Guideline-Directed Medical Therapy in Severe Heart Failure with Reduced Ejection Fraction: An Analysis from the HELP-HF Registry
Bibliographic record
Abstract
AIM: Persistent symptoms despite guideline-directed medical therapy (GDMT) and poor tolerance of GDMT are hallmarks of patients with advanced heart failure (HF) with reduced ejection fraction (HFrEF). However, real-world data on GDMT use, dose, and prognostic implications are lacking. METHODS AND RESULTS: We included 699 consecutive patients with HFrEF and at least one 'I NEED HELP' marker for advanced HF enrolled in a multicentre registry. Beta-blockers (BB) were administered to 574 (82%) patients, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers or angiotensin receptor-neprilysin inhibitors (ACEi/ARB/ARNI) were administered to 381 (55%) patients and 416 (60%) received mineralocorticoid receptor antagonists (MRA). Overall, ≥50% of target doses were reached in 41%, 22%, and 56% of the patients on BB, ACEi/ARB/ARNI and MRA, respectively. Hypotension, bradycardia, kidney dysfunction and hyperkalaemia were the main causes of underprescription and/or underdosing, but up to a half of the patients did not receive target doses for unknown causes (51%, 41%, and 55% for BB, ACEi/ARB/ARNI and MRA, respectively). The proportions of patients receiving BB and ACEi/ARB/ARNI were lower among those fulfilling the 2018 HFA-ESC criteria for advanced HF. Treatment with BB and ACEi/ARB/ARNI were associated with a lower risk of death or HF hospitalizations (adjusted hazard ratio [HR] 0.63, 95% confidence interval [CI] 0.48-0.84, and HR 0.74, 95% CI 0.58-0.95, respectively). CONCLUSIONS: In a large, real-world, contemporary cohort of patients with severe HFrEF, with at least one marker for advanced HF, prescription and uptitration of GDMT remained limited. A significant proportion of patients were undertreated due to unknown reasons suggesting a potential role of clinical inertia either by the prescribing healthcare professional or by the patient. Treatment with BB and ACEi/ARB/ARNI was associated with lower mortality/morbidity.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".