Renal Function and Long-Term Decline in Cognitive Function: The Baltimore Longitudinal Study of Aging
Bibliographic record
Abstract
BACKGROUND: Renal disease has been associated with greater risk of dementia and greater cognitive impairment. However, the relationship of lower renal function with long-term decline in specific domains of cognitive function remains unclear among community-dwelling, non-demented individuals. METHODS: Stroke- and dementia-free participants (n = 2,116) were enrolled in the Baltimore Longitudinal Study of Aging, a community-based, prospective, longitudinal study. Renal function was estimated by the inverse of serum creatinine adjusted for age, sex and race and (in sensitivity analyses) estimated glomerular filtration rate (eGFR) using the MDRD formula. Outcome measures were changes in scores on 6 cognitive tests encompassing a range of cognitive functions, measured at 2-year intervals. Mixed-effects regression models examined the longitudinal relations of renal function with cognitive functions after adjusting for demographics, comorbidity and other potential confounders. RESULTS: Mean age at initial testing was 53.9 years (SD 17.1), and 94 participants (4.4%) had an eGFR <60 ml/min/1.73 m(2) and 18.5% had at least one comorbidity. With increasing age, longitudinal increases in creatinine concentrations were associated with more rapid decline in performance on several cognitive measures, including the learning slope of the California Verbal Learning Test, a test of verbal learning (p < 0.01), and the Benton Visual Retention Test, a test of visual memory (p < 0.01). Associations were similar for changes in eGFRMDRD, which was also associated with the rate of decline in verbal memory. CONCLUSION: In a community-based adult population, declines in renal function independently associated with greater long-term declines in visual memory and verbal memory and learning.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".