Influence of Ejection Fraction on Cardiovascular Outcomes in a Broad Spectrum of Heart Failure Patients
Bibliographic record
Abstract
BACKGROUND: Left ventricular function is a principal determinant of cardiovascular risk in patients with heart failure. The growing number of patients with preserved systolic function heart failure underscores the importance of understanding the relationship between ejection fraction and risk. METHODS AND RESULTS: We studied 7599 patients with a broad spectrum of symptomatic heart failure enrolled in the Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) Program. All patients were randomized to candesartan at a target dose of 32 mg once daily or matching placebo and followed up for a median of 38 months. We related left ventricular ejection fraction (LVEF), measured before randomization at the sites, to cardiovascular outcomes and causes of death. Mean LVEF in patients enrolled in CHARM was 38.8+/-14.9% (median LVEF 36%). Patients with lower LVEF tended to have higher baseline New York Heart Association class. The hazard ratio for all-cause mortality increased by 39% for every 10% reduction in ejection fraction below 45% (hazard ratio 1.39, 95% CI 1.32 to 1.46), with adjustment for baseline covariates. All-cause mortality, cardiovascular death, and all components of cardiovascular death declined with increasing ejection fraction until an ejection fraction of 45%, after which the risk of these outcomes remained relatively stable with increasing LVEF. The absolute change in rate per 100 patient-years for each 10% reduction in LVEF was greatest for sudden death and heart failure-related death. The effect of candesartan in reducing cardiovascular outcomes was consistent across LVEF categories. CONCLUSIONS: LVEF is a powerful predictor of cardiovascular outcome in heart failure patients across a broad spectrum of ventricular function. Nevertheless, once elevated to a range above 45%, ejection fraction does not further contribute to assessment of cardiovascular risk in heart failure patients.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".