Abstract
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is linked to a higher risk of cardiovascular disease, particularly chronic coronary syndrome (CCS). However, reliable biomarkers for early CCS risk stratification in NAFLD patients remain lacking. This study aims to assess the pan-immune-inflammation value (PIV) and atherogenic index of plasma (AIP) for CCS in NAFLD patients and to construct a practical tool for personalized risk assessment. METHODS: This retrospective study included 459 NAFLD patients undergoing coronary angiography. Least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression were used to discover independent risk variables for CCS. A nomogram was constructed to quantify CCS risk. Model performance was evaluated by calibration curves, concordance index, and decision curve analysis (DCA). Trend tests assessed the relationship between PIV, AIP quartiles, and CCS risk, while quantile regression analyzed their associations with coronary lesion severity (Gensini scores). RESULTS: Eight independent variables were identified. Elevated lnPIV (OR, 2.195; 95% CI, 1.564-3.125; P< 0.001) and AIP (OR, 4.147; 95% CI, 1.770-10.095; P< 0.001) were strongly associated with CCS. The nomogram demonstrated good discrimination (C-index = 0.782) and calibration. Trend tests revealed a significant positive correlation between lnPIV/AIP quartiles and CCS risk (P for trend< 0.05). Quantile regression further indicated that lnPIV and AIP positively correlated with higher Gensini scores. CONCLUSIONS: lnPIV and AIP are independent biomarkers for CCS in NAFLD patients. The nomogram provides a valuable tool for CCS risk stratification and personalized management.