The continuum of prevention and heart failure in cardiovascular medicine: A joint scientific statement from the Heart Failure Society of America and the American Society for Preventive Cardiology
Bibliographic record
Abstract
Heart disease is the leading cause of death worldwide, with heart failure (HF) recognized as its most severe and debilitating manifestation. Though remarkable advancements have led to the establishment of life-saving and quality-of-life-enhancing medical and device-based therapies for HF, HF-related mortality trends have increased over the past decade. To combat this worldwide epidemic, care must evolve so that preventative recommendations are not siloed from HF management. Prevention must be prioritized more broadly, not only in the early detection and deterrence of HF, but across a patient's lifespan in conjunction with therapeutic intervention. Members of the Heart Failure Society of America and the American Society for Preventive Cardiology created this joint Societal Scientific Statement on the Prevention of Heart Failure to emphasize the links between cardiovascular disease prevention and HF and offer a conceptual roadmap along which to consider all aspects of preventative care. This includes primary prevention to reduce the burden of HF, secondary prevention to reduce the impact of HF among those with an established diagnosis of HF, and tertiary prevention, which encompasses the management of risk factors in patients who require advanced therapies, including durable mechanical circulatory support and heart transplantation.
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 | 0.065 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.005 | 0.013 |
| Research integrity | 0.034 | 0.060 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".