Medical Therapy for Heart Failure Associated With Pulmonary Hypertension
Bibliographic record
Abstract
The past 2 decades have witnessed a >40% improvement in mortality for patients with heart failure and left ventricular systolic dysfunction. 1 This success has coincided with the stepwise availability of drugs that target neurohormonal activation: β-adrenergic receptor blockers (β-blockers), ACE (angiotensin-converting enzyme) inhibitors and ANG (angiotensin) II blockers, neprilysin inhibitors, and aldosterone antagonists. Our understanding of right heart failure (RHF) has lagged behind and many proven targeted therapies for left heart failure do not appear to provide similar benefits for RHF. Until recently, the right ventricle (RV) has often been viewed as less important than the left ventricle and in contemporary literature received the moniker “The Forgotten Ventricle”. Recent advances in echocardiography and magnetic resonance imaging have enabled detailed assessments of RV anatomy and physiology in both health and disease allowing us to more accurately describe the clinical sequelae and end-organ manifestations of RHF. RV function is now recognized as one of the most important predictors of prognosis in many cardiovascular disease states. 2 Despite the significance of RV function to survival, there are no clinically approved therapies that directly nor selectively improve RV function. As well, relative to our understanding of left heart failure, the basis for RHF remains poorly understood. This article aims to condense the current knowledge on RV adaptation and failure, review current management strategies for RHF, and explore evolving therapeutic approaches.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.007 | 0.003 |
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".