Mapping of Current Practices of Palliative Care for Patients with Heart Failure Throughout Europe: A Scoping Review
Bibliographic record
Abstract
Heart failure (HF) is a growing health and societal challenge in Europe, due to an increasingly elderly, frail and multimorbid population. Many patients with HF experience a high burden of complex and multidimensional symptoms leading to a reduced quality of life and significant socioeconomic impact. Despite proven benefits, the integration of palliative care into HF management pathways remains inconsistent and underutilized. We aim to map how current national and international guidelines recommend integrating palliative care into HF management across the 10 countries represented by the EU-funded RAPHAEL consortium (Horizon Europe programme, No 101137170): Belgium, Germany, Lithuania, the Netherlands, Spain, Italy, Poland, Sweden, Switzerland and the United Kingdom. A systematic search was conducted across six databases (EMBASE, Global Health, MEDLINE, PsycINFO, The Cochrane Library and Web of Science) for publications from 1 January 2000 to 25 May 2024. Eligible publications focused on adults with HF and models of palliative care integration. Data were synthesized using content analysis. Of 1543 records screened, 13 publications were included. Most studies were guidelines, consensus or position papers; only one was qualitative research. The definition of the population with HF eligible for palliative care was heterogeneous and inconsistently defined, mostly by symptoms (4/13 publications; 31%) and pathophysiology (2/13; 15%). The most frequent triggers for palliative care referral were clinical features and symptoms (8/13; 62%), patients approaching the end of life (8/13; 62%), and symptomatic deterioration despite optimal therapy (7/13; 54%). Additional triggers included multiple (>1) unplanned hospitalizations (6/13; 46%) and spiritual, emotional or social issues (7/13; 54%). Outcomes of palliative care referral for HF patients focused on quality of life (9/13; 69%) and symptom control (9/13; 69%). Multiprofessional involvement was emphasized with cardiologists (12/13; 92%), nurses (10/12; 77%), palliative care specialists (9/13; 69%) and primary care physicians (4/13; 31%). Publications generally noted that despite increased awareness and recommendations, referrals remain low and mostly late stages. This review underscores the need for structured, early integration of palliative care in HF management across Europe with clear triggers for palliative care referral, application of standardized pathways and fostering of multiprofessional collaboration. Developing these, while simultaneously addressing implementation challenges through policy development, could improve patient outcomes and quality of life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".