The SGLT2i Dapagliflozin Reduces RV Hypertrophy Independent of Changes in RV Pressure Induced by Pulmonary Artery Banding
Bibliographic record
Abstract
Abstract Background— Sodium glucose linked transporter 2 (SGLT2) inhibition not only reduces morbidity and mortality in patients with diagnosed heart failure but also prevents the development of heart failure hospitalization in those at risk. While studies to date have focused on the role of SGLT2 inhibition in left ventricular failure, whether this drug class might be similarly efficacious in the treatment and prevention of right heart failure has not been unexplored.Hypothesis: We hypothesized that SGLT2 inhibition would reduce the structural, functional and molecular responses to pressure overload of the right ventricle.Methods: Thirteen-week-old Fischer F344 rats underwent pulmonary artery banding (PAB) or sham surgery prior to being randomized to receive either the SGLT2 inhibitor: dapagliflozin (1.5mg/kg/day) or vehicle by oral gavage. After six weeks of treatment, animals underwent transthoracic echocardiography and invasive hemodynamic studies. Animals were then terminated, and their hearts harvested for structural and molecular analyses.Results: PAB induced features consistent with a compensatory response to increased right ventricular (RV) afterload with elevated mass, end systolic pressure, collagen content and alteration in calcium handling protein expression (all p<0.05 when compared to sham + vehicle). Dapagliflozin reduced RV mass, including both wet and dry weight as well as normalizing the protein expression of SERCA 2A, AMPkinase and LC3I/II ratio expression (all p<0.05).Significance: Dapagliflozin reduces the structural, functional, and molecular manifestations of right ventricular pressure overload. Whether amelioration of these early changes in the RV may ultimately lead to a reduction in RV failure remains to be determined.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".