Role of Dapagliflozin in Attenuating Right Ventricular Remodelling: Transverse Aortic Constriction Model
Bibliographic record
Abstract
Heart Failure (HF) might be better considered a biventricular disease whereby left ventricular (LV) dysfunction leads to right ventricular (RV) dysfunction and vice versa. Structurally, the two chambers not only share a common septum and a pericardial space, but also share myocyte bundles that cross between the ventricles. Dapagliflozin is a sodium glucose linked co-transporter 2 (SGLT2) inhibitor that has recently been shown to improve heart function in the setting of diabetes. However, the effect of dapagliflozin on HF in a non-diabetic setting is unknown. Currently, dysfunction of the RV does not have a treatment strategy that has displayed a reduction in mortality. Therefore, we hypothesized that by reducing excess fluid volume, dapagliflozin will reduce RV chamber dilatation and wall tension, thereby leading to a reduction in RV hypertrophy and improved function. We utilized transverse aortic constriction (TAC) to induce pressure overload and administered one of three treatments: vehicle, dapagliflozin or perindopril, an angiotensin-converting enzyme inhibitor. At end study, measurement for biochemistry, echocardiography and cardiac catheterization took place. Overall, our results demonstrate a neutral impact by dapagliflozin, on a pressure overload induced model of TAC.
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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) | 0.001 | 0.001 |
| 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 | 0.002 |
| 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".