Contemporary Drug Treatment of Advanced Heart Failure with Reduced Ejection Fraction
Bibliographic record
Abstract
The introduction of multiple new pharmacological agents over the past three decades in the field of heart failure with reduced ejection fraction (HFrEF) has led to reduced rates of mortality and hospitalizations, and consequently the prevalence of HFrEF has increased, and up to 10% of patients progress to more advanced stages, characterized by high rates of mortality, hospitalizations, and poor quality of life. Advanced HFrEF patients often show persistent or progressive signs of severe HF symptoms corresponding to New York Heart Association class III or IV despite being on optimal medical, surgical, and device therapies. However, a subpopulation of patients with advanced HF, those with the most advanced stages of disease, were often insufficiently represented in the major trials demonstrating efficacy and tolerability of the drugs used in HFrEF due to exclusion criteria such as low BP and kidney dysfunction. Consequently, the results of many landmark trials cannot necessarily be transferred to patients with the most advanced stages of HFrEF. Thus, the efficacy and tolerability of guideline-directed medical therapies in patients with the most advanced stages of HFrEF often remain unsettled, and this knowledge is of crucial importance in the planning and timing of consideration for referral for advanced therapies. This review discusses the evidence regarding the use of contemporary drugs in the advanced HFrEF population, covering components such as guideline HFrEF drugs, diuretics, inotropes, and the use of HFrEF drugs in LVAD recipients, and provides suggestions on how to manage guideline-directed therapy in this patient group.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".