Pre-Discharge and Early Post-Discharge Management of Patients Hospitalized for Acute Heart Failure: A Scientific Statement by the Heart Failure Association of the ESC
Bibliographic record
Abstract
Acute heart failure is a major cause of urgent hospitalizations. These are followed by marked increases in death and rehospitalization rates, which then decline exponentially though they remain higher than in patients without a recent hospitalization. Therefore, optimal management of patients with acute heart failure before discharge and in the early post-discharge phase is critical. First, it may prevent rehospitalizations through the early detection and effective treatment of residual or recurrent congestion, the main manifestation of decompensation. Second, initiation at pre-discharge and titration to target doses in the early post-discharge period, of guideline-directed medical therapy may improve both short- and long-term outcomes. Third, in chronic heart failure, medical treatment is often left unchanged, so the acute heart failure hospitalization presents an opportunity for implementation of therapy. The aim of this scientific statement by the Heart Failure Association of the European Society of Cardiology is to summarize recent findings that have implications for clinical management both in the pre-discharge and the early post-discharge phase after a hospitalization for acute heart failure.
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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 | 0.014 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.010 | 0.009 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".