Role of Ejection Fraction in Patients at Risk for Advanced Heart Failure: Insights from the HELP-HF Registry
Bibliographic record
Abstract
Abstract Aims Patients with heart failure (HF) with reduced ejection fraction (EF) (HFrEF), mildly reduced EF (HFmrEF), and preserved EF (HFpEF) may all progress to advanced HF, but the impact of EF in the advanced setting is not well established. Our aim was to assess the prognostic impact of EF in patients with at least one ‘I NEED HELP’ marker for advanced HF. Methods and results Patients with HF and at least one high-risk ‘I NEED HELP’ criterion from four centres were included in this analysis. Outcomes were assessed in patients with HFrEF (EF ≤ 40%), HFmrEF (EF 41–49%), and HFpEF (EF ≥ 50%) and with EF analysed as a continuous variable. The prognostic impact of medical therapy for HF in patients with EF < 50% and EF > 50% was also evaluated. All-cause death was the primary endpoint, and cardiovascular death was a secondary endpoint. Among 1149 patients enrolled [mean age 75.1 ± 11.5 years, 67.3% males, 67.6% hospitalized, median follow-up 260 days (inter-quartile range 105–390 days)], HFrEF, HFmrEF, and HFpEF were observed in 699 (60.8%), 122 (10.6%), and 328 (28.6%) patients, and 1 year mortality was 28.3%, 26.2%, and 20.1, respectively (log-rank P = 0.036). As compared with HFrEF patients, HFpEF patients had a lower risk of all-cause death [adjusted hazard ratio (HRadj) 0.67, 95% confidence interval (CI) 0.48–0.94, P = 0.022], whereas no difference was noted for HFmrEF patients. After multivariable adjustment, a lower risk of all-cause death (HRadj for 5% increase 0.94, 95% CI 0.89–0.99, P = 0.017) and cardiovascular death (HRadj for 5% increase 0.94, 95% CI 0.88–1.00, P = 0.049) was observed at higher EF values. Beta-blockers and renin–angiotensin system inhibitors or sacubitril/valsartan were associated with lower mortality in both EF < 50% and EF ≥ 50% groups. Conclusions Among patients with HF and at least one ‘I NEED HELP’ marker for advanced HF, left ventricular EF is still of prognostic value.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".