Cardiac mechanisms of the beneficial effects of SGLT2 inhibitors in heart failure: Evidence for potential off-target effects
Bibliographic record
Abstract
Sodium glucose cotransporter 2 inhibitors (SGLT2i) constitute a promising drug treatment for heart failure patients with either preserved or reduced ejection fraction. Whereas SGLT2i were originally developed to target SGLT2 in the kidney to facilitate glucosuria in diabetic patients, it is becoming increasingly clear that these drugs also have important effects outside of the kidney. In this review we summarize the literature on cardiac effects of SGLT2i, focussing on pro-inflammatory and oxidative stress processes, ion transport mechanisms controlling sodium and calcium homeostasis and metabolic/mitochondrial pathways. These mechanisms are particularly important as disturbances in these pathways result in endothelial dysfunction, diastolic dysfunction, cardiac stiffness, and cardiac arrhythmias that together contribute to heart failure. We review the findings that support the concept that SGLT2i directly and beneficially interfere with inflammation, oxidative stress, ionic homeostasis, and metabolism within the cardiac cell. However, given the very low levels of SGLT2 in cardiac cells, the evidence suggests that SGLT2-independent effects of this class of drugs likely occurs via off-target effects in the myocardium. Thus, while there is still much to be understood about the various factors which determine how SGLT2i affect cardiac cells, much of the research clearly demonstrates that direct cardiac effects of these SGLT2i exist, albeit mediated via SGLT2-independent pathways, and these pathways may play a role in explaining the beneficial effects of SGLT2 inhibitors in heart failure.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".