Atrial fibrillation identification in patients with non-alcoholic fatty liver disease: a machine learning model based on immune-inflammatory markers.

ABSTRACT:

Background

The global prevalence of non-alcoholic fatty liver disease (NAFLD) is continuously rising, making it a significant public health concern. Recent studies indicate that NAFLD is independently associated with an increased risk of atrial fibrillation (AF), potentially mediated by chronic inflammation and immune responses. However, there is currently a lack of AF risk identification tools specifically for the NAFLD population. This study aimed to identify AF and model its association with immune-inflammatory markers in NAFLD patients.

Methods

This study enrolled 723 patients with ultrasound-confirmed NAFLD (AF group: n = 203, non-AF group: n = 520). Clinical data were collected, and 10 immune-inflammatory markers (including Systemic Immune-inflammation Index (SII), Sys

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC12837364 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature