Volume 23 Issue 6
Jun.  2025
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Article Navigation >  Chinese Journal of General Practice  > 2025  >  23(6): 967-971
XIA Yuanying, BI Mingming, FANG Xiaojuan, XU Xiuqin, LOU Chengli, WU Mei. Factors influencing arteriovenous fistula dysfunction in maintenance hemodialysis patients and construction and validation of prediction model[J]. Chinese Journal of General Practice, 2025, 23(6): 967-971. doi: 10.16766/j.cnki.issn.1674-4152.004044
Citation: XIA Yuanying, BI Mingming, FANG Xiaojuan, XU Xiuqin, LOU Chengli, WU Mei. Factors influencing arteriovenous fistula dysfunction in maintenance hemodialysis patients and construction and validation of prediction model[J]. Chinese Journal of General Practice, 2025, 23(6): 967-971. doi: 10.16766/j.cnki.issn.1674-4152.004044
shu

Factors influencing arteriovenous fistula dysfunction in maintenance hemodialysis patients and construction and validation of prediction model

doi: 10.16766/j.cnki.issn.1674-4152.004044
  • 1.

    Hemodialysis Center, Jiaxing University Affiliated Hospital of Traditional Chinese Medicine, Jiaxing, Zhejiang 314001, China

Funds:

 2023ZL174

  • Received Date: 2024-12-08
    Available Online: 2025-09-04
    Abstract
  •   Objective  The failure of arteriovenous fistula (AVF) seriously affects the quality of hemodialysis. This study aims to explore the influencing factors of AVF failure in maintenance hemodialysis patients and construct a predictive model to provide guidance for the evaluation, prediction, intervention, and prevention of AVF failure in hemodialysis patients.  Methods  A total of 342 maintenance hemodialysis patients from November 2022 to July 2024 at Jiaxing University Affiliated Hospital of Traditional Chinese Medicine were selected as the research subjects. According to whether hemodialysis patients experience AVF dysfunction, they were divided into a dysfunction group (n=55) and a control group (n=287). Clinical data from two groups of patients were collected, including basic information, dialysis and AVF-related information, and laboratory indicators. Multiple logistic regression analyses was conducted to screen risk factors and construct a predictive model for AVF dysfunction in hemodialysis patients. Another 88 hemodialysis patients were selected for clinical external validation.  Results  Advanced age (OR=1.059), diabetes (OR=3.622), blood stasis syndrome (OR=4.787), high level of D-D (OR=1.011), high level of FIB (OR=4.325) were risk factors for AVF dysfunction in hemodialysis patients (P < 0.05). Prediction model: P=ex/(1+ex), X=-19.897+0.058×age+1.287×diabetes+1.566×blood stasis syndrome+0.011×D-D+1.465×FIB. Clinical external validation showed that the accuracy of the model in predicting AVF failure in hemodialysis patients was 90.91% (80/88), and the consistency between the AVF failure prediction model and clinical actual results was high (Kappa=0.680).  Conclusion  Advanced age, diabetes, blood stasis syndrome, and high levels of D-D and FIB are risk factors for AVF dysfunction in hemodialysis patients. The prediction model constructed on this basis is highly accurate. It is of guiding significance for evaluating and predicting AVF dysfunction in hemodialysis patients.

     

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