Bo Yang ¹ Mingsu Gong ¹ Xiaojie Zhu ² Yang Luo ¹ Ruiqiu Li ¹ Hai Meng ² Yuhan Wang ^2*

• ¹ Department of Gastroenterology and Hepatology, Guizhou Aerospace Hospital, Zunyi, Guizhou Province, China
• ² Department of Gastroenterology and Hepatology, Binhai County People's Hospital, Yancheng, China

Introduction: Non-alcoholic fatty liver disease (NAFLD) is a leading cause of chronic liver disease worldwide, with liver fibrosis (LF) being a crucial pathological feature in the progression of NAFLD.Insulin resistance (IR) is believed to play an important role in the pathogenesis of NAFLD and the development of LF. This study aims to explore the relationship between various IR indicators and LF in patients with NAFLD.Methods: This study utilized data from the National Health and Nutrition Examination Survey 2017-2020 cycles. Liver steatosis and fibrosis were assessed using liver ultrasound transient elastography.To assess the association between multiple IR indicators and LF, the study methodology included univariate and multivariate logistic regression, as well as restricted cubic spline (RCS) analysis. Subsequently, we used multivariate logistic regression to develop and validate a predictive model for LF, and evaluated the model's performance using the area under the curve (AUC) and calibration curve.Results: A total of 904 patients were included in the final analysis. Among these NAFLD patients, 153 (16.92%) had LF. Compared to non-LF patients, LF patients had significantly higher body mass index (BMI), waist circumference (WC), alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyl transferase (GGT), HbA1c, and fasting blood glucose (FBG) levels (all p < 0.05). Analysis of IR indicators showed that LF patients had significantly higher levels of TyG, TyG-WHtR, TyG-BMI, TyG-WC, TyG-GGT, METS-IR, and HOMA-IR (all p < 0.05). After adjusting for covariates, TyG-WHtR remained an independent risk factor (OR=2.69; 95% CI: 2.08-3.47), indicating a strong correlation with LF. The developed nomogram, incorporating AST, TyG, TyG-BMI, and diabetes, showed an AUC of 0.809 (95% CI: 0.771-0.847), indicating good predictive performance for LF in NAFLD patients. Conclusions: This study confirms that a significant association between various IR and LF in NAFLD patients, and the developed nomogram provides a practical tool for early risk assessment.These findings underscore the clinical value of incorporating IR indices into routine practice to identify high-risk patients, enabling timely interventions to prevent fibrosis progression and improve outcomes.