Heart Failure with Mid-Range Ejection Fraction in CHARM: Characteristics, Outcomes and Effect of Candesartan Across the Entire Ejection Fraction Spectrum
Bibliographic record
Abstract
AIMS: We tested the hypothesis that candesartan improves outcomes in heart failure (HF) with mid-range ejection fraction [HFmrEF; ejection fraction (EF) 40-49%]. METHODS AND RESULTS: In 7598 patients enrolled in the CHARM Programme (HF across the spectrum of EF), we assessed characteristics, outcomes and treatment effect of candesartan according to EF. Patients with HFmrEF (n = 1322, 17%) were similar to those with HF with reduced EF (HFrEF; n = 4323, 57%) with respect to some characteristics, and intermediate between HFrEF and HF with preserved EF (HFpEF; n = 1953, 26%) with respect to others. Over a mean follow-up of 2.9 years, the incidence rates for the primary outcome of cardiovascular death or HF hospitalization were 15.9, 8.5 and 8.9 per 100 patient-years in HFrEF, HFmrEF and HFpEF. In adjusted analyses, the rates of the primary outcome declined with increasing EF up to 50%. For treatment effect, the incidence rates for the primary outcome for candesartan vs. placebo were 14.4 vs. 17.5 per 100 patient-years in HFrEF [hazard ratio (HR) 0.82, 95% confidence interval (CI) 0.75-0.91; P < 0.001], 7.4 vs. 9.7 per 100 patient-years in HFmrEF (HR 0.76, 95% CI 0.61-0.96; P = 0.02), and 8.6 vs. 9.1 per 100 patient-years in HFpEF (HR 0.95, 95% CI 0.79-1.14; P = 0.57). For recurrent HF hospitalization, the incidence rate ratios were 0.68 in HFrEF (95% CI 0.58-0.80; P < 0.001), 0.48 in HFmrEF (95% CI 0.33-0.70; P < 0.001), and 0.78 in HFpEF (95% CI 0.59-1.03; P = 0.08). With EF as a continuous spline variable, candesartan significantly reduced the primary outcome until EF well over 50% and recurrent HF hospitalizations until EF well over 60%. CONCLUSION: Candesartan improved outcomes in HFmrEF to a similar degree as in HFrEF. ClinicalTrials.gov: CHARM Alternative NCT00634400, CHARM Added NCT00634309, CHARM Preserved NCT00634712.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".