Effect of linagliptin on type 2 diabetes mellitus and its predictive factors

Objective To explore the therapeutic effect of linagliptin on type 2 diabetes and its predictive factors. Methods A total of 142 type 2 diabetes patients who were admitted from September 2018 to June 2020 were selected as research subjects and administered with linagliptin. According to the therapeutic effects, the patients were divided into two groups: an effective group and an ineffective group. The predictive factors of the effect of linagliptin in the treatment of type 2 diabetes were analyzed by multivariate logistic regression. In addition, 84 type 2 diabetes patients who received linagliptin treatment during the same period were included to verify the predictive performance of the model. Results The total effective rate of linagliptin in the treatment of type 2 diabetes was 51.41% (73/142). Multivariate logistic regression analysis showed that low baseline glycosylated hemoglobin (OR=10.568), low fasting blood glucose (OR=1.453), low body mass index (BMI) (OR=1.307), and short course of type 2 diabetes (OR=2.536) were the predictive factors of linagliptin. The nomogram showed that the C-index of the prediction model based on these prediction factors was 0.852. The calibration curve showed that the absolute error of the prediction possibility of the nomogram model was 0.011, and the ROC curve of the validation model showed that its AUC was 0.843. Conclusions Low baseline glycated hemoglobin, low fasting blood glucose, low BMI, and short course of diabetes mellitus are the predictive factors that affect the therapeutic effect of gliglitazone on type 2 diabetes.