<i>European Journal of Heart Failure</i> Consensus Statement. Heart Failure Pharmacotherapy for Patients with Heart Failure with Reduced Ejection Fraction and Concomitant Atrial Fibrillation: Review of Evidence and Call to Action
Bibliographic record
Abstract
Heart failure (HF) and atrial fibrillation (AF) are major global health challenges with rising prevalence and significant morbidity, mortality, and healthcare burden. Despite advances in HF management, AF remains a critical comorbidity that worsens outcomes and requires ad hoc treatment strategies, increasing the risk of non-adherence and side effects. While rhythm control strategies in AF have gained attention for their prognostic benefits in HF, the pharmacological treatment of HF in patients with AF, including the benefit of rhythm versus rate control, remains underexplored. The relationship between HF and AF lacks sufficient evidence and targeted research to assess the optimal treatment strategies. This narrative review critically examines current HF pharmacotherapy in the context of AF, focusing on the four cornerstone treatments and modifiers of prognosis for HF with reduced ejection fraction: beta-blockers, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers/sacubitril-valsartan, aldosterone antagonists, and sodium-glucose co-transporter 2 inhibitors. Although these therapies are well-established in HF patients, their efficacy in patients with concomitant AF requires further prospective investigation. The unique challenges posed by AF, including arrhythmia-induced remodelling and cardiomyopathy, necessitate a more individually tailored treatment. We also highlight critical knowledge gaps and the need for dedicated clinical trials specifically assessing HF therapies in AF subgroups, such as paroxysmal, long-standing persistent and permanent AF, and the benefit of heart rate and rhythm control strategies. The future of precision medicine in HF-AF management lies in bridging these evidence gaps through targeted research and interdisciplinary collaboration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.013 | 0.008 |
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".