Utility of learning ratio scores from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word List Memory Test in distinguishing patterns of cognitive decline in veterans referred for neuropsychological evaluation

Elevated urine albumin-to-creatinine ratio as a risk factor for cognitive impairment in older adults: A cross-sectional analysis of NHANES data

BACKGROUND

Cognitive impairment is an escalating challenge in aging populations, with risk factors extending beyond traditional domains. The urine albumin-to-creatinine ratio (UACR), a marker of kidney and vascular health, has been associated with systemic dysfunction, yet its association with cognitive impairment remains underexplored. This study aims to delve into the association between UACR and cognitive function in older adults.

METHODS

This study conducted a cross-sectional analysis using data from the 2011-2014 National Health and Nutrition Examination Survey (NHANES), including 2,385 adults aged ≥60 years. Cognitive function was assessed using composite 'Cognitive Scores' derived from standardized tests. Participants were categorized into quartiles based on UACR levels. Multivariate linear regression models were used to evaluate the association between UACR and cognitive scores. Additionally, multivariate logistic regression models were used to assess the relationship between UACR and cognitive impairment, adjusting for demographic and clinical covariates. Smooth curve fitting and interaction analyses were also performed to further investigate the relationship between UACR and cognitive impairment.

RESULTS

For every 10-unit increase in UACR, cognitive scores declined by 0.019 (β = -0.019, 95% CI: -0.036 to -0.002; P < 0.05), and the odds of cognitive impairment increased by 2.6% (OR = 1.026, 95% CI: 1.004 to 1.048; P < 0.05). This trend was also observed in participants with UACR levels below 30, where for every 10-unit increase in UACR, cognitive scores decreased by 0.013 (β = -0.013, 95% CI: -0.027 to -0.001; P < 0.05), and the odds of cognitive impairment increased by 1.4% (OR = 1.014, 95% CI: 1.003 to 1.038; P < 0.05). The study also identified a nonlinear relationship, where the risk of cognitive impairment increased with rising UACR levels, but this risk plateaued at a UACR value of 12.86. Hypertension was found to be a significant factor influencing the relationship between UACR and cognitive impairment (P for interaction < 0.05).

CONCLUSION

This study highlights the significant association between elevated UACR and cognitive impairment in older adults. Notably, even at lower UACR levels, increases in UACR are associated with a higher risk of cognitive impairment. These findings underscore the importance of incorporating kidney health management into strategies aimed at preventing cognitive decline. Further longitudinal studies are needed to clarify the causal relationship and explore interventions targeting UACR to preserve cognitive function.

Evaluating practice effects across learning trials - ceiling effects or something more?

BACKGROUND

Practice effects (PE) are traditionally considered improvements in performance observed resulting from repeated exposure to test materials across multiple testing sessions. While PE are commonly observed for memory tests, this effect has only been considered in summary total scores. The current objective was to consider PE in summary total scores, individual learning trials, and learning slopes.

METHOD

One-week PE for individual trial and learning slope performance was examined on the BVMT-R and HVLT-R in 151 cognitively intact participants and 131 participants with Mild Cognitive Impairment (MCI) aged 65 years and older.

RESULTS

One-week PE were observed across all trials and summary total scores for both memory measures and diagnostic classifications, despite the potential for ceiling effects to limit improvement on retesting. PE were largest on the first trial relative to subsequent learning trials. This effect was diminished - but not eliminated - in participants with MCI. Conversely, no PE were observed for learning slope scores, which was counter to expectations and likely confounded by ceiling effects.

CONCLUSIONS

PE were present across learning trials but not learning slopes, and the initial learning trial at follow-up tended to benefit most from PE relative to subsequent learning trials. Ceiling effects appeared to influence PE for learning slopes more than learning trials. These results highlight the potential diagnostic utility of PE across individual learning trials and inform how they are distributed at follow-up, while also suggesting that learning slopes may be generally stable during longitudinal assessment.