Effect of semaglutide on kidney function across different levels of baseline HbA1c, blood pressure, body weight and albuminuria in SUSTAIN 6 and PIONEER 6
Bibliographic record
Abstract
BACKGROUND: This post hoc analysis explored the effects of semaglutide on estimated glomerular filtration (eGFR) slope by baseline glycemic control, blood pressure (BP), body mass index (BMI) and albuminuria status in people with type 2 diabetes and high cardiovascular risk. METHODS: Pooled SUSTAIN 6 (Trial to Evaluate Cardiovascular and Other Long-Term Outcomes With Semaglutide in Subjects With Type 2 Diabetes) and PIONEER 6 (A Trial Investigating the Cardiovascular Safety of Oral Semaglutide in Subjects With Type 2 Diabetes) data were analyzed for change in eGFR slope by baseline hemoglobin A1c (HbA1c) (<8%/≥8%; <64/≥64 mmol/mol), systolic BP (<140/90/≥140/90 mmHg) and BMI (<30/≥30 kg/m2). SUSTAIN 6 data were analyzed by baseline urinary albumin:creatinine ratio (UACR; <30/30-300/>300 mg/g). RESULTS: The estimated absolute treatment differences overall in eGFR slope (95% confidence intervals) favored semaglutide versus placebo in the pooled analysis [0.59 (0.29; 0.89) mL/min/1.73 m2/year] and in SUSTAIN 6 [0.60 (0.24; 0.96) mL/min/1.73 m2/year]; the absolute benefit was consistent across all HbA1c, BP, BMI and UACR subgroups (all P-interaction >.5). CONCLUSION: A clinically meaningful reduction in risk of chronic kidney disease progression was observed with semaglutide versus placebo regardless of HbA1c, BP, BMI, and UACR levels.
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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.008 |
| 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) | 0.003 | 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".