The Role of Epicardial Fat Thickness and B-type Natriuretic Peptide (BNP)/N-terminal Pro B-type Natriuretic Peptide (NT-proBNP) in Heart Failure Risk Stratification: A Systematic Review
Bibliographic record
Abstract
Heart failure (HF) remains a global health challenge, necessitating improved risk stratification tools. This systematic review evaluates the combined role of epicardial fat thickness (EFT) and B-type natriuretic peptide (BNP)/N-terminal pro B-type natriuretic peptide (NT-proBNP) in HF risk stratification, examining their pathophysiological interplay and clinical utility across diverse populations, including a wide age range, various comorbidities (e.g., obesity, diabetes, and systemic sclerosis), and geographic regions. EFT, a measurable marker of epicardial adipose tissue (EAT) located between the myocardium and visceral pericardium, was evaluated alongside BNP/NT-proBNP, established biomarkers of cardiac stress. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses 2020 guidelines, 12 case-control studies were included after screening 192 records from PubMed/MEDLINE, Embase, Scopus, Web of Science, and Cochrane Library. Studies assessed EFT and BNP/NT-proBNP in HF or at-risk populations. Methodological quality was appraised using the Newcastle-Ottawa Scale (NOS). EFT consistently correlated with elevated BNP/NT-proBNP, though patterns differed by HF phenotype. In HF with reduced ejection fraction (HFrEF), NT-proBNP associated more strongly with muscle loss than adiposity, while in HF with preserved ejection fraction (HFpEF), EFT was linked to metabolic comorbidities and inflammatory markers. Paradoxically, lower EFT predicted worse outcomes in nonischemic cardiomyopathy (NICMP), potentially reflecting disease-related fat depletion or cachexia; this finding underscores the need for phenotype-specific interpretation of EFT in risk stratification. Mechanistically, EAT contributed to myocardial remodeling via adipokine secretion and inflammatory signaling. Four studies had a low risk of bias (NOS ≥ 8), while one showed a high risk. The combined assessment of EFT and BNP/NT-proBNP offers complementary prognostic insights, EFT capturing subclinical inflammation and adiposity-related remodeling, while BNP/NT-proBNP reflects myocyte stress, potentially guiding personalized treatment decisions, including closer monitoring of HFpEF patients with elevated EFT and early nutritional or anti-inflammatory interventions in those with muscle loss and elevated NT-proBNP. Inclusion criteria encompassed adult populations with HF or related conditions, with exclusion of reviews, case reports, and non-English articles, supporting the methodological rigor of this synthesis. Standardized EFT measurement and targeted EAT-modulating therapies warrant further investigation.
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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 | 0.007 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".