Insufficient Reduction in Heart Rate During Hospitalization Despite Beta-Blocker Treatment in Acute Decompensated Heart Failure: Insights from the ASCEND-HF Trial
Bibliographic record
Abstract
AIMS: Heart failure (HF) can be associated with a higher resting heart rate (HR), and an elevated HR is associated with adverse long-term events. However, the mechanistic and causal role of HR in HF is unclear. This study aimed to investigate changes in HR during hospitalization, and the association between discharge HR and clinical outcomes as well as an interaction with beta-blocker therapy in patients with acute decompensated HF (ADHF). METHODS AND RESULTS: We studied 2906 patients with an LVEF ≤35%, without AF, who were enrolled in the ASCEND-HF trial. A total of 2492 (85.8%) patients had a HR ≥70 b.p.m. at baseline and 1580 (54.4%) patients were on beta-blocker treatment. Although HR was gradually reduced from baseline to discharge (85.5 ± 15.9 b.p.m. at baseline, 81.7 ± 14.1 b.p.m. at 24 h from treatment initiation, and 79.1 ± 12.2 b.p.m. at discharge), 80.2% of the patients still had a HR ≥70 b.p.m. at discharge. Patients with a HR ≥70 b.p.m. at discharge had significantly lower survival rates than those with a HR <70 b.p.m. (adjusted hazard ratio 1.02, 95% confidence interval 1.01-1.04, P = 0.002). Moreover, HR at discharge had a curvilinear association with mortality, and had no significant interaction effect with beta-blocker therapy at discharge (P = 0.82). CONCLUSIONS: Despite current beta-blocker therapy, many patients with hospitalized ADHF with reduced LVEF have relatively high discharge HR, and discharge HR is associated with higher mortality. Further studies are warranted to determine the optimal strategy for HR control to improve outcomes.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".