Abstract 13302: Worsening Heart Failure During Acute Heart Failure Hospitalization: Insights from ASCEND-HF
Bibliographic record
Abstract
Background: After presentation with acute heart failure (AHF), some patients will worsen despite initial standard therapy during the hospitalization. This group of patients with worsening heart failure (WHF) is proposed as an endpoint in AHF trials, but limited data exist regarding the association between WHF and clinical outcomes. We assessed the characteristics and outcomes of patients with and without WHF in the ASCEND-HF trial. Methods: WHF was defined as having at least one sign, symptom or radiologic evidence of new, persistent or WHF requiring new therapy during the index hospitalization. We assessed the relationship between WHF and the endpoints of 30-day death or HF hospitalization, 30-day death and 180-day death using logistic regression and Cox proportional hazards models. We also assessed whether there was a differential association between early (day 1-3) vs. late (day ≥4) WHF and outcomes. Results: Of 7,141 AHF patients, 5% (N=354) experienced WHF. At baseline, patients with WHF were more often male, have a history of atrial fibrillation or diabetes, a lower blood pressure or ejection fraction, and higher creatinine or natriuretic peptide levels. WHF was associated with increased risk for 30- and 180-day outcomes even after risk adjustment ( Table ). There was no evidence of a differential association between early and late WHF with post-discharge outcomes. Conclusions: In the setting of a large AHF trial, 5% of patients developed WHF during the index hospitalization, which was associated with marked increased risk for 30-day mortality or readmission and 180-day mortality. WHF represents an important, patient-centered outcome that should be a focus of future treatments. ![][1] [1]: /embed/graphic-1.gif
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".