Abstract 13158: Hospitalization for De Novo versus Worsening Chronic Heart Failure: Insights From the ASCEND-HF Trial
Bibliographic record
Abstract
Introduction: Heart failure (HF) is a heterogeneous syndrome and individual patient survival varies widely. It is unclear how hospitalized acute HF (AHF) patients who are long-term chronic HF survivors differ from those with more recent HF diagnoses. Methods: The ASCEND-HF trial randomized 7,141 hospitalized AHF patients with reduced or preserved ejection fraction (EF) to nesiritide or placebo in addition to standard care. The present analysis compared patients by duration of HF diagnosis prior to index hospitalization using pre-specified cutpoints (0-1 month [i.e. “ de novo ”], >1-12 months, >12-60 months, >60 months). Results: Overall, 5,741 (80.4%) patients had documentation of duration of HF diagnosis ( de novo , N=1536; >1-12 months, N=1020; >12-60 months, N=1653; >60 months, N=1532). Mean age ranged from 64-66 years and mean EF from 29-32% across all HF duration groups. Compared to patients with longer HF duration, de novo patients were more likely to have non-ischemic HF etiology, fewer comorbidities, lower natriuretic peptide levels, and better baseline functional status (all P-value <0.01). After adjustment, compared to de novo patients, longer HF duration was associated with more persistent dyspnea at 24 hours and increased 180-day mortality (Table). The influence of HF duration on mortality did not differ by age, gender, race, etiology of HF, or EF (all P-value for interaction ≥0.05). Conclusion: In this large AHF trial cohort, patient profile differed by duration of the HF diagnosis. De novo HF diagnosis was independently associated with greater early dyspnea relief and improved post-discharge survival compared to those with chronic HF diagnoses.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".