Abstract 4366000: Association of Albuminuria with Cognition in Midlife: The CARDIA study
Bibliographic record
Abstract
Background: Chronic kidney disease (CKD) has been associated with late-life cognitive decline. We aim to evaluate whether an early marker of kidney damage, measured by urinary albumin-creatinine ratio (UACR), is associated with midlife cognition. Methods: We analyzed data from 3,281 CARDIA Year 30 participants (mean age = 55±3.6 years). A global cognition score was calculated by summing standardized z-scores from Montreal Cognitive Assessment (MoCA), Digit Symbol Substitution Test (DSST), Stroop (reverse-coded), Rey Auditory Verbal Learning Test (RAVLT), and letter/category fluency tests. UACR was assessed continuously (log-transformed) and categorically (<10, 10–29, ≥30 mg/g; with ≥30 mg/g defined as microalbuminuria). Cross-sectional associations with cognitive scores were evaluated using multivariable linear regression, adjusting for demographics, education, BMI, smoking, and further for diabetes, hypertension, depression, and APOE ε4. Sensitivity analyses were conducted among normotensive participants. Results: Higher UACR was associated with poorer cognitive performance, including lower scores on MoCA (β= –0.06, p< 0.001), Stroop (β= –0.04, p= 0.02), DSST (β= –0.05, p= 0.01), and global cognition (β= –0.03, p= 0.04). A graded inverse association was observed across UACR categories (Table1), with microalbuminuria linked to lower MoCA (β= –0.15, p= 0.01), Stroop (β= –0.17, p= 0.01), and DSST (β= –0.13, p= 0.04); and even moderate UACR levels (10–29 mg/g) linked to reduced MoCA performance (β= –0.10, p= 0.02). Most findings remained consistent in normotensive participants (data not shown). Conclusions: Elevated UACR is associated with poorer midlife cognition, independent of cardiovascular risk factors, and may serve as an early marker of cognitive decline, supporting the importance of kidney health monitoring in dementia prevention.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".