Research progress on the biomarkers of sepsis-induced cardiomyopathy.
10.3760/cma.j.cn121430-20241112-00924
- Author:
Hongbin LI
1
;
Bei HU
1
Author Information
1. Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou 510080, Guangdong, China.
- Publication Type:English Abstract
- MeSH:
Humans;
Biomarkers/blood*;
Cardiomyopathies/etiology*;
Sepsis/diagnosis*;
MicroRNAs/blood*;
Prognosis;
Fatty Acid-Binding Proteins/blood*
- From:
Chinese Critical Care Medicine
2025;37(6):599-604
- CountryChina
- Language:Chinese
-
Abstract:
Sepsis constitutes one of the principal causes of death globally, and the mortality rate of patients complicated with sepsis-induced cardiomyopathy (SIC) surges by over 50%. Early identification of patients with sepsis, particularly SIC, and implementing clinical intervention are vital measures to reduce the mortality. In recent years, biomarkers for the diagnosis and prognosis of SIC have emerged rapidly. Among classical myocardial injury biomarkers, cardiac troponin (cTn), brain natriuretic peptide (BNP), and soluble growth stimulation gene 2 protein (sST2) have predictive value for the prognosis of SIC. Meanwhile, heart-type fatty acid-binding protein (h-FABP) possess relatively high value in diagnosis. Moreover, plasma metabolites, microRNA (miRNA), as well as recently identified markers related to sepsis or cardiovascular diseases also demonstrate outstanding predictive value in both the diagnosis and prognosis of SIC. For instance, exosomal miR-150-5p, blood miR-155, blood miR-378a-3p, blood miR-21-3p, blood miR-233, blood miR-23b, blood miR-135, lipocalin (LCN), heme oxygenase-1 (HO-1), fibroblast growth factor-21 (FGF-21), and growth differentiation factor-15 (GDF-15) show varying degrees of predictive value when it comes to diagnosing SIC. S100A8/A9 protein, triglyceride-glucose (TyG) index, angiotensinogen II (Ang II) and lactoferrin are correlated with the prognosis of SIC. Meanwhile, it has been discovered that the combination of multiple biomarkers outperforms a single biomarker, and certain combinations exhibit superior diagnostic performance. However, most of these studies use single-center clinical data, which has certain limitations and still calls for more high-quality evidence support. Therefore, identifying biomarker combinations that are supported by high-quality evidence, have bedside application potential, and possess high sensitivity and specificity is of crucial importance for the prevention, diagnosis, and treatment of SIC. This review is carried out on the current articles that report biomarkers with predictive value and the diagnosis and prediction of multiple biomarkers in combination, in the hope of continuously optimizing the diagnostic strategy for the specific identification of early SIC.
