Effects of Sodium-Glucose Cotransporter-2 Inhibitors on Kidney Outcomes across Baseline Cardiovascular-Kidney-Metabolic Conditions
Bibliographic record
Abstract
Key Points Sodium-glucose cotransporter-2 (SGLT2) inhibitors slowed the rate of eGFR slope decline in patients with heart failure, CKD, and type 2 diabetes mellitus and in all combinations of multimorbid conditions among these diseases. SGLT2 inhibitors decreased kidney composite outcomes among all disease states and different combinations of multimorbidity, except in patients with heart failure with preserved ejection fraction and heart failure without type 2 diabetes mellitus. SGLT2 inhibitors were found to decrease the risk of kidney failure in patients with type 2 diabetes mellitus and also in those with CKD. Background The effects of sodium-glucose cotransporter-2 inhibitors (SGLT2is) on kidney outcomes in patients with varying combinations of heart failure, CKD, and type 2 diabetes mellitus have not been quantified. Methods PubMed and Scopus were queried up to December 2023 for primary and secondary analyses of placebo-controlled trials of SGLT2is in patients with heart failure, CKD, or type 2 diabetes mellitus. Outcomes of interest were composite kidney end point (combination of eGFR <15 ml/min per 1.73 m 2 , sustained doubling of serum creatinine, varying percent change in eGFR, and need for KRT), rate of eGFR slope decline, and albuminuria progression. Hazard ratios (HRs) and mean differences with their 95% confidence intervals (CIs) were extracted onto an Excel sheet, and the results were then pooled using a random-effect model through Review Manager (version 5.3, Cochrane Collaboration). Results Eleven trials ( n =80,928 patients) were included. Compared with the placebo, SGLT2is reduced the risk of the composite kidney end point by 41% (HR, 0.59; 95% CI, 0.42 to 0.83) in heart failure with reduced ejection fraction, 36% (HR, 0.64; 95% CI, 0.55 to 0.73) in CKD, and 38% (HR, 0.62; 95% CI, 0.56 to 0.69) in type 2 diabetes mellitus. A similar pattern of benefit was observed in combinations of these comorbidities and in patients without baseline heart failure, CKD, or type 2 diabetes mellitus. SGLT2is slowed the rate of eGFR slope decline and reduced the risk of sustained doubling of serum creatinine by 36% (HR, 0.64; 95% CI, 0.56 to 0.72) in the overall population, and a consistent effect on kidney outcomes was observed in most subpopulations with available data. Conclusions SGLT2i improved kidney outcomes in cohorts with heart failure, CKD, and type 2 diabetes mellitus, and these effects were consistent across patients with different combinations of these comorbidities.
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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".