Résumé
Objective To investigate the value of triglyceride-glucose index (TyG) and body mass index (BMI) in predicting nonalcoholic fatty liver disease (NAFLD) in type 2 diabetes mellitus (T2DM). Methods A retrospective analysis was performed for the clinical data of 349 patients with T2DM who were treated in Shengjing Hospital of China Medical University from May 2020 to July 2021, and according to the presence or absence of NAFLD, they were divided into T2DM+NAFLD group with 213 patients and simple T2DM group with 136 patients. The t -test or the Mann Whitney U test was used for comparison of continuous data between two groups, and the chi-square test was used for comparison of categorical data between two groups. A logistic regression analysis was used to investigate the association of TyG and BMI with T2DM+NAFLD, and the receiver operating characteristic (ROC) curve was plotted to evaluate the prediction efficiency of TyG alone, BMI alone, and TYG combined with BMI for NAFLD in T2DM. The Kappa coefficient was used to analyze the consistency of prediction results. Results Compared with the simple T2DM group, the T2DM+NAFLD group had significantly higher BMI, diastolic pressure, fasting blood glucose, HbA1c, alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transpeptidase, triglyceride, total cholesterol, low-density lipoprotein cholesterol, and TyG (all P 0.05). The logistic regression analysis showed that TyG (odds ratio [ OR ]=6.513, 95% confidence interval [ CI ]: 1.884-22.517, P < 0.001) and BMI ( OR =1.369, 95% CI : 1.191-1.575, P < 0.001) were independent risk factors for NAFLD in T2DM. The ROC curve analysis showed that TyG had an area under the ROC curve (AUC) of 0.875 in predicting NAFLD in T2DM, with a sensitivity of 80.3%, a specificity of 80.1%, a positive predictive value of 86.36%, and a negative predictive value of 72.19% at the optimal cut-off value of 9.41; BMI had an AUC of 0.787, with a sensitivity of 78.9%, a specificity of 64.0%, a positive predictive value of 77.36%, and a negative predictive value of 64.23% at the optimal cut-off value of 24.22; TyG combined with BMI had an AUC of 0.910, a sensitivity of 81.2%, a specificity of 88.2%, a positive predictive value of 91.53%, and a negative predictive value of 75.00% in predicting NAFLD in T2DM. TyG alone, BMI alone, and TyG combined with BMI had a Kappa coefficient of 0.592, 0.416, and 0.673, respectively, in predicting NAFLD in T2DM. Conclusion TyG and BMI can be used to predict the onset of NAFLD in T2DM, and the combination of TyG and BMI can improve the predictive value.
Résumé
Objective: To explore the differences between chemical constituents of Lonicerae Japonicae Flos and Lonicerae Flos based on the quality and quantity analysis. Methods: The chromatographic separation was carried out on a Luna C18-HST column (100 mm × 3.0 mm, 2.5 μm) with gradient elution kept at 40 ℃. The mobile phases consist of 0.1% formic acid aqueous solution and 0.1% formic acid acetonitrile solution at a flow rate of 1.0 mL/min. The samples were analyzed with a small volume (1 μL) per injection. DAD detection was performed at 327 nm from 0 to 3 min, 350 nm from 3 to 5 min and ELSD detection was performed from 5 to 8 min. Results: Almost all the compounds had good linearities (r = 0.997 6-0.999 9). The excellent recovery rates were 98.71%-100.8% with their RSD from 0.53%-1.87%. Twenty batches of samples obtained from different locations were examined and their chromatographic profiles were compared. Conclusion: The results showed that this method was simple, reliable, and stable, and it could be used to rapidly distinguish Lonicerae Japonicae Flos and Lonicerae Flos with high resolution in a single run within 8 min. Furthermore, the method could accurately determinate chlorogenic acid, luteolin-7-O-glucoside, maranthoidin B, and dipsaccside B.