Elegibility for Sacubitril/Valsartan in italian clinical practice: insights from the OPTIMA-HF registry
Bibliographic record
Abstract
Abstract Background/Introduction Guidelines strongly recommend patients with heart failure with reduced ejection fraction (HFrEF) be treated with multiple medications proven to improve clinical outcomes, as tolerated. Among them, angiotensin receptor blocker/neprylisin inhibitor (ARNi) are the foundation of neuro-hormonal blockade in patients with HFrEF, however the degree to which gaps in this medication use and dosing persist in outpatient practice is unclear. Purpose To assess the proportion of patients with HFrEF who are eligible for ARNi based on the PARADIGM-HF trial criteria and the association between eligibility and baseline characteristics. Methods The OPTIMA-HF (Optimization of Therapy in the Italian Management of Heart Failure) registry included outpatients in Italy with chronic HFrEF receiving at least 1 oral medication for management of HF. Patients were characterized by baseline use and dose of angiotensin-converting enzyme inhibitor (ACEI)/angiotensin II receptor blocker (ARB)/ARNI, beta-blocker, mineralocorticoid receptor antagonist (MRA) and sodium glucose co-transporter II inhibitor (SGLT2i). Patient-level factors associated with medication use were examined. Results Outpatients with HFrEF from 29 ambulatory cardiology practices and university hospitals in the OPTIMA-HF registry recruited between January 2022 and September 2023 were included. Of 1291 patients, 1018 (79%) met the PARADIGM-HF criteria and 949 of them (93%) were on ARNi. Of the enrolled patients, 342 (27%) were not on ARNi, however only 129 (38%) did not met the PARADIGM-HF inclusion criteria for ARNi prescription. Reasons for not meeting PARADIGM-HF criteria were no beta-blocker background therapy (22%), hyperkalemia (4%), hypotension (15%), chronic kidney disease (65%) and hyperkalemia (79%). In a logistic regression model not being on ARNi was associated with older age, chronic kidney disease, not being on cardiac resynchronization therapy, lower systolic blood pressure, lower BMI, and higher PAPs (Figure), representing the picture of a more fragile patient net of compliance with the PARADIGM-HF criteria. Conclusions Among outpatients with HFrEF in the OPTIMA-HF Registry, 79% met the PARADIGM-HF criteria. Strategies to improve guideline-directed use of HFrEF medications remain urgently needed, and these findings may inform targeted approaches to optimize outpatient medical therapy.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".