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Predictive value of triglyceride glucose index in non-obese non-alcoholic fatty liver disease
Xiaopeng Zhu1, Fang Sun1, Xia Gao1
1Department of Health Management, Daping Hospital, Army Medical University, Chongqing, Chongqing, China.
Objectives:
A large number of patients with non-obese non-alcoholic fatty liver disease (NAFLD) in China remain undiagnosed and untreated due to insufficient awareness and ineffective pharmacotherapy. Therefore, a convenient, predictive marker and diagnostic tools are imperative. This study aimed to investigate the ability of the triglyceride glucose index (TyG) in predicting non-obese NAFLD.
Design:
An observational cross-sectional study.
Setting:
Department of Health Management, large urban academic medical centre and DRYAD database data.
Participants:
This study included 456 patients with non-obese NAFLD and matched 456 non-fatty liver controls according to age, sex and body mass index (BMI).
Primary And Secondary Outcome Measures:
The receiver operating characteristic (ROC) curve was used to evaluate the predictive role of the TyG index in non-obese NAFLD. Based on the TyG index, a clinical prediction model for non-obese NAFLD was constructed, then the prediction model was verified by the DRYAD database (n=11 562).
Results:
TyG in non-obese NAFLD was higher than that in controls (9.00 (8.66-9.40) vs 8.46 (8.10-8.83), p<0.001). Logistic regression analysis showed that TyG was an independent risk factor for non-obese NAFLD (OR=9.03, 95% CI: 5.46 to 14.94, p<0.001). ROC analysis showed that the area under the curve (AUC) was 0.78, the sensitivity was 82.5%, the specificity was 60.5%. Based on the TyG index, sex, age and BMI, the AUC of the predictive model for non-obese NAFLD was 0.78 (95% CI: 0.75 to 0.81, p<0.001). Using the DRYAD database to verify the prediction model, the AUC of the verification group was 0.85 (95% CI: 0.84 to 0.86, p<0.001).
Conclusions:
The high level of the TyG may be an independent risk factor for non-obese NAFLD. The prediction model for non-obese NAFLD based on the TyG index has good clinical prediction value.
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