【摘要】 目的探讨代谢综合征(MS)组分组合对心脑血管疾病(CVD)的预测能力。方法应用美国Fram-ingham Risk Score(FRS)和中国人群的心血管病综合危险度简易评估工具——缺血性心血管病(ischemic cardiovasculardiseases,ICVD)两种模型分别对CVD事件做出预测,并比较不同MS组分组合人群CVD事件的危险度。结果 MS的4种组分同时存在时CVD发病风险最大,其FRS和ICVD预测CVD的绝对风险中位数分别为14.0%和10.3%。MS组CVD 10年发病绝对风险均高于MS高危组和对照组(P<0.01),FRS模型预测MS组中危及高危能力高于ICVD模型(P<0.05),特别是>60岁MS患者。结论 FRS和ICVD两个模型均可以区分不同人群CVD的危险度,FRS模型长于对中危、高危人群CVD的预测,而ICVD模型长于对低危人群CVD的预测。从而为制定有针对性的危险因素控制策略、减少CVD的发生提供科学依据。更多还原

【Abstract】 Objective To compare the cardiovascular prediction ability between Framingham risk score algorithm(FRS) and ischemic cardiovascular disease(ICVD) of metabolic syndrome(MS) and component clusters.Methods CVD events were predicted by FRS and ICVD models,and the risk levels of CVD events among different MS component clusters were compared.Results CVD incidence was the highest when four components of MS exist at the same time,and the risk medians were 14.0% and 10.3% respectively for FRS and ICVD on predicting CVD.Absolute risk for CVD in ten years was significantly higher in MS group than in high risk group and control group(P<0.01).Moderate risk and high risk prediction on CVD calculated by FRS were significantly higher than those by ICVD(P<0.05),especially for MS patients over 60 years.Conclusion Both FRS and ICVD model can identify CVD risks among different populations.FRS statistical model specializes in moderate and high risk prediction of CVD,while the ICVD algorithm specializes in low risk prediction on CVD.The two models can provide scientific basis for targeted risk control strategies to reduce the incidence of CVD.更多还原