Pathophysiology and Clinical Use of Agents with Vasodilator Properties in Acute Heart Failure. A Scientific Statement of the Heart Failure Association (HFA) of the European Society of Cardiology (ESC)
Bibliographic record
Abstract
Acute heart failure (AHF) affects millions of people each year and vasodilators have been a central part of treatment for over 25 years. The haemodynamic effects of vasodilators vary considerably among individual agents. Some vasodilators, such as nitrates, primarily act on the venous system by redistributing the circulating blood volume away from the heart towards the venous capacitance system. Other vasodilators, such as nesiritide, lead to balanced vasodilatation in the arteries and veins, decreasing left ventricular afterload and preload. Considering mechanisms of action, intravenous vasodilators are thought to be effective in patients with AHF, particularly in those with acute pulmonary oedema, where increased cardiac filling pressures and elevated systemic blood pressures occur in the absence of, or with minimal systemic fluid accumulation. However, the 2021 European heart failure guidelines have downgraded the use of vasodilators due to two recent studies and several contemporary meta-analyses failing to show benefit in terms of survival. Thus, there remains no firm recommendation suggesting the use of vasodilator treatment over usual care. In addition, despite repeated efforts to develop new vasodilatory agents, no novel therapy has outperformed traditional AHF management. In parallel with the development of novel vasodilators, changing the design of clinical trials for AHF to consider phenotype diversity of AHF patients remains an unmet need. New randomized clinical trials should particularly focus on subgroups that may mechanistically derive benefit from vasodilators, which may entail moving enrolment of patients to clinical settings close to moment of decompensation, such as the emergency department.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".