Reducing heart failure deaths by 25% in 25 years: the ‘25in25’ heart failure summit
Bibliographic record
Abstract
Heart failure (HF) is a major cause of morbidity and mortality in older people, and 80% of people with HF are aged over 60 years. HF is the end point for almost all common cardiovascular diseases, as well as many non-cardiovascular diseases. Despite this, HF remains underdetected and undertreated. Detection and treatment of HF has improved significantly in recent years, with several novel treatments developed in the last decade improving outcomes for patients. Therefore, earlier detection and improved treatment of HF has the potential to reduce morbidity and mortality for older people, particularly given the shift in ageing demographics anticipated over the coming decades. The British Geriatrics Society Cardiovascular Specialist Interest Group recently participated in the British Society for Heart Failure (BSH) '25in25' Heart Failure Summit, which aims to reduce deaths due to HF by 25% in the next 25 years. The 2023 summit comprised experts from over 45 top health organisations across Europe, Canada and the US. The summit brought together cross-disciplinary expertise to support the implementation of strategies to improve outcomes for people living with HF, and, in this commentary, we reflect upon the priorities identified. We discuss the current barriers to the early detection and management of HF, and the particular challenges and complexity of managing HF in older people. Finally, we discuss the role of patient empowerment and how this can lead to improved care for older people living with HF.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".