Comparison of Outcomes After Hospitalization for Worsening Heart Failure, Myocardial Infarction, and Stroke in Patients with Heart Failure and Reduced and Preserved Ejection Fraction
Bibliographic record
Abstract
AIMS: To investigate the prognostic significance of hospitalization for worsening heart failure (WHF), myocardial infarction (MI), and stroke in patients with chronic heart failure (HF). METHODS AND RESULTS: We studied 5011 patients with HF and reduced EF (HF-REF) in the CORONA trial and 4128 patients with HF and preserved EF (HF-PEF) in the I-Preserve trial. Adjusted hazard ratios (HRs) for death were estimated for 0-30 days and ≥31 days after first post-randomization WHF, MI, or stroke used as a time-dependent variable, compared with patients with none of these events. In CORONA, 1616 patients (32%) had post-randomization first events (1223 WHF, 216 MI, 177 stroke), and the adjusted HR for mortality ≤30 days after an event was: WHF 7.21 [95% confidence interval (CI) 2.05-25.40], MI 23.08 (95% CI 6.44-82.71), and stroke 32.15 (95% CI 8.93-115.83). The HR for mortality at >30 days was: WHF 3.62 (95% CI 3.11-4.21), MI 4.41 (95% CI 3.23-6.02), and stroke 3.19 (95% CI 2.21-4.61). In I-Preserve, 896 patients (22%) experienced a post-randomization event (638 WHF, 111 MI, 147 stroke). The HR for mortality ≤30 days was WHF 31.77 (95% CI 7.60-132.81), MI 154.77 (95% CI 34.21-700.17), and stroke 223.30 (95% CI 51.42-969.78); for >30 days it was WHF 3.36 (95% CI 2.79-4.05), MI 3.29 (95% CI 2.14-5.06), and stroke 5.13 (95% CI 3.61-7.29). CONCLUSIONS: In patients with both HF-REF and HF-PEF, hospitalization for WHF was associated with high early and late mortality. The early relative risk of death was not as great as following MI or stroke, but the longer term relative risk of death was similar following all three types of event. Numerically, more deaths occurred following WHF because it was a much more common event.
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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 | 0.001 | 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".