Insulin Sensitivity Is an Important Determinant of Renal Health in Adolescents With Type 2 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Diabetic nephropathy (DN) remains the most common cause of end-stage renal disease and is a major cause of mortality in type 2 diabetes. Insulin sensitivity is an important determinant of renal health in adults with type 2 diabetes, but limited data exist in adolescents. We hypothesized that measured insulin sensitivity (glucose infusion rate [GIR]) would be associated with early markers of DN reflected by estimated glomerular filtration rate (eGFR) and albumin-creatinine ratio (ACR) in adolescents with type 2 diabetes. RESEARCH DESIGN AND METHODS: Type 2 diabetic (n = 46), obese (n = 29), and lean (n = 19) adolescents (15.1 ± 2.2 years) had GIR measured by hyperinsulinemic-euglycemic clamps. ACR was measured and GFR was estimated by the Bouvet equation (combined creatinine and cystatin C). RESULTS: Adolescents with type 2 diabetes had significantly lower GIR, and higher eGFR and ACR than obese or lean adolescents. Moreover, 34% of type 2 diabetic adolescents had albuminuria (ACR ≥30 mg/g), and 24% had hyperfiltration (≥135 mL/min/1.73 m2). Stratifying ACR and eGFR into tertiles, adolescents with type 2 diabetes in the highest tertiles of ACR and eGFR had respectively lower GIR than those in the mid and low tertiles, after adjusting for age, sex, Tanner stage, BMI, and HbA1c (P = 0.02 and P = 0.04). GIR, but not HbA1c, LDL, or systolic blood pressure, was also associated with eGFR after adjusting for sex and Tanner stage (β ± SE: -2.23 ± 0.87; P = 0.02). CONCLUSIONS: A significant proportion of adolescents with type 2 diabetes showed evidence of early DN, and insulin sensitivity, rather than HbA1c, blood pressure, or lipid control, was the strongest determinant of renal health.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".