Differentiating Mild Cognitive Impairment and Cognitive Changes of Normal Aging

Mosti, Caterina; Rog, Lauren A.; Fink, Joseph W.

doi:10.1007/978-3-319-93497-6_28

Cited by 9 publications

(5 citation statements)

References 114 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The present findings suggest that the association between mild depressive symptomology and prefrontal/limbic atrophy also extends to the left hippocampus. Although the mechanism of this relationship remains largely unknown, it is possible that such mood or affect symptomology is associated with the subtle changes in cognition as a function of emerging hippocampal and cortical atrophy [ 109 ]. Another perspective is that hippocampal atrophy may be directly affecting networks that are associated with mood and impact depressive symptomology through numerous mechanisms such as estrogen depletion and deregulation of certain neural circuits [ 110 ].…”

Section: Discussionmentioning

confidence: 99%

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

Drouin

McFall

Potvin³

et al. 2022

JAD

View full text Add to dashboard Cite

Background: Hippocampal atrophy is a well-known biomarker of neurodegeneration, such as that observed in Alzheimer’s disease (AD). Although distributions of hippocampal volume trajectories for asymptomatic individuals often reveal substantial heterogeneity, it is unclear whether interpretable trajectory classes can be objectively detected and used for prediction analyses. Objective: To detect and predict hippocampal trajectory classes in a computationally competitive context using established AD-related risk factors/biomarkers. Methods: We used biomarker/risk factor and longitudinal MRI data in asymptomatic adults from the AD Neuroimaging Initiative (n = 351; Mean = 75 years; 48.7% female). First, we applied latent class growth analyses to left (LHC) and right (RHC) hippocampal trajectory distributions to identify distinct classes. Second, using random forest analyses, we tested 38 multi-modal biomarkers/risk factors for their relative importance in discriminating the lower (potentially elevated atrophy risk) from the higher (potentially reduced risk) class. Results: For both LHC and RHC trajectory distribution analyses, we observed three distinct trajectory classes. Three biomarkers/risk factors predicted membership in LHC and RHC lower classes: male sex, higher education, and lower plasma Aβ1–42. Four additional factors selectively predicted membership in the lower LHC class: lower plasma tau and Aβ1–40, higher depressive symptomology, and lower body mass index. Conclusion: Data-driven analyses of LHC and RHC trajectories detected three classes underlying the heterogeneous distributions. Machine learning analyses determined three common and four unique biomarkers/risk factors discriminating the higher and lower LHC/RHC classes. Our sequential analytic approach produced evidence that the dynamics of preclinical hippocampal trajectories can be predicted by AD-related biomarkers/risk factors from multiple modalities.

show abstract

Section: Discussionmentioning

confidence: 99%

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

Drouin

McFall

Potvin³

et al. 2022

JAD

View full text Add to dashboard Cite

show abstract

“…This corroborates with established literature that normal aging changes are totally different from moderate cognitive impairment or dementia. MCI represents the intermediate phase between normal aging and dementia, where novel early interventions can be rendered by healthcare providers [37].…”

Section: Discussionmentioning

confidence: 99%

Factors Influencing the Deterioration from Cognitive Decline of Normal Aging to Dementia among Nursing Home Residents

Hayajneh

Rababa

Alghwiri

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: A dearth of differential research exists regarding the determinants of mild cognitive impairment (MCI) and moderate cognitive impairment or dementia among nursing home residents. This study aimed to identify and examine the factors that lead to progression of MCI to moderate cognitive impairment or dementia in nursing home residents.Methods: A cross-sectional design was used in this study. Convenience sampling of 182 participants was conducted in nursing homes located in the central part of Jordan. Montreal cognitive assessment (MoCA) was used to screen both MCI and moderate cognitive impairment or dementia. Bivariate analysis, including t-test and ANOVA test, and logistic and linear regression models were used to examine and identify the predictors of dementia.Results: Most nursing home residents had MCI (87.4%) compared to a few with moderate cognitive impairment or dementia. Age (t = -2.773), number of comorbidities (t = -4.045), depression (t = -4.809), frailty (t = -4.038), and quality of life physical (t = 3.282) and mental component summaries (t = 2.469) were significantly different between the stages of cognitive impairment. Marital status (t = -4.050, p < 0.001), higher-income (t = 3.755, p < 0.001), recent hospitalization (t = 2.622,p = 0.01), depression (t = -2.737, p = 0.007), and frailty (t = 2.852, p = 0.005) were significantly associated with mental ability scores among nursing home residents.Conclusion: The coexistence of comorbidities and depression among nursing home residents with MCI necessitates prompt management by healthcare providers to combat depressive symptoms in order to delay the dementia trajectory among at-risk residents.

show abstract

Section: Discussionmentioning

confidence: 99%

Factors Influencing the Deterioration from Cognitive Decline of Normal Aging to Dementia among Nursing Home Residents

Hayajneh

Rababa

Alghwiri

et al. 2020

Preprint

View full text Add to dashboard Cite

Background: A dearth of differential research exists regarding the determinants of mild cognitive impairment (MCI) and moderate cognitive impairment or dementia among nursing home residents. This study aimed to identify and examine the association between medical factors (number of comorbidities, hospitalization, disability, depression, frailty and quality of life) and moderate cognitive impairment or dementia in nursing homes residents.Methods: A cross-sectional design was used in this study. Convenience sampling of 182 participants was conducted in nursing homes located in the central part of Jordan. Montreal cognitive assessment (MoCA) was used to screen both MCI and moderate cognitive impairment or dementia. Bivariate analysis, including t-test and ANOVA test, and logistic and linear regression models were used to examine and identify the medical factors associated with moderate cognitive impairment or dementia compared to mild cognitive impairment.Results: Most nursing home residents had MCI (87.4%) compared to a few with moderate cognitive impairment or dementia. Age (t = -2.773), number of comorbidities (t = -4.045), depression (t = -4.809), frailty (t = -4.038), and quality of life physical (t = 3.282) and mental component summaries (t = 2.469) were significantly different between the stages of cognitive impairment. Marital status (t = -4.050, p < 0.001), higher-income (t = 3.755, p < 0.001), recent hospitalization (t = 2.622,p = 0.01), depression (t = -2.737, p = 0.007), and frailty (t = 2.852, p = 0.005) were significantly associated with mental ability scores among nursing home residents.Conclusion: The coexistence of comorbidities and depression among nursing home residents with MCI necessitates prompt management by healthcare providers to combat depressive symptoms in order to delay the dementia trajectory among at-risk residents.Trail registration: ClinicalTrials.gov NCT04589637, October 15,2020, Retrospectively registered.

show abstract

Differentiating Mild Cognitive Impairment and Cognitive Changes of Normal Aging

Cited by 9 publications

References 114 publications

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

Data-Driven Analyses of Longitudinal Hippocampal Imaging Trajectories: Discrimination and Biomarker Prediction of Change Classes

Factors Influencing the Deterioration from Cognitive Decline of Normal Aging to Dementia among Nursing Home Residents

Factors Influencing the Deterioration from Cognitive Decline of Normal Aging to Dementia among Nursing Home Residents

Contact Info

Product

Resources

About