Impact of hospitalization for acute coronary events on subsequent mortality in patients with chronic heart failure
Bibliographic record
Abstract
AIMS: We explored the impact of having a hospital admission for an acute coronary syndrome (ACS) on the subsequent prognosis among patients with chronic heart failure (CHF). METHODS AND RESULTS: A total of 7599 patients with CHF, New York Heart Association Classes II-IV, were randomly assigned to candesartan or placebo. We assessed the risk of death after a first ACS using time-updated Cox proportional hazard models adjusted for baseline predictors. During a mean follow-up of 3.3 years, 1174 patients experienced at least one ACS. Myocardial infarction (MI) was the first ACS in 442 subjects and unstable angina (UA) in 732. After these events, 219 (49.5%) and 167 (22.8%) patients died during follow-up. The early risk of death was more pronounced after MI: 30.2% died within 30 days compared with 3.6% after UA. After an ACS event, the risk of death declined steadily over time, although 18 months after an MI the risk was still twice that of patients without an ACS. CONCLUSION: Patients with CHF, who develop an ACS, have markedly increased subsequent mortality, particularly in the early phase after an MI.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".