Background And Objectives: Recent studies found different associations of cognitive function with albuminuria or estimated GFR (eGFR). Most studies were limited to the elderly or did not take both renal variables into account. Therefore, this study analyzed the association of cognitive function with albuminuria and eGFR in community-dwelling persons aged 35 to 82 years.
Design, Setting, Participants, & Measurements: This was a cross-sectional study comprising 4095 participants of the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study. Cognitive function, measured with the Ruff Figural Fluency Test (RFFT), was treated as the dependent variable, and albuminuria and eGFR were treated as independent variables.
Results: The prevalence of albuminuria <10, 10 to 29, and ≥30 mg/24 h was 54%, 31%, and 15%, respectively. Mean eGFR (± SD) was 79 ± 15 ml/min per 1.73 m(2). Because of interaction between albuminuria and age, analyses were performed per age tertile. After multivariate adjustment, albuminuria ≥ 30 mg/24 h, but not eGFR, was associated with lower RFFT score in the youngest tertile (B -5.3; 95% CI, -0.6 to -9.2; P = 0.05), but not in older tertiles. Moreover, subjects in the youngest tertile with increasing albuminuria (5-15 and >15 mg/24 h) before RFFT measurement had lower mean RFFT scores than subjects with stable albuminuria: mean difference -4.9 (P = 0.3) and -6.7 (P = 0.03), respectively.
Conclusions: In this community-based cohort, elevated albuminuria was associated with worse cognitive function in young but not in old persons. There was no association of eGFR with cognitive function.
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http://dx.doi.org/10.2215/CJN.05530610 | DOI Listing |
Age-related hearing loss (ARHL) is considered one of the most common neurodegenerative disorders in the elderly; however, how it contributes to cognitive decline is poorly understood. With resting-state functional magnetic resonance imaging from 66 individuals with ARHL and 54 healthy controls, group spatial independent component analyses, sliding window analyses, graph-theory methods, multilayer networks, and correlation analyses were used to identify ARHL-induced disturbances in static and dynamic functional network connectivity (sFNC/dFNC), alterations in global network switching and their links to cognitive performances. ARHL was associated with decreased sFNC/dFNC within the default mode network (DMN) and increased sFNC/dFNC between the DMN and central executive, salience (SN), and visual networks.
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Department of Epidemiology and Biostatistics University of California, San Francisco San Francisco California USA.
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Institute of Theoretical Physics, Jagiellonian University, Kraków, Poland.
Understanding brain function relies on identifying spatiotemporal patterns in brain activity. In recent years, machine learning methods have been widely used to detect connections between regions of interest (ROIs) involved in cognitive functions, as measured by the fMRI technique. However, it's essential to match the type of learning method to the problem type, and extracting the information about the most important ROI connections might be challenging.
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Department of Rehabilitation, Tokyo University of Technology, Tokyo, JPN.
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