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    闫秀君, 尹冬, 晏曼. 利格列汀治疗 2 型糖尿病效果及其预测因素分析[J]. 徐州医科大学学报, 2022, 42(11): 828-832. DOI: 10.3969/j.issn.2096-3882.2022.11.009
    引用本文: 闫秀君, 尹冬, 晏曼. 利格列汀治疗 2 型糖尿病效果及其预测因素分析[J]. 徐州医科大学学报, 2022, 42(11): 828-832. DOI: 10.3969/j.issn.2096-3882.2022.11.009
    shu
    Linagliptin treatment effect and its predictive factors analysis[J]. Journal of Xuzhou Medical University, 2022, 42(11): 828-832. DOI: 10.3969/j.issn.2096-3882.2022.11.009
    Citation: Linagliptin treatment effect and its predictive factors analysis[J]. Journal of Xuzhou Medical University, 2022, 42(11): 828-832. DOI: 10.3969/j.issn.2096-3882.2022.11.009
    shu

    利格列汀治疗 2 型糖尿病效果及其预测因素分析

    Linagliptin treatment effect and its predictive factors analysis

      摘要
    • 摘要: 目的：探讨利格列汀治疗 2 型糖尿病效果及治疗效果预测因素。方法：选取2018年9月至2020年6月收治的142例 2 型糖尿病 (Diabetes mellitus type 2，T2D)患者为研究对象，所有受试者均接受利格列汀治疗，治疗后根据治疗效果将患者分为显效组和无效组，并采用多因素Logistic回归方程分析利格列汀治疗T2D效果的预测因素。结果：治疗后显示利格列汀治疗T2D的总有效率为51.41%（73/142），根据利格列汀治疗效果分为显效组（n=73）和无效组（n=69例）。多因素Logistic回归方程分析显示，基线糖化血红蛋白较低（OR=10.568）、空腹血糖较低（OR=1.453）、BMI较低（OR=1.307），T2D病程较短（OR=2.536）是利格列汀治疗T2D效果的预测因素，列线图显示基于利格列汀治疗T2D效果的预测因素建立的预测利格列汀治疗T2D效果的C-index为0.852，校正曲线显示列线图模型预测可能性绝对误差为0.011。结论：利格列汀治疗T2D的临床总有效率为51.41%，其中基线糖化血红蛋白较低、空腹血糖较低、BMI较低，高糖尿病病程较短是影响利格列汀治疗T2D效果的预测因素，在临床工作中应重点关注T2D患者基线糖化血红蛋白较、空腹血糖、BMI水平及T2D病程较短，以降低其对利格列汀治疗T2D效果的影响。

       

      Abstract: ob＜x＞jective: To explore the therapeutic effect of linagliptin and the predictive factors of the therapeutic effect. Methods: 142 patients with type 2 diabetes (Diabetes mellitus type 2, T2D) who were admitted from September 2018 to June 2020 were selected as the research subjects. All subjects received linagliptin treatment. The patients were divided into the markedly effective group and the ineffective group, and the multivariate Logistic regression equation was used to analyze the predictive factors of the effect of linagliptin in the treatment of T2D. Results: After treatment, it was shown that the total effective rate of linagliptin in the treatment of T2D was 51.41% (73/142). According to the treatment effect of linagliptin, the markedly effective patients were regarded as the markedly effective group (n=73), and the effective and ineffective patients were regarded as ineffective Group (n=69 cases). Multivariate logistic regression analysis showed that the ba＜x＞seline glycosylated hemoglobin was lower (OR=10.568), fasting blood glucose was lower (OR=1.453), BMI was lower (OR=1.307), and the T2D course was shorter (OR=2.536). The predictive factors of T2D effect of linagliptin. The nomogram shows that the C-index established ba＜x＞sed on the predictive factors of linagliptin in the treatment of T2D is 0.852. The calibration curve shows that the nomogram model predicts the possibility of predicting the effect of linagliptin on T2D. The absolute error of sex is 0.011. Conclusion: The total clinical effective rate of linagliptin in the treatment of T2D is 51.41%, of which lower ba＜x＞seline glycosylated hemoglobin, lower fasting blood glucose, lower BMI, and shorter duration of high diabetes are predictive factors that affect the effect of linagliptin in the treatment of T2D In clinical work, attention should be paid to the ba＜x＞seline glycosylated hemoglobin ratio, fasting blood glucose, BMI level and shorter T2D course of T2D patients in order to reduce its impact on the effect of linagliptin in the treatment of T2D

       

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