Circulating Vitamin D Metabolites and Kidney Disease in Type 1 Diabetes
Bibliographic record
Abstract
CONTEXT: Impaired vitamin D metabolism may contribute to the development and progression of diabetic kidney disease. OBJECTIVE: The aim of the study was to test associations of circulating vitamin D metabolites with risks of incident microalbuminuria, impaired glomerular filtration rate (GFR), and hypertension in type 1 diabetes. DESIGN: We performed a cohort study of 1193 participants in the Diabetes Control and Complications Trial (DCCT), a randomized clinical trial of intensive diabetes therapy, and its observational follow-up, the Epidemiology of Diabetes Interventions and Complications (EDIC) Study. We measured plasma concentrations of 25-hydroxyvitamin D [25(OH)D], 1,25-dihydroxyvitamin D, and 24,25-dihydroxyvitamin D by mass spectrometry at the end of the DCCT and tested associations with incident microalbuminuria, impaired GFR, and hypertension over up to 16 yr of EDIC follow-up. RESULTS: At the time metabolites were measured, mean age was 32.4 yr; mean duration of diabetes, 7.5 yr; mean iothalamate GFR, 132.9 ml/min/1.73 m(2); and geometric mean albumin excretion rate, 11.8 mg/24 h. Over follow-up, 166 cases of microalbuminuria, 54 cases of impaired GFR, and 541 cases of hypertension were observed. Compared with 25(OH)D of at least 30 ng/ml, 25(OH)D below 20 ng/ml was associated with a 65% higher risk of microalbuminuria (95% confidence interval, 7 to 154%) in adjusted analyses. Low concentrations of 24,25-dihydroxyvitamin D, but not 1,25-dihydroxyvitamin D, were also associated with increased risk of microalbuminuria. No circulating vitamin D metabolite was associated with risk of impaired GFR or hypertension. CONCLUSIONS: Low plasma concentrations of 25(OH)D and 24,25-dihydroxyvitamin D are associated with increased risk of microalbuminuria in type 1 diabetes. In contrast, we did not find evidence linking impaired vitamin D metabolism to early GFR loss or the development of hypertension.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".