Pharmacological Treatment of Heart Failure: Recent Advances
Bibliographic record
Abstract
BACKGROUND: Heart failure is a clinical condition with high mortality and morbidity that occurs when the heart is unable to pump enough blood to meet the metabolic demands of the body. The pharmacological management of heart failure has been revolutionized over the past decade with novel treatments. OBJECTIVE: The aim of the review is to highlight the recent pharmacological advances in the management of heart failure. RESULTS: Sodium-glucose cotransporter-2 inhibitor (SGLT2i), iron carboxymaltose, finerenone, omecamtiv mecarbil, and vericiguat have been shown to reduce hospitalization for heart failure. However, only SGLT2i, vericiguat, and omecamtiv mecarbil have been shown to reduce cardiovascular death. Finerenone has been shown to reduce cardiovascular events and renal adverse outcomes in patients with diabetes and kidney disease. Currently, only SGLT2i has been studied in patients beyond the heart failure with reduced ejection fraction population. CONCLUSION: The current quadruple therapy in the treatment of heart failure has demonstrated a reduction in the hospitalization of patients and a decrease in mortality associated with the condition. Individualized heart failure therapy research have shown some benefit in select heart failure patients. Further research on novel therapies will help improve heart failure patient outcomes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".