25-hydroxyvitamin D Levels and chronic kidney disease in the AusDiab (Australian Diabetes, Obesity and Lifestyle) study
Bibliographic record
Abstract
BACKGROUND: Low 25-hydroxy vitamin D (25(OH)D) levels have been associated with an increased risk of albuminuria, however an association with glomerular filtration rate (GFR) is not clear. We explored the relationship between 25(OH)D levels and prevalent chronic kidney disease (CKD), albuminuria and impaired GFR, in a national, population-based cohort of Australian adults (AusDiab Study). METHODS: 10,732 adults ≥ 25 years of age participating in the baseline survey of the AusDiab study (1999-2000) were included. The GFR was estimated using an enzymatic creatinine assay and the CKD-EPI equation, with CKD defined as eGFR <60 ml/min/1.73 m(2). Albuminuria was defined as a spot urine albumin to creatinine ratio (ACR) of ≥ 2.5 mg/mmol for men and ≥ 3.5 for women. Serum 25(OH)D levels of <50 nmol/L were considered vitamin D deficient. The associations between 25(OH)D level, albuminuria and impaired eGFR were estimated using multivariate regression models. RESULTS: 30.7% of the study population had a 25(OH)D level <50 nmol/L (95% CI 25.6-35.8). 25(OH)D deficiency was significantly associated with an impaired eGFR in the univariate model (OR 1.52, 95% CI 1.07-2.17), but not in the multivariate model (OR 0.95, 95% CI 0.67-1.35). 25(OH)D deficiency was significantly associated with albuminuria in the univariate (OR 2.05, 95% CI 1.58-2.67) and multivariate models (OR 1.54, 95% CI 1.14-2.07). CONCLUSIONS: Vitamin D deficiency is common in this population, and 25(OH)D levels of <50 nmol/L were independently associated with albuminuria, but not with impaired eGFR. These associations warrant further exploration in prospective and interventional studies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| 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".