The Rationale and Evidence for SGLT2 Inhibitors as a Treatment for Nondiabetic Glomerular Disease
Bibliographic record
Abstract
Background: Recent studies show that sodium-glucose cotransporter 2 inhibitors (SGLT2i), originally approved for glycemic control in patients with type 2 diabetes, also exert renoprotective effects independently from effects on dysglycemia. Moreover, recent work indicates that SGLT2i treatment may be effective in patients with nondiabetic chronic kidney disease, including primary and secondary glomerular diseases. Summary: SGLT2i lower blood glucose by blocking glucose resorption in the early renal proximal tubule through the glucose transporter, SGLT2, leading to enhanced urinary glucose excretion. Recent studies indicate that SGLT2i may have pleiotropic effects on cells other than proximal tubular cells. SGLT2i reduce the glomerular workload by decreasing the intraglomerular pressure, thus ameliorating hyperfiltration, if present, and may also decrease systemic blood pressure. SGLT2i may also act directly on endothelial cells, possibly via modulating the effects of adhesion molecules and reducing inflammatory cytokines and reactive oxygen species. SGLT2i may have direct anti-inflammatory and antifibrotic effects on renal tubules. Some reports suggest direct protective effects on podocytes and mesangial cells as well. Here, we provide a review of the potential mechanisms of renoprotection, therapeutic utility, and potential side effects of SGLT2i in patients with nondiabetic glomerular diseases, based on data from studies carried out in cells, experimental animals, and humans. Key Messages: SGLT2i may be a promising addition to the glomerular disease treatment armamentarium. However, it is unclear at what point of the natural history of specific glomerular diseases (whether this is immune or nonimmune mediated) SGLT2i can be beneficial. Additionally, further studies are needed to assess the long-term efficacy and safety of SGLT2i in patients with nondiabetic glomerular diseases.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".