Patients with higher values had a significantly higher prevalence of and liver .
Higher TyG-BMI values are associated with increased prevalence of non-alcoholic steatohepatitis (NASH) and significant fibrosis.
TyG-BMI serves as an independent predictor for NASH, at-risk NASH, and various stages of liver fibrosis.
Receiver operating characteristic (ROC) curve analysis indicates TyG-BMI has excellent predictive ability for liver conditions in patients with NAFLD.
Validation of the results in a separate cohort supports the findings regarding TyG-BMI's predictive capabilities.
Multivariate models incorporating TyG-BMI and elastography metrics show elevated diagnostic performance for identifying liver disease.
Simplified
OBJECTIVE: The objective of this study was to thoroughly investigate the clinical value of triglyceride glucose-body mass index () in patients diagnosed with non-alcoholic fatty liver disease (NAFLD). Specifically, we aimed to determine its association with non-alcoholic steatohepatitis () and the progression of liver .
METHODS: The study included 393 patients diagnosed with NAFLD after liver biopsy. The patients were divided into two distinct cohorts: a training cohort ( = 320) and a validation cohort ( = 73). The training cohort was further divided into four groups based on TyG-BMI quartiles. The clinical characteristics of the patients in each group were compared in detail, and the association between TyG-BMI and NASH, NAFLD Activity Score (NAS) ≥ 4, at-risk NASH, significant fibrosis, advanced fibrosis, and cirrhosis was analyzed using multiple models. Additionally, we generated receiver operating characteristic (ROC) curves to evaluate the predictive ability of TyG-BMI for NASH and fibrosis staging in patients with NAFLD. N N
RESULTS: Patients with higher TyG-BMI values had a significantly higher prevalence of NASH, NAS ≥ 4, at-risk NASH, significant fibrosis, advanced fibrosis, and cirrhosis (all < .05). TyG-BMI was an independent predictor of these diseases in both unadjusted and adjusted models (all < .05). ROC curve analysis further revealed the excellent performance of TyG-BMI in predicting NASH, NAS ≥ 4, at-risk NASH, significant fibrosis, advanced fibrosis, and cirrhosis. The validation cohort yielded analogous results. Furthermore, we constructed three multivariate models of TyG-BMI in conjunction with elastography metrics, which demonstrated elevated diagnostic AUC values of 0.782, 0.792, 0.794, 0.785, 0.834, and 0.845, respectively. p p
CONCLUSION: This study confirms a significant association between insulin resistance and NAFLD, including at-risk NASH and fibrosis staging, as assessed using the TyG-BMI index. TyG-BMI and its associated multivariate models can be valuable noninvasive indicators for NAFLD diagnosis, risk stratification, and disease course monitoring.
Key numbers
4.82
Increase in Disease Prevalence
Odds ratio for in the highest quartile compared to the lowest.
0.650
AUC for Prediction
Area under the ROC curve for predicting .
0.845
AUC for Advanced Prediction
AUC for the -LSM-CAP model predicting advanced .
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