Liver Function Tests in Patients with Acute Heart Failure and Associated Outcomes: Insights from ASCEND-HF
Bibliographic record
Abstract
AIMS: We aimed to characterize abnormal liver function tests in patients with heart failure (HF), as they are commonly encountered yet poorly defined. METHODS AND RESULTS: We used data from ASCEND-HF (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) to characterize associations with baseline liver function tests (LFTs). Each LFT was analysed as both a continuous and dichotomous variable [normal vs. abnormal; bilirubin >1.0 mg/dL; aspartate aminotransferase (AST) and alanine aminotransferase (ALT) >35 mmol/L]. Logistic regression assessed the association of LFTs and 30-day all-cause mortality and HF rehospitalization, and Cox proportional hazards assessed the association with 180-day all-cause mortality among patients alive at a 30-day landmark. In ASCEND-HF, 4228 (59%) had complete admission LFT data. Of these, 42% had abnormal bilirubin, 22% had abnormal ALT, and 30% had abnormal AST. Patients with abnormal LFTs were younger, had lower body mass index, and lower left ventricular ejection fraction. In multivariable models, increased total bilirubin was associated with increased 30-day mortality or HF rehospitalization [hazard ratio (HR) 1.17 per 1 mg/dL increase, 95% confidence interval (CI) 1.04, 1.32; P = 0.012], but not with an increase in 180-day mortality (HR 1.10, 95% CI 0.97, 1.25; P = 0.13) per 1 mg/dl increase. Compared with normal bilirubin levels, abnormal bilirubin was associated with increased 30-day mortality or HF rehospitalization (HR 1.24, 95% CI 1.00, 1.54; P = 0.048) and 180-day mortality (HR 1.32, 95% CI 1.08, 1.62; P = 0.007). We found no association with AST or ALT and outcomes. CONCLUSION: Greater than 40% of patients hospitalized with acute HF had abnormal LFTs. After multivariable adjustment, only elevated bilirubin was independently associated with worse clinical outcomes and may represent an important prognostic variable.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".