Associations of Kidney Tubular Biomarkers With Incident Macroalbuminuria and Sustained Low eGFR in DCCT/EDIC
Bibliographic record
Abstract
OBJECTIVE: Tubulointerstitial injury contributes to diabetic kidney disease (DKD) progression. We tested tubular biomarker associations with DKD development in type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: We performed a case-cohort study examining associations of tubular biomarkers, measured across seven time points spanning ∼30 years, with incident macroalbuminuria ("severely elevated albuminuria," urinary albumin excretion rate [AER] ≥300 mg/day) and sustained low estimated glomerular filtration rate (eGFR) (persistent eGFR <60 mL/min/1.73 m2) in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study. Biomarkers included KIM-1 and sTNFR1 in serum/plasma, MCP-1 and EGF in urine, and a composite tubular secretion score reflecting secreted solute clearance. We assessed biomarkers using single values, as mean values from consecutive time points, and as change over consecutive time points, each as time-updated exposures. RESULTS: At baseline, mean diabetes duration was 5.9 years, with mean HbA1c 8.9%, eGFR 125 mL/min/1.73 m2, and AER 16 mg/day. There were 4.8 and 3.5 cases per 1,000 person-years of macroalbuminuria and low eGFR, respectively. Assessed according to single biomarker values, KIM-1 was associated with risk of subsequent macroalbuminuria and low eGFR (hazard ratio [HR] per 20% higher biomarker 1.11 [95% CI 1.06, 1.16] and 1.12 [1.04, 1.21], respectively) and sTNFR1 was associated with subsequent macroalbuminuria (1.14 [1.03, 1.25]). Mean KIM-1 and EGF-to-MCP-1 ratio were associated with subsequent low eGFR. In slope analyses, increases in KIM-1 and sTNFR1 were associated with subsequent macroalbuminuria (per 20% biomarker increase, HR 1.81 [1.40, 2.34] and 1.95 [1.18, 3.21]) and low eGFR (2.26 [1.65, 3.09] and 2.94 [1.39, 6.23]). CONCLUSIONS: Serial KIM-1 and sTNFR1 are associated with incident macroalbuminuria and sustained low eGFR in T1D.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 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".