-dwelling seniors, which can discriminate well between dementia severity including MCI versus controls. The mCAIDE may be a valuable tool for case ascertainment in research studies, helping flag primary care patients for cognitive testing, and identify those in need of lifestyle interventions for symptomatic control.

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The Role of Daily Social Interactions in Detecting Mild Cognitive Impairment

Innovation in Aging ◽

10.1093/geroni/igaa057.2013 ◽

2020 ◽

Vol 4 (Supplement_1) ◽

pp. 598-598

Author(s):

Ruixue Zhaoyang ◽

Stacey Scott ◽

Eric Cerino ◽

Martin Sliwinski

Keyword(s):

Older Adults ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Cognitive Function ◽

Social Interactions ◽

Social Relationships ◽

Daily Basis ◽

Community Dwelling ◽

Normal Cognitive Function ◽

Social Markers

Abstract Social relationships play an important role in cognitive health and aging. However, it is unclear how older adult’s cognitive function affects their everyday social interactions, especially for those with mild cognitive impairment (MCI). This study examined whether older adults with intact cognition vs. MCI differed in their daily social interactions. Community-dwelling older adults from the Einstein Aging Study (N=244, 70-91 yrs) reported their social interactions five times daily for 14 consecutive days using smartphones. Compared to those with normal cognitive function, older adults with MCI reported less frequent positive social interactions (p=0.012) and in-person social activities (p=0.006) on a daily basis. These two groups, however, did not show significant differences in their social relationships assessed by a conventional global questionnaire. The results support that, relative to global social relationships, daily social interactions are more sensitive, ecologically valid social markers that can facilitate the early detection of MCI.

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