Consistent Kidney Benefits With Semaglutide vs. Placebo Regardless of Baseline Urine Albumin Creatinine Ratio in Subjects With Type 2 Diabetes at High Cardiovascular Risk: A Post Hoc Analysis of SUSTAIN 6
Bibliographic record
Abstract
Background: In a previous analysis of SUSTAIN 6 and PIONEER 6 (cardiovascular [CV] outcomes trials in subjects with type 2 diabetes [T2D] at high CV risk), semaglutide reduced estimated glomerular filtration rate (eGFR) slope vs placebo, both in addition to standard of care antidiabetes medication. This was most pronounced in those with eGFR <60 mL/min/1.73 m2; it is of clinical interest to understand if this benefit is consistent across urine albumin:creatinine ratio (UACR) groups. The aim of this post hoc analysis was to investigate the effects of semaglutide on eGFR slopes in subjects with different albuminuria levels at baseline in SUSTAIN 6 (PIONEER 6 was excluded as UACR was not collected in this trial). Methods: eGFR slope estimated by a random effect model was compared in subjects by baseline UACR: <30/≥30-≤300/>300 mg/g. To account for potential differences in baseline characteristics, a sensitivity analysis was performed. These subgroups were also compared in those with baseline eGFR ≥30-<60 or ≥60 mL/min/1.73 m2. Results: Across the three subgroups (N=3,232), baseline characteristics were similar, except for higher blood pressure and lower eGFR in subjects with UACR >300 mg/g vs other subgroups. Overall, subjects receiving semaglutide had a slower decline in eGFR at 2 years vs placebo, an effect that was consistent across the three subgroups (p-value for interaction: 0.99; Figure). Results were consistent in the sensitivity analysis and those with eGFR ≥30-<60 vs ≥60 mL/min/1.73 m2. Conclusions: Semaglutide appears to slow eGFR decline vs placebo in subjects with T2D at high CV risk regardless of baseline albuminuria status. Funding: Commercial Support - Novo Nordisk A/SEstimated annual eGFR slopes according to treatment and UACR groups at baseline
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.007 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".