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山东大学学报(医学版) ›› 2017, Vol. 55 ›› Issue (6): 93-97.doi: 10.6040/j.issn.1671-7554.0.2017.349

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健康管理人群脑卒中风险预测模型

李敏1,2,王春霞3,夏冰3,朱茜1,2,孙苑潆1,2,王淑康1,2,薛付忠1,2,贾红英4   

  1. 1.山东大学公共卫生学院生物统计学系, 山东 济南 250012;2.山东大学齐鲁生物医学大数据研究中心, 山东 济南 250012;3.济宁医学院附属医院健康管理中心, 山东 济宁 272000;4.山东大学第二医院循证医学中心, 山东 济南 250033
  • 收稿日期:2017-04-24 出版日期:2017-06-10 发布日期:2017-06-10
  • 通讯作者: 贾红英. E-mail:jiahongying@sdu.edu.cn 薛付忠. E-mail:xuefzh@sdu.edu.cn E-mail:jiahongying@sdu.edu.cn
  • 基金资助:
    国家国际科技合作专项项目(2014DFA32830)

A stroke prediction model for the health management population

LI Min1,2, WANG Chunxia3, XIA Bing3, ZHU Qian1,2, SUN Yuanying1,2, WANG Shukang1,2, XUE Fuzhong1,2, JIA Hongying4   

  1. 1. Department of Biostatistics, School of Public Health, Shandong University, Jinan 250012, Shandong, China;
    2. Cheeloo Research Center for Biomedical Big Data, Shandong University, Jinan 250012, Shandong, China;
    3. Health Management Center, Affiliated Hospital of Jining Medical University, Jining 272000, Shandong, China;
    4. Evidence Based Medicine Center, The Second Hospital of Shandong University, Jinan 250033, Shandong, China
  • Received:2017-04-24 Online:2017-06-10 Published:2017-06-10

摘要: 目的 构建20岁以上健康管理人群脑卒中发病风险预测模型。 方法 依托山东多中心健康管理纵向观察大数据库,构建20岁以上人群的脑卒中发生队列。采用Fine-Gray竞争风险模型分性别分别构建脑卒中风险预测模型。 结果 观察期间共新发生脑卒中患者1 299例,其中男829例,女470例,发病密度为4.51‰。男性预测模型纳入变量为年龄、高血压、冠心病史、糖尿病、吸烟、体质量指数、甘油三酯、白细胞计数、血小板计数、高密度脂蛋白、总胆固醇;女性预测模型纳入变量为年龄、高血压、冠心病史、红细胞计数、血红蛋白、体质量指数。男性与女性预测模型的受试者工作特征曲线下面积(AUC)分别为0.846(95%CI:0.828~0.864)、0.878(95%CI:0.858~0.898)。 结论 成功构建的脑卒中风险预测模型在健康管理人群中具有很好的预测能力。

关键词: 健康管理人群, 脑卒中, 风险预测模型, 纵向队列

Abstract: Objective To construct a stroke prediction model for the health management population aged above 20 years. Methods A total of 74,326 cohort members without stroke at baseline were included based on the Shandong Multi-center Longitudinal Cohort for Health Management. Fine-Gray model was used to construct a stroke risk prediction model for females and males respectively. Results During the average follow-up of 3.9 years, 1,299(male: 829, female: 470)new stroke occurred, and the incidence density was 4.51‰. The risk factors for males included age, hypertension, coronary heart disease, diabetes mellitus, smoking, body mass index, triglyceride, white blood cell count, platelet count, high-density lipoprotein, and total cholesterol. The risk factors for females included age, hypertension, coronary heart disease, red blood cell count, hemoglobin, and body mass index. The estimated area under the receiver-operating characteristic curve(AUC)for the male model and female model was 0.846(95%CI: 0.828-0.864), and 0.878(95%CI: 0.858-0.898). Conclusion The stroke risk prediction model we constructed is effective in identifying individuals at high risk of stroke in the health management population.

Key words: Stroke, Prediction model, Longitudinal cohort, Health management population

中图分类号: 

  • R743.3
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