摘要:目的:探讨2型糖尿病合并糖尿病足患者与胰岛素抵抗的关系。方法:205例2型糖尿病患伴糖尿病足患者作为观察组,无足部病变的糖尿病患者作为对照组,观察其体重指数、空腹血糖、胰岛素、血脂等指标,两组间进行比较并相关性分析、多元回归分析。胰岛素抵抗指数(HOMAIR)=FPG×FIns/22.5。结果:糖尿病足患者的HOMAIR显著高于无糖尿病的患者(Plt;0.05)。多元回归分析显示糖尿病病程、LDL及BMI是影响2型糖尿病足患者胰岛素抵抗的主要危险因素。结论:糖尿病足患者存在着更严重的胰岛素抵抗。Abstract: Objective: To discuss the relationship between diabetes and pedopathy of type II diabetes and insulin resistance. Methods:The diabetes type II patients were divided into group A (combined with pedopathy) and group B (without pedopathy). The blood glucose and insulin of empty stomach, BMI,Alc and lipid were detected. The insulin resistance index (HOMAIR) was calculated and compared between two groups. Results:The HOMAIR was higher in group A than that in group B (Plt;0.05).The duration of disease,LDL and BMI was positive related with diabetes pedopathy. Conclusion:The insulin resistance was more worse in pedopathy of Type II diabetes.
Objective To explore the association between triglyceride glucose-waist circumference (TyG-WC) index and the risk of stroke among the middle-aged and older people, and compare the differences among TyG-WC, triglyceride glucose (TyG), and waist circumference (WC) in the prediction of stroke. Methods The data of adults aged 45 years or older enrolled in the China Health and Retirement Longitudinal Study registry in 2011 were collected, and the endpoint was self-reported or physician-diagnosed new stroke event by 2015. According to the baseline TyG-WC tertile, individuals were divided into three groups: TyG-WC tertile 1, tertile 2, and tertile 3 groups. Multiple logistic regression analyses were performed to analyze the associations of TyG-WC, TyG, and WC with the risk of stroke. The area under the curve (AUC) of receiver operating characteristic (ROC) curve, integrated discrimination improvement (IDI) score, and net reclassification improvement (NRI) score were calculated to evaluate the predictive value of TyG-WC, TyG, and WC in stroke. Results A total of 5847 participants were finally included, with 1949 in each group. After 4 years of follow-up, there were 252 cases of new stroke. There was significant difference in the incidence of stroke among the three groups (TyG-WC tertile 1 group: 2.57%, TyG-WC tertile 2 group: 4.16%, TyG-WC tertile 3 group: 6.21%; P<0.05). The results of multiple logistic regression analyses showed that the risk of new stroke in the third tertile group of TyG-WC and WC was higher than that in the first tertile group, respectively [TyG-WC: odds ratio (OR)=1.465, 95% confidence interval (CI) (1.033, 2.078), P=0.032; WC: OR=1.717, 95%CI (1.190, 2.478), P=0.004], while TyG was not the risk factor of stroke (P>0.05). The ROC curve analysis showed that the AUC of WC (0.566) was slightly higher than that of TyG-WC (0.556) and TyG (0.527). The IDI of TyG-WC (0.25%) was slightly higher than that of WC (0.22%), and the both were higher than that of TyG (0.07%). The NRI of WC (25.04%) was slightly higher than that of TyG-WC (19.68%), and the both were high than that of TyG (12.02%). Conclusions Compared with TyG, higher TyG-WC and WC are associated with the increased risk of new stroke among the middle-aged and older people. The predictive value of TyG-WC and WC for the risk of new stroke in the middle-aged and elderly is similar, and is better than that of TyG.
Objective To construct, validate and evaluate a nomogram prediction model based on triglyceride-glucose index for predicting the risk of type 2 diabetes mellitus (T2DM) in patients with obstructive sleep apnea (OSA). Methods A total of 414 patients diagnosed with OSA who were hospitalized in the Second Affiliated Hospital of Kunming Medical University from July 2013 to July 2023 were retrospectively analyzed. They were randomly divided into training set (n=289) and validation set (n=125) at a ratio of 7:3 using R software. In the training set, univariate logistic regression, best subsets regression (BSR) and multivariate Logistic regression were used to determine the independent predictors of OSA combined with T2DM and construct a nomogram. The area under the receiver operating characteristic curve (AUC), calibration curve, Hosmer-Lemeshow goodness of fit test, decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the discrimination, calibration and clinical applicability of the nomogram prediction model. Finally, the internal validation of the nomogram prediction model was carried out on the validation set. Results In the training set, the results of univariate logistic regression, BSR and multivariate logistic regression analysis showed that hypertension (OR=2.413, 95%CI 1.276-4.563, P=0.007), apnea hypopnea index (OR=1.034, 95%CI 1.014-1.053, P=0.001), triglyceride-glucose index( OR=12.065, 95%CI 5.735-25.379, P<0.001), triglyceride/high density lipoprotein cholesterol (OR=0.736, 95%CI 0.634-0.855, P<0.001) were independent predictors of T2DM in OSA patients. A nomogram prediction model was constructed based on the above four predictors. In the training set and validation set, the AUC, sensitivity, and specificity of the nomogram prediction model for predicting the risk of T2DM in OSA patients were 0.820 (95%CI 0.771-0.869), 75.7%, 75.9% and 0.778 (95%CI 0.696-0.861), 74.5%, 73.0%, respectively, indicating that the nomogram had good discrimination. The calibration curve showed that the nomogram had a good calibration for predicting T2DM in OSA patients. DCA and CIC also showed that the nomogram prediction model had certain clinical utility. Conclusions A simple, fast and effective nomogram prediction model with good discrimination, calibration and clinical applicability was successfully constructed, validated and evaluated. It can be used to predict the risk of T2DM in OSA patients and help clinicians to identify patients with high risk of T2DM in OSA patients.
ObjectiveTo investigate the possible mechanism of the improvement of type 2 diabetes mellitus with insulin resistance of skeletal muscles after Roux-en-Y gastric bypass surgery (RYGB). MethodsThirty GK rats were randomly divided into GK-RYGB group, sham operation group (GK-SO group), and control group (GK-control group); in addition, 10 Wistar rats served as normal control group.On day 28, the animals were sacrificed.The ghrelin concen-tration and PI3Kp85α, Akt/PKB, and GLUT4 levels were measured by ELISA, Western blot, and real-time PCR me-thods, respectively. Results①Compared with the GK-SO group and GK-control group, the plasma ghrelin levels were significantly increased in the normal control group (P < 0.01) and GK-RYGB group (P < 0.01).②Compared with the GK-SO group and GK-control group, p-/t-PI3Kp85α, p-/t-Akt/PKB, and m-/t-GLUT4 proteins were significantly incre-ased in the normal control group (P < 0.01, P < 0.05, and P < 0.01, respectively) and GK-RYGB group (P < 0.01, P < 0.05, and P < 0.01, respectively).③Compared with the GK-SO group and GK-control group, PI3Kp85α, Akt, and GLUT4 mRNA were significantly increased in the normal control group (P < 0.01, P < 0.05, and P < 0.05, respectively) and GK-RYGB group (P < 0.01, P < 0.05, and P < 0.05, respectively). ConclusionRYGB could elevate the ghrelin level obviously and upregulate PI3Kp85α, Akt/PKB, and GLUT4 levels and thus improve the insulin resistance of skeletal muscles of rats with T2DM.