Inflammation in heart failure: pathophysiology and therapeutic strategies
Bibliographic record
Abstract
A role for inflammation in the development and progression of heart failure (HF) has been proposed for decades. Multiple studies have demonstrated the potential involvement of several groups of cytokines and chemokines in acute and chronic HF, though targeting these pathways in early therapeutic trials have produced mixed results. These studies served to highlight the complexity and nuances of how pro-inflammatory pathways contribute to the pathogenesis of HF. More recent investigations have highlighted how inflammation may play distinct roles based on HF syndrome phenotypes, findings that may guide the development of novel therapies. In this review, we propose a contemporary update on the role of inflammation mediated by the innate and adaptive immune systems with HF, highlighting differences that exist across the ejection fraction spectrum. This will specifically be looked at through the lens of established and novel biomarkers of inflammation. Subsequently, we review how improvements in inflammatory pathways may mediate clinical benefits of existing guideline-directed medical therapies for HF, as well as future therapies in the pipeline targeting HF and inflammation.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| 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".