Advanced Heart Failure: Guideline-Directed Medical Therapy, Diuretics, Inotropes, and Palliative Care
Bibliographic record
Abstract
Heart failure (HF) is a major cause of mortality, hospitalizations, and reduced quality of life and a major burden for the healthcare system. The number of patients that progress to an advanced stage of HF is growing. Only a limited proportion of these patients can undergo heart transplantation or mechanical circulatory support. The purpose of this review is to summarize medical management of patients with advanced HF. First, evidence-based oral treatment must be implemented although it is often not tolerated. New therapeutic options may soon become possible for these patients. The second goal is to lessen the symptomatic burden through both decongestion and haemodynamic improvement. Some new treatments acting on cardiac function may fulfil both these needs. Inotropic agents acting through an increase in intracellular calcium have often increased risk of death. However, in the recent Global Approach to Lowering Adverse Cardiac Outcomes Through Improving Contractility in Heart Failure (GALACTIC-HF) trial, omecamtiv mecarbil was safe and effective in the reduction of the primary outcome of cardiovascular death or HF event compared with placebo (hazard ratio, 0.92; 95% confidence interval, 0.86-0.99; P = 0.03) and its effects were larger in those patients with more severe left ventricular dysfunction. Patients with severe HF who received omecamtiv mecarbil experienced a significant treatment benefit, whereas patients without severe HF did not (P = 0.005 for interaction). Lastly, clinicians should take care of the end of life with an appropriate multidisciplinary approach. Medical treatment of advanced HF therefore remains a major challenge and a wide open area for further research.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".