Cardiac Remodelling in the Era of the Recommended Four Pillars Heart Failure Medical Therapy
Bibliographic record
Abstract
Cardiac remodelling is a key determinant of worse cardiovascular outcome in patients with heart failure (HF) and reduced ejection fraction (HFrEF). It affects both the left ventricle (LV) structure and function as well as the left atrium (LA) and the right ventricle (RV). Guideline recommended medical therapy for HF, including angiotensin-converting enzyme inhibitors/angiotensin receptors II blockers/angiotensin receptor blocker-neprilysin inhibitors (ACE-I/ARB/ARNI), beta-blockers, mineralocorticoid receptor antagonists (MRA) and sodium-glucose transport protein 2 inhibitors (SGLT2i), have shown to improve morbidity and mortality in patients with HFrEF. By targeting multiple pathophysiological pathways, foundational HF therapies are supposed to drive their beneficial clinical effects by a direct myocardial effect. Simultaneous initiation of guideline directed medical therapy (GDMT) through a synergistic effect promotes a 'reverse remodelling', leading to a full or partial recovered structure and function by enhancing systemic neurohumoral regulation and energy metabolism, reducing cardiomyocyte apoptosis, lowering oxidative stress and inflammation and adverse extracellular matrix deposition. The aim of this review is to describe how these classes of drugs can drive reverse remodelling in the LV, LA and RV and improve prognosis in patients with HFrEF.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".