Kidney Disease and Cognitive Function: African American-Diabetes Heart Study MIND
Bibliographic record
Abstract
AIMS: Albuminuria and reduced estimated glomerular filtration rate (eGFR) are linked with poorer cognitive performance in European-ancestry populations with advanced nephropathy; relationships in African Americans (AAs) with type 2 diabetes (T2D) are less clear. Tests of cognitive performance, urine albumin:creatinine ratio (UACR), and CKD-EPI eGFR were performed in unrelated AAs with T2D to determine relationships. METHODS: Cross-sectional analysis of 263 unrelated AAs with T2D recruited in the African American-Diabetes Heart Study (AA-DHS) MIND. Global cognitive function (mini-mental state exam [3MSE] and Montreal Cognitive Assessment [MoCA]), memory (Rey Auditory Verbal Learning Test [RAVLT]), executive function (Stroop, verbal fluency for animals, and Digit Symbol Copy [DSC]), UACR, and eGFR were determined. Relationships between cognitive tests and renal parameters were assessed using multivariate models, adjusted for age, gender, body mass index, hemoglobin A1c, level of education, hypertension, and LDL cholesterol. RESULTS: Participants had a mean ± SD age of 60.2 ± 9.7 years, 62.7% were female, T2D duration was 14.3 ± 8.9 years, eGFR 86.0 ± 23.2 ml/min/1.73 m(2), and UACR 155.8 ± 542.1 (median 8.1) mg/g. In adjusted models, higher UACR was associated with worse 3MSE (p = 0.014), MoCA (p = 0.0089), DSC (p = 0.0004), Stroop performance time (p = 0.003), Stroop errors (p = 0.032), and Stroop interference (p = 0.026). Higher eGFR was associated with better performance on DSC (p = 0.0071). CONCLUSIONS: In AAs with T2D, albuminuria and eGFR were associated with cognitive function, even in mild kidney disease. These data stress the need for interventions to prevent cognitive decline well before the late stages of kidney disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".