摘要
背景动脉粥样硬化性心血管疾病(ASCVD)最有效的预防策略是实施基层管理,其核心措施是进行风险评估,现有老年人ASCVD预测模型不能很好地指导中医基层管理,因此,需将中医元素融入预测模型的开发,以指导ASCVD中西医结合基层管理。目的构建并验证基于中医体质的老年人ASCVD预测模型。方法纳入2017年在华苑街社区卫生服务中心、陈塘庄街社区卫生服务中心、向阳路街社区卫生服务中心、大邱庄镇中心卫生院进行健康查体的1418名老年人(≥65岁)为研究对象,收集研究对象一般资料,对研究对象进行体质辨识。于2017—2022年随访研究对象ASCVD发病情况(临床结局),随访截止于2022-11-30。将研究对象数据按照8∶2随机拆分为训练集和验证集,在训练集中,采用向前逐步法构建老年人ASCVD常规预测模型(模型1)和老年人ASCVD常规+体质预测模型(模型2)。绘制基于中医体质的老年人ASCVD预测模型列线图。绘制校准曲线及进行Hosmer-Lemeshow拟合优度检验判定模型的校准度。绘制受试者工作特征(ROC)曲线并计算ROC曲线下面积(AUC)判定模型的区分度。使用AUC、净重分类改善度(NRI)、综合判别指数(IDI)、临床决策曲线(DCA)对模型2与模型1进行比较,评估改善效能。结果训练集(n=1127)与验证集(n=291)研究对象一般资料比较,差异无统计学意义(P>0.05)。多因素Logistic分析结果显示,模型1包含性别、年龄、腰围、收缩压、三酰甘油、BMI、收缩压×高血压用药史,共计7种预测变量;模型2包含性别、年龄、腰围、收缩压、三酰甘油、BMI、收缩压×高血压用药史、体质类型,共计8种预测变量。Hosmer-Lemeshow拟合优度检验结果示模型2拟合度良好,Delong检验结果显示,模型2的AUC高于模型1(Z=2.741,P=0.006),NRI=0.511(95%CI=0.359~0.663,P<0.001),IDI=0.038(95%CI=0.024~0.051,P<0.001),提示添加体质预测变量可提高模型预测的准确度。临床效用对比结果示,在5%~74%阈值概率下,使用模型2预测严重老年人ASCVD事件的净收益率优于模型1。结论本研究构建了一个包含性别、年龄、腰围、收缩压、三酰甘油、BMI、收缩压×高血压用药史、体质类型8个预测变量的老年人ASCVD预测模型,经检验,区分度、校准度表现良好,较传统常规预测模型表现更为优秀,可以应用于老年人ASCVD个体化风险评估,指导ASCVD中西医结合基层管理。
Background The most effective prevention strategy for atherosclerotic cardiovascular disease(ASCVD)is primary management,with the core measure of risk assessment.The existing prediction models for ASCVD for the elderly are not able to guide TCM primary management well.Therefore,it is necessary to integrate TCM elements into the development of prediction models to guide the primary management of ASCVD with combined traditional Chinese and western medicine.Objective To construct and validate the ASCVD prediction model for the elderly based on TCM constitution.Methods A total of 1418 elderly people who underwent physical examination at Huayuan Street Community Health Service Center,Chentangzhuang Street Community Health Service Center,Xiangyang Road Street Community Health Service Center and Daqiuzhuang Town Central Health Center in 2017 were included as the study subjects.General data of the study subjects were collected and constitution identification was performed.The incidence of ASCVD(clinical outcome)was followed up from 2017 to 2022.The follow-up will end at 2022-11-30.The data of the subjects were randomly divided into a training set(n=1127)and validation set(n=291)according to 8∶2.In the training set,the conventional ASCVD prediction model for the elderly(model 1)and the conventional ASCVD+constitution prediction model for the elderly(model 2)were constructed by using the forward stepwise method.The nomogram of ASCVD prediction model for the elderly based on TCM constitution was plotted.The calibration curve was plotted and the Hosmer-Lemeshow goodness of fit test was performed to determine the calibration of the model.The receiver operating characteristic curve was plotted and the area under the curve(AUC)was calculated to determine the discrimination of the model.AUC,Net Reclassification Index(NRI),Integrated Discrimination Improvement(IDI),and Decision Curve Analysis(DCA)were used to compare model 2 with model 1 to evaluate the improvement efficacy of model 2.Results There was no significant difference in the general data between the training set and validation set(P>0.05).The results of multivariate analysis showed that model 1 included 7 predictors of gender,age,waist circumference,systolic blood pressure,triacylglycerol(TG),BMI,systolic blood pressure×hypertension medication history.model 2 included 8 predictors of gender,age,waist circumference,systolic blood pressure,TG,BMI,systolic blood pressure×hypertension medication history,and constitution type.Hosmer-Lemeshow goodness-of-fit test showed good fit of model 2;Delong test results showed that AUC of model 2 was higher than that of model 1(Z=2.741,P=0.006),NRI=0.511(95%CI=0.359-0.663,P<0.001),IDI=0.038(95%CI=0.024-0.051,P<0.001),suggesting that the addition of constitution predictors could improve the accuracy of model prediction.The clinical utility comparison results showed that the net benefit of model 2 to predict severe ASCVD events in the elderly was better than model 1 at a threshold probability of 5%to 74%.Conclusion In this study,a ASCVD prediction model for the elderly was constructed including 8 predictor variables of gender,age,waist circumference,systolic blood pressure,TG,BMI,systolic blood pressure×hypertension medication history,and constitution type.After testing,the differentiation and calibration performed well,which was better than the conventional prediction model,and can be applied to the individualized risk assessment of ASCVD in the elderly and guide the primary management of ASCVD with combined traditional Chinese and western medicine.
作者
高颖
许欣宜
刘洋
杨晓琨
GAO Ying;XU Xinyi;LIU Yang;YANG Xiaokun(First Teaching Hospital of Tianjin University of Traditional Chinese Medicine,Tianjin 300381,China;National Clinical Medicine Research Center of Chinese Medicine Acupuncture and Moxibustion,Tianjin 300381,China)
出处
《中国全科医学》
CAS
北大核心
2024年第15期1878-1885,共8页
Chinese General Practice
基金
2022年天津市家庭医生团队能力建设实践课题(JYZ202201)。
