Galectin-3 and Kidney Function in Type 2 Diabetes Treated with Dapagliflozin: Analysis from DECLARE-TIMI 58
Bibliographic record
Abstract
BACKGROUND: Galectin-3 (Gal-3) is a circulating biomarker of fibrosis, with higher levels being associated with an increased risk of progression of heart failure and kidney disease. Patients with type 2 diabetes mellitus (T2DM) are at increased risk of both. METHODS: DECLARE-TIMI 58 was a randomized, placebo-controlled trial of dapagliflozin in patients with T2DM with or at high risk for atherosclerotic cardiovascular disease and creatinine clearance ≥60 mL/min. In a nested biomarker substudy, Gal-3 was measured at baseline and in adjusted analyses associated with the prespecified kidney-specific composite endpoint [Kidney-EP; sustained ≥40% decrease in estimated glomerular filtration rate (eGFR) to <60 mL/min, new end-stage kidney disease or adjudicated kidney-related death]. RESULTS: Among 14 530 pts, median Gal-3 was 14.9 ng/mL [interquartile range (IQR), 11.9, 18.4]. Gal-3 was weakly associated with urine albumin creatinine ratio (r = 0.098, P < 0.0001) and eGFR (r = -0.27, P < 0.001) at baseline and independently associated with the Kidney-EP:adj hazard ratio (HR) 1.15 [95% confidence interval (CI) 1.03, 1.28] per 1-SD log (Gal-3), P = 0.013. Dapagliflozin significantly reduced the relative risk of the Kidney-EP across quartiles of baseline Gal-3 [overall HR 0.45 (95% CI 0.23, 0.85), P < 0.0001; P interaction = 0.87]. A greater risk difference was observed with dapagliflozin in patients with higher Gal-3, in whom a higher absolute risk at baseline was observed [absolute risk reduction (ARR) Q4 1.9 (95% CI 0.6, 3.2) vs. Q1 0.6% (-0.1, 1.3), ARR P trend 0.048]. CONCLUSIONS: Plasma Gal-3 is independently associated with the progression of kidney dysfunction in patients with T2DM and normal kidney function. There was a gradient of greater absolute benefit for reducing kidney disease progression in patients treated with dapagliflozin and with higher Gal-3 concentrations at baseline, in whom a higher absolute risk was observed. REGISTRATION: clinicaltrials.gov (NCT01730534).
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".