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女性冠心病患病风险评价数学模型的建立与验证

  

  1. 玉溪市人民医院 a.检验科;b.重症医学科;云南 玉溪 653100
  • 出版日期:2016-11-05 发布日期:2016-11-04
  • 通讯作者: 通信作者:冯磊,email:fngj2004@163.com
  • 基金资助:
    云南省教育厅一般项目(2011C083)

Building and confirming the mathematical model to estimate the occurrence of coronary heart disease in female

  1. a. Department of Laboratory;b. Intensive Care Unit, People′s Hospital of Yuxi,Yuxi  653100, China
  • Online:2016-11-05 Published:2016-11-04
  • Contact: Corresponding author: Feng Lei, Email: fngj2004@163.com

摘要: 目的尝试建立综合多个生理生化指标的评价数学模型,提高女性冠心病(CHD)的诊断效能。方法通过相关性及ROC曲线分析,明确与女性CHD密切关联的指标,尝试建立评价数学模型,通过ROC曲线确定诊断效能,并在患者中进行重复性验证。结果①建模对照组与建模病例组除低密度脂蛋白胆固醇(LDLC)、载脂蛋白B(APOB)和脂蛋白a[Lp(a)]外,其余各指标差异均有统计学意义;②年龄、甘油三酯(TG)、同型半胱氨酸(Hcy)、γ谷氨酰转移酶(GGT)、高密度脂蛋白胆固醇(HDLC)和载脂蛋白A(APOA)与CHD具有很强的相关性;③年龄、Hcy、GGT、HDLC、APOA  5个指标ROC曲线下面积大于0.75;④建立了6个数学评价模型,其中模型6的ROC曲线下面积达到了0.955;⑤数学模型能在验证人群中被重复。结论通过建立包含了多个指标的数学评价模型,能显著提升女性判断是否患CHD的诊断效能。

关键词: 冠心病;女性;模型, 统计学

Abstract: ObjectiveTo build the mathematical estimation model with multiple physiological and biochemical factors in order to improve the potency in diagnosing coronary heart disease (CHD) in female. MethodsThrough the correlation analysis and ROC curve, the factors which had significant relationship with CHD were confirmed. The mathematical estimation model was built,the diagnostic efficiency was confirmed by ROC curve and the repeatability was performed in patients. Results①There were significant differences between test group and control group except for LDLC, APOB and Lp(a); ②There were very strong relationship between CHD and age, TG, HCY, GGT, HDLC, APOA; ③In ROC curve,the areas of five indexes such  as age,HCY, GGT, HDLC and APOA were more than 0.75; ④A total of six mathematical models were built  and the area of the sixth model was 0.955; ⑤The mathematical estimation model can be repeated to validate  the patients. ConclusionThe mathematical estimation models with multiple factors can significantly promote the potency in diagnosing CHD in female.

Key words: coronary heart disease, female, models, statistical