P5537Clinical outcomes, mortality, and causes of death in patients with NSTEMI according to heart failure at admission: insights from a large contemporary revascularization trial
Bibliographic record
Abstract
Background: Patients with non–ST-elevation myocardial infarction (NSTEMI) and heart failure (HF) are recognized as a high-risk subgroup; mortality in patients without HF is low. In historical cohorts, revascularization has been underused in patients with HF. Outcomes of these patients in the current era of widespread revascularization are unknown. Purpose: We describe the clinical characteristics, outcomes, and causes of death in patients according to HF status in a large NSTEMI population scheduled to undergo systematic coronary angiography (CAG). Methods: The TAO (Treatment of Acute Coronary Syndrome with Otamixaban) trial randomized NSTEMI patients with systematic CAG scheduled within 72 h to heparin + eptifibatide vs otamixaban. In a post hoc analysis, patients were categorized according to presence or absence of HF (Killip grade ≥2) at admission. Events were adjudicated and causes of death were categorized. Results: A total of 13,184 NSTEMI patients were enrolled, of whom 944 (7.2%) had HF at admission (Killip 2 in 85.1% of cases). Use of invasive procedures was, per protocol, almost universal in both HF and non HF patients (98.3% vs 99.3% [with vs without HF] p<0.0003), with more frequent coronary revascularization (PCI or CABG) in no HF group (63.1% vs 81.1%, p<0.001). At day 30, death occurred in 57/944 (6%) patients with HF and 156/12228 patients (1.3%) without HF. Cardiovascular death (CV) was the dominant cause of death (78.8% vs 78.4%, p=0.94) and the distribution of the causes of CV death including worsening HF (22.6% vs 26%, p=0.65) and no CV death did not differ according to baseline HF status. At six months follow-up, mortality remained higher in patients presenting with HF (9.5% vs 2.1%, p<0.0001). The composite ischemic criteria of CV death, MI, stent thrombosis, and stroke at day 30 was significantly higher in patients with HF (12.2% vs 7.1%, p<0.0001).
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".