高血压合并2型糖尿病列线图预测模型建立

Construction of a nomogram model for the prediction of type 2 diabetes mellitus in patients with hypertension

目的探讨新疆维吾尔自治区克拉玛依市居民高血压患者合并2型糖尿病(type 2 diabetes mellitus,T2DM)的影响因素,构建高血压合并T2DM的个体化风险预测模型。方法选取2020年1—12月在克拉玛依市医院和卫生服务中心健康检查者中被诊断为高血压的10155例患者为研究对象,回顾性收集患者的基本特征、人体测量指标和实验室检测数据。采用Lasso回归筛选独立危险因素,在此基础上利用多因素logistic回归分析进一步探讨并建立列线图预测模型。采用受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under the curve,AUC)评估列线图预测模型的预测能力。利用Bootstrap自抽样法对模型进行内部验证,利用一致性指数(C-index)、Hosmer-Lemeshow检验以评估模型区分度和校准度。结果高血压合并T2DM者1616例(15.91%),未合并T2DM者8539例(84.09%)。多因素logistic回归分析结果显示,高龄(OR=1.18~1.73,95%CI:1.00~2.04)、荤食为主(OR=1.91,95%CI:1.67~2.19)、体质量指数偏高(OR=1.18~1.96,95%CI:1.02~2.28)、腰围偏高(OR=1.88,95%CI:1.69~2.10)、三酰甘油偏高(OR=2.27,95%CI:2.02~2.55)、高密度脂蛋白胆固醇偏低(OR=1.98,95%CI:1.76~2.23)和有糖尿病家族史(OR=2.13,95%CI:1.79~2.54)为高血压患者合并T2DM独立危险因素(P均<0.05)。构建的高血压合并T2DM列线图预测模型ROC曲线下面积为0.748(95%CI:0.742~0.754),经内部验证,该模型的C-index为0.746(95%CI:0.697~0.795),校准曲线显示该模型预测结果与实际结果的一致性良好(χ^(2)=3.982,P=0.782)。结论本研究构建的列线图预测模型,具有良好判别能力,对于社区医务工作者早期甄别高血压合并T2DM高风险人群,并制定针对性干预策略具有指导意义。

Objective To explore the independent risk factors of type 2 diabetes mellitus(T2 DM)in patients with hypertension in Karamay,the Xinjiang Uygur Autonomous Region,and to build a personalized prediction model for predicting T2 DM in hypertensive patients.Methods 10155 patients with confirmed hypertension in Karamay hospital and health service center from January to December 2020 were selected as study cohort.Patients′demographic information,anthropometric indexes and laboratory test data were retrospectively obtained.Lasso regression was used to screen independent risk factors.In addition,multivariate logistic regression analysis was used to further explore and construct the nomogram prediction model.The area under the receiver operating characteristic(ROC)curve(AUC)was used to evaluate the prediction ability of the nomogram model.The bootstrap self-sampling method was used for internal validation of the model and the consistency index(c-index)and Hosmer lemeshow test were used to evaluate the discrimination and calibration of the model.Results Among 10155hypertensive cases,1616(15.91%)also had T2DM.Multivariate logistic regression analysis showed that older age(OR=1.18-1.73,95%CI:1.00-2.04),high consumption of meat(OR=1.91,95%CI:1.67-2.19),high body mass index(OR=1.18-1.96,95%CI:1.02-2.28),high waist circumference(OR=1.88,95%CI:1.69-2.10),high level of triglyceride(OR=2.27,95%CI:2.02-2.55)and low level of high density lipoprotein cholesterol(OR=1.98,95%CI:1.76-2.23)and family history of diabetes(OR=2.13,95%CI:1.79-2.54)were independent risk factors for T2DM in hypertensive patients(P<0.05).The area under the ROC curve of the constructed nomogram prediction model of hypertension complicated with T2DM was 0.748(95%CI:0.742-0.754).After internal validation,the C-index of the model was 0.746(95%CI:0.697-0.795).The calibration showed that the prediction results of the model were in good agreement with the actual results(χ^(2)=3.982,P=0.782).Conclusions The nomogram prediction model constructed in this study has good discrimination ability,which may guide community medical providers to identify the high-risk population of hypertension complicated with T2DM in the early stage and formulate targeted intervention strategies.