Challenges in heart failure ESC Guidelines implementation - insights from a real world registry
Bibliographic record
Abstract
Abstract Background ARNIs and, more recently, SGLT2i inhibitors have become part of the cornerstone of the treatment of heart failure garnering in the latest HF guidelines a Class I recommendation for patients with heart failure and reduced ejection fraction (≤40%). Alongside with renin-angiotensin-aldosterone system inhibitors and beta-blockers, they are recognized as "disease-modifying" drugs which should be promptly initiated in HF patients. Despite the evident benefits demonstrated by these drugs, their utilization in clinical practice remains limited. Purpose The aim of this study was to evaluate the implementation and the uptitration of heart failure "disease-modifying" drugs in the real world, as well as the eligibility rate of the study population for these treatments. Methods Our data derive from an observational study enrolling 165 consecutive ambulatory patients with heart failure regardless of ejection fraction. The study comprises several phases: 1) a T0 phase involving a retrospective analysis of several anamnestic, clinical, laboratory and echocardiographic parameters collected within one to seven months before study initiation; 2) a T1 phase prospectively evaluating the same patient characteristics over a period extending from the fifth to the seventh month following specific educational initiatives regarding HF-GMDT implementation. Results 165 consecutive patients were enrolled in our center during phase T0:90% of them were in treatment with a beta-blocker; 73% were receiving an ARNI/ACEi/ARB and 62% an MRA with main causes of underprescription in HFrEF patients being kidney dysfunction, hyperkalaemia, hypotension and bradycardia; 85% of our HFrEF patients were in treatment with SGLT2i and recurrent urinary tract infections and kidney dysfunction were the main reasons for underprescription. Only a small portion of our patients wasn't receiving disease modifying therapies because of unknown reasons (0,04% - 0,2% and 0,05% respectively for ACE/ARNI/ARB - MRA and BB). Nevertheless target doses were attained in a minority of the patients (29% -10% and 36% respectively for ARNI - MRA and BB). Conclusion While a satisfactory proportion of our patients were on heart failure medications, the majority of them did not attain target dosages, suggesting a potential gap between guideline recommendations and clinical practice. The prospective phase of our study (T1) holds the promise of assessing whether the implementation of specific educational initiatives might contribute to heightened awareness regarding the efficacy and safety of these "disease modifiers" therapies, thus facilitating their integration into clinical practice.
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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 | 0.032 | 0.077 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".