以代谢相关因子构建新疆哈萨克族人群心脑血管疾病发病风险预测模型

Using metabolism related factors constructing a predictive model for the risk of cardiovascular diseases in Xinjiang Kazakh population

目的以代谢综合征(MS)及其因子构建和验证新疆哈萨克族人群心脑血管疾病(CVD)发病风险预测模型。方法以2010~2012年新疆伊犁州新源县基线调查满5年的2286名哈萨克族居民为研究对象,分别于2013、2016和2017年通过当地医院的病例收集CVD事件。对基线706例MS患者进行因子分析,从18种体检指标中提取主因子与年龄、性别构建CVD发病风险预测模型。剔除基线发生CVD和数据不全者,2007人作为内部验证人群;以哈拉布拉乡219人作为外部验证人群,分别进行logistic判别分析,计算每位研究对象CVD的发病概率和受试者工作特征曲线,评价CVD模型的预测能力。结果新疆哈萨克族MS患病率为30.88%。在哈萨克族MS人群分别提取7个主因子,分别是肥胖因子、血脂血糖因子、肝功能因子、血脂因子、肾代谢因子、血压因子、肝酶因子。所构建的CVD模型预测内部验证人群的曲线下面积(AUC)为0.773(95%CI 0.754~0.792),外部验证人群的AUC为0.858(95%CI 0.805~0.901)。结论以哈萨克族MS患者提取的7个主因子构建的CVD发病风险预测模型有较高的验证效度,可用于新疆哈萨克族人群CVD的风险评估。

Objective To construct and confirm a predictive model for the risks of cardiovascular diseases(CVD)with metabolic syndrome(MS)and its factors in Xinjiang Kazakh population.Methods A total of 2286 Kazakh individuals were followed for 5 years from 2010 to 2012 as baseline survey.They were recruited in Xinyuan county,Yili city,Xinjiang.CVD cases were identified via medical records of the local hospitals in 2013,2016 and 2017,respectively.Factor analysis was performed on 706 MS patients at baseline,and main factors,age,and sex were extracted from 18 medical examination indexs to construct a predictive model of CVD risk.After excluding the subjects with CVD at baseline and incomplete data,2007 were used as internal validation,and 219 Kazakhs in Halabra Township were used as external validation.Logistic regression discriminations were used for internal validation and external validation,as well as to calculate the probability of CVD for each participant and receiver operating characteristic curves.Results The prevalence of MS in Kazakh was 30.88%.Seven main factors were extracted from the Kazakh MS population,namely obesity factor,blood lipid and blood glucose factor,liver function factor,blood lipid factor,renal metabolic factor,blood pressure factor,and liver enzyme factor.The area under the curve(AUC)for predicting CVD in the internal validation was 0.773(95%CI 0.754-0.792).In the external validation,the AUC for predicting CVD was 0.858(95%CI 0.805-0.901).Conclusions The CVD risk prediction model constructed by 7 main factors extracted from Kazakh MS patients has high validation efficiency and can be used for risk assessment of CVD in Xinjiang Kazakh population.