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血液透析患者心血管疾病风险预测模型研究

赵欣 刘倩倩 李航宇

赵欣, 刘倩倩, 李航宇. 血液透析患者心血管疾病风险预测模型研究[J]. 中华全科医学, 2024, 22(5): 742-745. doi: 10.16766/j.cnki.issn.1674-4152.003493
引用本文: 赵欣, 刘倩倩, 李航宇. 血液透析患者心血管疾病风险预测模型研究[J]. 中华全科医学, 2024, 22(5): 742-745. doi: 10.16766/j.cnki.issn.1674-4152.003493
ZHAO Xin, LIU Qianqian, LI Hangyu. Study on cardiovascular disease risk prediction model for hemodialysis patients[J]. Chinese Journal of General Practice, 2024, 22(5): 742-745. doi: 10.16766/j.cnki.issn.1674-4152.003493
Citation: ZHAO Xin, LIU Qianqian, LI Hangyu. Study on cardiovascular disease risk prediction model for hemodialysis patients[J]. Chinese Journal of General Practice, 2024, 22(5): 742-745. doi: 10.16766/j.cnki.issn.1674-4152.003493

血液透析患者心血管疾病风险预测模型研究

doi: 10.16766/j.cnki.issn.1674-4152.003493
基金项目: 

国家自然科学基金项目 81503381

详细信息
    通讯作者:

    赵欣,E-mail:hahachenfuhua@yeah.net

  • 中图分类号: R459.5  R54

Study on cardiovascular disease risk prediction model for hemodialysis patients

  • 摘要:   目的  本研究旨在评估血液透析患者心血管疾病风险预测得分的推导与验证, 以期为临床诊治提供参考。  方法  选择2020年1-12月期间东南大学医学院附属南京同仁医院进行常规血液透析3个月以上的患者388例, 随访至2023年5月。将所有参与者作为训练数据集得出预测分数, 并使用引导验证数据集进行验证。使用受试者工作特征曲线AUC评价预测分数的判别能力。  结果  在388例基线无心血管疾病的患者中, 132例在平均(3.27±1.01)年的随访期内首次发生心血管事件。年龄、高血压、糖尿病和异常白细胞(WBC)计数被确定为显著的预测因素, 与无危险因素的人群相比, 得分为1分、2分和3~4分的人群患心血管疾病的风险增加, 调整后的HR(95%CI)分别为3.293(1.174~9.260)、7.429(2.681~20.516)和15.434(5.441~43.759)。该模型在训练和验证数据集上均显示出良好的判别能力[AUC分别为0.703(95%CI: 0.652~0.753)和0.688(95%CI: 0.655~0.720)]。  结论  本研究推导并验证了血液透析患者心血管风险的预测模型, 鉴于血液透析患者的数量迅速增加, 这一简单的模型可在临床实践中识别高危个体, 以便更精确和有效地进行个性化治疗。

     

  • 图  1  训练数据集和验证数据集的ROC曲线

    注:A为训练数据集(n=388);B为验证数据集(n=1 000)。

    Figure  1.  ROC curves for training and validation datasets

    图  2  训练数据集和验证数据集对心血管疾病发生风险的3年预测

    注:A为训练数据集(n=388);B为验证数据集(n=1 000)。

    Figure  2.  Three-year prediction of cardiovascular disease risk using training and validation datasets

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出版历程
  • 收稿日期:  2023-07-16
  • 网络出版日期:  2024-07-20

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