The European Heart Failure Management Resources, Treatment Reimbursement and Activities of Professional and Patient Organizations
Bibliographic record
Abstract
AIMS: The European Heart Failure (HF) Survey was developed by the Heart Failure Association (HFA) of the European Society of Cardiology (ESC) to map HF management resources, reimbursement of drugs/devices for HF treatment, and structure and activities of HF professional and patient organizations. METHODS AND RESULTS: The survey encompassed 43 ESC member countries. The median number of hospitals with dedicated HF centres was 2.6 (interquartile range [IQR] 0.9-4.7) per million people. Natriuretic peptide assessment was available at a median of 6.1 (IQR 1.8-10.6) emergency departments and 8.2 (IQR 1.3-14.7) hospitals per million people, respectively, whilst cardiac magnetic resonance was available at a median of 2.0 (IQR 0.9-3.8) hospitals per million people. Short-term and long-term mechanical circulatory support and heart transplantation were available at a median of 1.1 (IQR 0.5-2.4), 0.4 (IQR 0.0-0.5) and 0.3 (0.2-0.5) hospitals per million people, respectively. Whilst essential HF medications were mostly available and reimbursed, gaps were observed in availability and funding of newer and advanced therapies. Density of all diagnostic and therapeutic capabilities was greater in countries with more favourable socioeconomic status. National HF societies were reported in 98% of countries, whilst HF patient organizations in 45% of countries.anaemia. CONCLUSIONS: The European HF Survey is the result of long-standing HFA/ESC efforts to monitor HF epidemiology, management resources, educational and awareness activities. It offers a valuable assessment of current management capabilities, highlighting challenges in providing contemporary standards of care. It also provides insights into future directions needed to address these gaps.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".