SGLT2 Inhibition Is Predicted to Reduce LV End Diastolic Pressure: A Mathematical Modeling Analysis
Bibliographic record
Abstract
In the recent cardiovascular outcomes trials, Sodium Glucose Cotransporter‐2 Inhibitors (SGLT2i) were shown to reduce heart failure hospitalization, but the mechanisms underlying this effect remain unclear. While SGLT2i's direct mechanism of action is in the kidney, the consequences of its renal mechanisms may indirectly induce changes that improve cardiac hemodynamics. We sought to use a mathematical modeling approach to predict the effect of SGLT2i on cardiac hemodynamics in healthy and diabetic virtual subjects. We conjugated a mathematical model of cardiorenal hemodynamics and volume homeostasis with clinical measures of plasma and urinary sodium, water, and creatinine in healthy volunteers who were subjected to dapagliflozin for 7 days. We have shown in our previous study that accounting for direct SGLT2 inhibition, coupled NHE3 downregulation and osmotic diuresis, allowed the model to describe the renal response to SGLT2i. We then simulated the effect of SGLT2i on cardiac hemodynamics. Our simulations predicted a considerable decrease in left ventricle end diastolic pressure (LV EDP) as well as a small decrease in mean arterial pressure (MAP) from the baseline in healthy virtual subjects. In diabetic virtual patients, the predicted decrease in LV EDP was greater than that of healthy volunteers. Ejection fraction (EF) and cardiac output (CO) were minimally changed. While experimental validation is needed, a decrease in LV EDP, without a commiserate decrease in EF and CO, would be expected to reduce fluid congestion and edema, and may help explain how SGLT2i prevent the development of congestion and edema in patients at risk for heart failure. We are currently evaluating the expected effect of SGLT2i on cardiac hemodynamics in virtual patients with existing heart failure. This model provides a means for quantitatively understanding the link between SGLT2i's renal mechanisms and their consequent effects on the failing heart. Support or Funding Information This research is funded by AstraZeneca, Pfizer and Merck. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".