Impact of mild and moderate aortic stenosis on clinical outcomes in patients with acute heart failure: insights from the RELAX-AHF-2 trial
Bibliographic record
Abstract
Abstract Background Aortic stenosis leads to increased afterload, which may be detrimental in a failing left ventricle and has been associated with increased risk of heart failure hospitalizations and mortality in chronic heart failure. The prevalence and impact of aortic stenosis in acute heart failure is less well described. Purpose We aimed to evaluate the prevalence and prognostic impact of aortic stenosis in a large cohort of patients hospitalized with acute heart failure. Methods All patients from the Relaxin in Acute Heart Failure 2 (RELAX-AHF-2) trial with data available on aortic stenosis severity were included in the present analysis (n = 6241). Patients with severe aortic stenosis were ineligible for RELAX-AHF-2. Baseline characteristics, in-hospital outcomes, and 180-day clinical outcomes were compared between patients with and without aortic stenosis. Results Mild or moderate aortic stenosis was present in 454 (7.3%) patients. Patients with aortic stenosis were older, more often female, had more comorbidities and a higher left ventricular ejection fraction compared to patients without aortic stenosis. Mild or moderate aortic stenosis was associated with a higher risk of cardiovascular mortality or readmission for heart or renal failure (unadjusted Hazard Ratio (HR) 1.32, 95% CI 1.11 – 1.57). This association was maintained when adjusting for age and sex, but not after comprehensive multivariable adjustment (adjusted HR 1.04, 95% CI 0.82 – 1.32). Conclusion The presence of mild or moderate aortic stenosis reflects an increased risk for poor clinical outcome in patients with acute heart failure.Graphical Abstract
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".