Abstract 14185: Heart Failure Occurring at any Time During Hospitalization is Associated with Higher Mortality in Non-ST Elevation-Acute Coronary Syndromes
Bibliographic record
Abstract
Background: Heart failure (HF) is a frequent complication of ACS and is associated with poor prognosis. However, most studies only included patients with ST elevation myocardial Infarction (STEMI). Thus, we aim to describe the occurrence and timing of HF complicating non-ST elevation acute coronary syndrome (NSTE-ACS), identify predictors of admission and in-hospital new onset HF, and assess the association of HF with post-discharge mortality at 30 day. Methods: We examined combined patient-level data from 46,519 NSTE-ACS patients enrolled in 7 clinical trials: GUSTO IIb, PURSUIT, PARAGON A, PARAGON B, ESSENCE, SYNERGY and EARLY-ACS. Patients with cardiogenic shock or Killip class IV were excluded. Admission HF was defined as Killip Class II or III and patients with in-hospital HF had no admission HF and had a complication of HF or pulmonary edema prior discharge. Logistic regression models were performed to assess predictors of HF and the association of 30-day mortality after hospital discharge with HF, adjusting for baseline variables. Results: From the NSTE-ACS patients, 4,910 (10.5%) had HF on admission, 1,194 (2.6%) developed HF during hospitalization, and 40,415 (86.9%) had no HF at any time. Patients presenting with HF or developing HF during hospitalization tended to be older and more likely female compared with those with no heart failure. Increased age, female sex, current smoker, higher HR, DM, lower SBP, hypertension, prior MI, and ST changes were strongly associated with HF. Patients with HF on admission and during hospitalization had higher risk of post-discharge death at 30 days when compared with patients without heart failure (Table). Conclusion: In this large patient population of NSTE-ACS, occurrence of heart failure at any time was associated with increased risk of death within 30 days of hospital discharge. Research targeting new strategies to prevent and to manage HF after NSTE-ACS is needed. Table. Post-discharge 30-day mortality
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.007 | 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".