Acute Heart Failure and Atrial Fibrillation: Insights From the Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure (ASCEND‐HF) Trial
Bibliographic record
Abstract
BACKGROUND: Patients with acute heart failure (AHF) frequently have atrial fibrillation (AF), but how this affects patient-reported outcomes has not been well characterized. METHODS AND RESULTS: We examined dyspnea improvement and clinical outcomes in 7007 patients in the Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure (ASCEND-HF) trial. At baseline, 2677 (38.2%) patients had current or a history of AF and 4330 (61.8%) did not. Patients with a history of AF were older than those without (72 vs. 63 years) and had more comorbidities and a higher median left ventricular ejection fraction (31% vs. 27%, P<0.001). Compared to those without AF, patients with AF had a similar mean ventricular rate on admission (81 vs. 83 beats per minute [bpm]; P=0.138) but a lower rate at discharge (75 vs. 78 bpm; P<0.001). There was no difference in dyspnea improvement between patients with and without AF at 6 hours (P=0.087), but patients with AF had less dyspnea improvement at 24 hours (P<0.001). Compared to patients without AF, patients with AF had a higher 30-day all-cause mortality rate (4.7% vs. 3.3%; P=0.005), a higher 30-day HF rehospitalisation rate (7.2% vs. 5.3%; P=0.001), and a higher coprimary composite outcome of 30-day death or readmission (11.6% vs. 8.6%; P<0.001). This difference persisted after adjustment for prognostic variables (adjusted odds ratio=1.19; (95% confidence interval, 1.02 to 1.38; P=0.029). CONCLUSIONS: Among patients admitted to the hospital with AHF, current or a history of AF is associated with less dyspnea improvement and higher morbidity and mortality at 30-days, compared to those not in AF. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: NCT00475852.
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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 | 0.003 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".