Renal and Cardiovascular Risk According to Tertiles of Urinary Albumin-to-Creatinine Ratio: The Adolescent Type 1 Diabetes Cardio-Renal Intervention Trial (AdDIT)
Bibliographic record
Abstract
OBJECTIVE Baseline data from the Adolescent Type 1 Diabetes Cardio-Renal Intervention Trial (AdDIT) indicated that tertiles of urinary albumin-to-creatinine ratios (ACRs) in the normal range at age 10–16 years are associated with risk markers for diabetic nephropathy (DN) and cardiovascular disease (CVD). We aimed to determine whether the top ACR tertile remained associated with DN and CVD risk over the 2–4-year AdDIT study. RESEARCH DESIGN AND METHODS One hundred fifty adolescents (mean age 14.1 years [SD 1.6]) with baseline ACR in the upper tertile (high-ACR group) recruited to the AdDIT trial, who remained untreated, and 396 (age 14.3 years [1.6]) with ACR in the middle and lower tertiles (low-ACR group), who completed the parallel AdDIT observational study, were evaluated prospectively with assessments of ACR and renal and CVD markers, combined with carotid intima-media thickness (cIMT) at baseline and end of study. RESULTS After a median follow-up of 3.9 years, the cumulative incidence of microalbuminuria was 16.3% in the high-ACR versus 5.5% in the low-ACR group (log-rank P < 0.001). Cox models showed independent contributions of the high-ACR group (hazard ratio 4.29 [95% CI 2.08–8.85]) and HbA1c (1.37 [1.10–1.72]) to microalbuminuria risk. cIMT change from baseline was significantly greater in the high- versus low-ACR group (mean difference 0.010 mm [0.079], P = 0.006). Changes in estimated glomerular filtration rate, systolic blood pressure, and hs-CRP were also significantly greater in the high-ACR group (P < 0.05). CONCLUSIONS ACR at the higher end of the normal range at the age of 10–16 years is associated with an increased risk of progression to microalbuminuria and future CVD risk, independently of HbA1c.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".