Acute Heart Failure Care – a Consensus Series of an International Experts' Group
Bibliographic record
Abstract
The care of patients hospitalized for acute heart failure (AHF) has been largely unchanged from the early 1960s until a few years ago, consisting mainly of oxygen and diuretics supplemented sometimes by other vasoactive drugs. These treatments, although effective in the short term in controlling congestion, do not prevent early readmissions and death, occurring in over 30% of patients in the 6 months after an AHF hospitalization. In the last years, studies showed that AHF diagnosis can be improved, early diuretic care can be optimized, and early intensive therapy with combined drug regimens can reduce the rate of adverse outcomes. However, unlike acute coronary syndromes, where guidelines have existed since 1996, there are no separate detailed guidelines for AHF. In a series of four papers (International Expert Opinion Series on AHF Management) an international expert group highlights important aspects of AHF care where the evidence base to inform clinical practice is lacking. These papers focus on (1) diagnosis and treatment during prehospital and in the emergency department, (2) management during the first days of admission, (3) care before and after AHF discharge, and (4) hospitalized AHF management in patients presenting with cardiogenic shock, significant valvular disease, or end-stage renal disease. These papers are not intended to serve as guidelines, but rather to suggest a framework for future recommendations for the diagnosis and treatment of AHF. In the current summary paper, we highlight the main considerations and key recommendations in each of the parts of AHF care.
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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 | 0.031 | 0.056 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 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".