405-P: Glycemic Control Impacts Renal Function Decline among People with Type 1 Diabetes after the Onset of Diabetic Kidney Disease
Bibliographic record
Abstract
While poor glycemic control increases the risk of diabetic kidney disease (DKD) , its impact on renal function decline among those with established DKD is unclear. To examine this, we tested the relationship between baseline HbA1c and renal outcomes in the 3-year Preventing Early Renal Loss (PERL) trial (n=530) , which included persons with type 1 diabetes (T1D) and early-to-moderate DKD (eGFR 40-100 ml/min/1.73m2 and persistent albuminuria and/or ongoing GFR decline) . In Cox regression models, baseline HbA1c was associated (p<0.0001) with a higher risk of progression to ESKD or serum creatinine doubling (HR 1.87 per HbA1c unit increment, 95% CI 1.42-2.47) , and in mixed-effects linear regression models, with 0.87 and 0.51 ml/min/1.73m2/year higher rates of estimated glomerular filtration rate (eGFR) and iohexol GFR decline (p<0.00for both) . Baseline albumin excretion rate (AER) was a modifier of the HbA1c-GFR slope relationships (p for interaction <0.05) , such that HbA1c was associated with a higher rate of GFR decline among those with AER≥200 μg/min than among those with AER<20 or 20≤AER<200 (Fig.1) . Thus, worse glycemic control in PERL was a major determinant of GFR decline and ESKD risk after DKD onset, especially in persons with overt proteinuria. Efforts to normalize HbA1c should continue among such persons. Disclosure H.Shah: None. J.B.Mcgill: Advisory Panel; Gilead Sciences, Inc., Lilly Diabetes, MannKind Corporation, Novo Nordisk A/S, Provention Bio, Inc., Salix Pharmaceuticals, Consultant; Bayer AG, Boehringer Ingelheim International GmbH, Research Support; Dexcom, Inc., Novo Nordisk. I.B.Hirsch: Consultant; Abbott Diabetes, Bigfoot Biomedical, Inc., GWave, Roche Diabetes Care, Research Support; Beta Bionics, Inc., Insulet Corporation, Medtronic. C.Wu: None. A.Galecki: None. M.Mauer: None. A.Doria: Research Support; Novo Nordisk Foundation. Perl consortium: n/a. Funding National Institutes of Health UC4DK101108Juvenile Diabetes Research Foundation 17-2012-377The Leona M. and Harry B. Helmsley Charitable Trust 2018PG-T1D014
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".