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

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

东南大学医学院附属南京同仁医院肾内科，江苏南京 211102

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
计量
- 文章访问数: 31
- HTML全文浏览量: 40
- PDF下载量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2023-07-16
- 网络出版日期: 2024-07-20

Study on cardiovascular disease risk prediction model for hemodialysis patients

Department of Nephrology, Tongren Hospital, Affiliated to Southeast University School of Medicine, Nanjing, Jiangsu 211102, China

摘要

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。
- 心血管疾病 /
- 血液透析 /
- 预测模型 /
- 危险因素
Abstract: Objective To evaluate the derivation and validation of cardiovascular disease risk prediction scores in hemodialysis patients and to provide a reference for clinical diagnosis and treatment. Methods A total of 388 patients who underwent routine hemodialysis for more than 3 months from January to December 2020 were selected and followed up until May 2023.All participants were used as the training dataset to obtain the predicted scores, and the guided validation dataset was used for validation.Evaluate the discriminative ability of predicted scores using the area under the subject's work characteristic curve (AUC). Results Among 388 patients without cardiovascular disease at baseline, 132 had a first cardiovascular event during a mean follow-up of (3.27±1.01) years.Among the 26 clinical parameters, age, hypertension, diabetes and abnormal WBC count were identified as significant predictors and included in the prediction model.Compared with those without these risk factors, those with scores of 1, 2, and 3-4 had an increased risk of cardiovascular disease.The adjusted hazard ratio and 95%CI were 3.293(1.174-9.260), 7.429(2.681-20.516) and 15.434(5.441-43.759), respectively.The model shows good discriminative ability on both training and validation data sets[AUC values of 0.703(95%CI: 0.652-0.753) and 0.688(95%CI: 0.655-0.720), respectively]. Conclusion We have derived and validated a predictive model for cardiovascular risk in hemodialysis patients.With the rapidly increasing number of hemodialysis patients, this simple model can be used to identify high-risk individuals in clinical practice for more accurate and effective personalized treatment.
- Cardiovascular disease /
- Hemodialysis /
- Predictive model /
- Risk factors

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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

下载: 全尺寸图片幻灯片

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

下载: 全尺寸图片幻灯片

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