The Use of Metabolomes in Risk Stratification of Patients with Heart Failure: A Scoping Review

Heart failure (HF) is associated with substantial morbidity and mortality. Metabolic abnormalities are increasingly recognized as integral to HF pathophysiology and may provide incremental value for phenotyping and prediction of outcomes. However, a comprehensive synthesis of metabolic alterations and their prognostic implications remains limited. This scoping review aimed to map metabolic changes in HF, describe analytical methods, and evaluate their diagnostic and prognostic relevance for clinical risk assessment.

We systematically searched PubMed, Scopus, Web of Science, Cochrane Central, and grey literature from January 2010 to December 2024 to identify studies evaluating metabolic profiling in patients with HF. Two independent reviewers screened studies using predefined inclusion criteria and data were extracted using a customized charting form. Discrepancies were resolved by consensus or a third reviewer. We reported and synthesized findings narratively in accordance with scoping review methodology.

Seventy-two studies (66 observational and 6 randomized) were included, encompassing HF phenotypes including HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF), and HF with preserved ejection fraction (HFpEF). The analytical approaches included mass spectrometry and nuclear magnetic resonance (¹H-NMR) platforms. The main metabolite classes that demonstrated prognostic significance were amino acids, acylcarnitines, and lipids, and gut-derived metabolites, which were associated with mortality, HF hospitalization, or disease progression. Several studies reported incremental prognostic value beyond conventional biomarker; however, most were exploratory, with modest sample sizes, limited external validation, and heterogeneous methodologies.

Metabolomic profiling identifies biologically relevant alterations predicted worse clinical outcomes in HF and may complement existing risk assessment strategies. Nevertheless, standardized workflows and large prospective validation studies are required before clinical implementation can be considered.