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中国医药导刊 ›› 2025, Vol. 27 ›› Issue (6): 576-580.

• 临床医药 • 上一篇    下一篇

基于彩色多普勒超声及临床多参数的动静脉内瘘并发症风险预测模型应用研究

张期芳1, 唐青1, 徐佩佩2*   

  1. 南京江北医院护理部1,肾内科2,江苏 南京 210048
  • 收稿日期:2024-12-17 修回日期:2025-04-23 接受日期:2025-08-02 出版日期:2025-06-28 发布日期:2025-08-06
  • 基金资助:
    2020年中石化南化公司临床医学专项科研项目(ZX20207)

The Application of A Risk Prediction Model for Arteriovenous Fistula Complications Based on Color Doppler Ultrasound and Clinical Multi Parameters prediction model is used in clinical practice

ZHANG Qifang1, TANG Qing1, XU Peipei2*   

  1. Department of Nursing1 Department of Nephrology2 Nanjing Jiangbei Hospital Jiangsu Nanjing 210048, China
  • Received:2024-12-17 Revised:2025-04-23 Accepted:2025-08-02 Online:2025-06-28 Published:2025-08-06
  • Supported by:
    《 基于“个案管理”下血液透析患者血管通路全程管理模式的构建与实施》(ZX20207)

摘要:

目的:探讨维持性血液透析(maintenance hemodialysis MHD)患者自体动静脉内瘘(internal arteriovenous fistula AVF)并发症发生的危险因素,并构建风险预测模型,为降低并发症采取有效干预措施提供依据。方法:回顾性分析20201月至202312月于我院肾内科行AVF手术的259MHD患者的临床资料,收集患者的血管彩色多普勒参数和一般临床资料,根据是否发生并发症分为并发症组和正常组。采用单因素和多因素Logistic回归分析影响并发症发生的危险因素,并得出回归方程。结果导入R软件,生成可视化Nomogram图模型,绘制受试者工作特征(receiver operating characteristicROC)曲线和校准曲线,评估预测模型对MHD患者AVF并发症发生风险的区分度和准确度。结果:259例患者中,并发症组73例(占比28.18%),正常组186例(占比71.82%)。多因素分析结果显示:桡动脉峰值流速(β=-0.08295%CI0.867~0.980P=0.009)、桡动脉内径(β=-1.80095%CI0.0520.134P=0.005)、头静脉血流量(β=-0.05895%CI0.8930.997P=0.038)、空腹血糖(β=0.08495%CI0.9221.003P=0.035)是AVF并发症发生的独立危险因素。所构建的AVF并发症风险预测模型ROC曲线下面积(AUC)为0.98695%CI0.9740.998),校准曲线的斜率接近1,平均绝对误差(MAE)为0.015。结论:基于彩色多普勒超声及临床多参数的预测模型可以在评估AVF并发症发生方面起到重要的作用,在临床工作中利用此模型对患者加以评估,对有风险的患者及早进行干预,可减少并发症的发生。


关键词: 维持性血液透析, 动静脉内瘘, 并发症, 危险因素, 风险预测模型

Abstract:

Objective: To investigate the risk factors for complications of autologous arteriovenous fistula AVF in maintenance hemodialysis MHD patients and construct a risk prediction model to guide interventions for reducing complication.Methods: A retrospective analysis was conducted on the clinical data of 259 MHD patients who underwent AVF surgery in the department of nephrology of our hospital from January 2020 to December 2023. The vascular color Doppler ultrasound parameters and clinical data of the patients were collected. The patients were divided into the complication group and the normal group according to whether complications occurred. Univariate and multivariate Logistic regression analyses were performed to identify the risk factors influencing the occurrence of complications and the regression equations were obtained. The results were imported into R software to generate a visual Nomogram model draw the receiver operating characteristic ROC curve and calibration curve and evaluate the discrimination and accuracy of the predictive model for the risk of AVF complications in MHD patients.Results: Among the 259 patients 73 cases accounting for 28.18% were in the complication group and 186 cases accounting for 71.82% were in the normal group. Multivariate analysis identified the following independent risk factors radial artery peak systolic velocity PSV) (β = -0.082 95% CI 0.867-0.980P = 0.009), radial artery diameter β = -1.800 95% CI 0.052-0.134P = 0.005), cephalic vein blood flow β = -0.058 95% CI 0.893-0.997P = 0.038), and fasting blood-glucose β = 0.084 95% CI 0.922-1.003P = 0.035. The area under the ROC curve AUC is 0.986 95% CI 0.974-0.998. The slope of the calibration curve is close to 1 and the mean absolute error MAE is 0.015. Conclusion The predictive model integrating color Doppler ultrasound and multivariate clinical parameters can play an important role in evaluating the occurrence of complications of AVF. The clinical application of this model enables early risk stratification and targeted interventions to reduce complication incidence.

 

Key words: Maintenance hemodialysis , Arteriovenous fistula , Complication , Risk factors , Risk prediction model

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