The association between inflammatory, metabolic, and hepatic fibrosis-related biomarkers and atrial fibrillation in older patients with metabolic dysfunction-associated steatotic liver disease.

OBJECTIVE

This study aims to explore the associations between biomarkers related to inflammation, metabolism, and liver fibrosis and the prevalence of atrial fibrillation(AF) in older patients with metabolic dysfunction-associated steatotic liver disease (MASLD), and to identify potential indicators that could be conveniently applied in epidemiological studies of AF within this population.

METHODS

A total of 2035 older patients with MASLD who underwent physical examinations at Northern Jiangsu People's Hospital in Jiangsu Province, China, from January 2021 to June 2023 were selected and divided into AF and non-AF groups. Least Absolute Shrinkage and Selection Operator(LASSO) regression was used for variable selection, and multivariate logistic regression analysis, restricted cubic spline analysis(RCS), subgroup analysis, and predictive model evaluation tools were employed to investigate the associations between these indicators and the risk of AF in older MASLD patients.

RESULTS

Both LASSO regression and multivariate logistic regression analyses indicated that NAFLD Fibrosis Score(NFS) (OR(95% CI) = 1.924(1.464, 2.558)), Albumin-Bilirubin score(ALBI) (OR (95% CI) = 1.299 (1.156, 1.466)), Fibrosis-4(FIB-4) (OR (95% CI) = 1.385 (1.146, 1.694)), and Monocyte to High-Density Lipoprotein Cholesterol Ratio(MHR)(OR (95% CI) = 1.501 (1.247, 1.809)) are independent risk factors for AF in older patients with MASLD. RCS analysis showed significant non-linear associations between NFS, FIB-4, and MHR and the risk of AF in older MASLD patients (P for nonlinear < 0.05). Subgroup analysis revealed significant interaction effects between diabetes and the AF risk associated with NFS, ALBI, and FIB-4, as well as between sex and the AF risk associated with MHR(P for interaction < 0.05). The variable importance ranking results based on the Boruta algorithm, as well as the Receiver Operating Characteristic (ROC) curve and Decision Curve Analysis (DCA), all indicate that NFS and ALBI have high predictive performance and clinical benefits.

CONCLUSION

NFS and ALBI are significantly positively correlated with the prevalence of AF in older patients with MASLD and can serve as potential epidemiological predictive indicators.