中国血液净化

中国血液净化 ›› 2025, Vol. 24 ›› Issue (02): 149-152.doi: 10.3969/j.issn.1671-4091.2025.02.011

• 综述 • 上一篇    下一篇

人工智能在维持性血液透析患者动静脉内瘘管理中的应用进展

姚石燕   沈华娟    董永泽    贾艳清    赵梦娇   

  1. 311121 杭州，1杭州师范大学护理学院
    310014 杭州，2浙江省人民医院护理部
    310053 杭州，3浙江中医药大学护理学院
  • 收稿日期:2024-05-27 修回日期:2024-08-19 出版日期:2025-02-12 发布日期:2025-02-12
  • 通讯作者: 沈华娟 E-mail:13588158842@163.com
  • 基金资助:
    浙江省医药卫生科技计划(2021KY468)；浙江省中医药科技计划(2022ZB040)；浙江省医药卫生科技计划(2023RC129)

Advances in the application of artificial intelligence for management of arteriovenous fistula in maintenance hemodialysis patients

YAO Shi-yan, SHEN Hua-juan, DONG Yong-ze, JIA Yan-qing, ZHAO Meng-jiao   

  1. College of Nursing, Hangzhou Normal University, Hangzhou 311121, China; 2Department of Nursing, Zhejiang Provincial People's Hospital, Hangzhou 310014, China; 3College of Nursing, Zhejiang University of Chinese Medicine, Hangzhou 310053, China
  • Received:2024-05-27 Revised:2024-08-19 Online:2025-02-12 Published:2025-02-12
  • Contact: 310014 杭州，2浙江省人民医院护理部 E-mail:13588158842@163.com

摘要： 终末期肾病因其长期性、不可治愈性成为威胁患者健康的重要公共卫生问题之一。维持性血液透析是终末期肾病患者最有效的肾脏替代疗方法。动静脉血管通路是常用的透析通路类型，提高新建动静脉内瘘成熟率和长期通畅率一直是临床透析工作者的重点和难点。近年来，人工智能(artificial intelligence，AI)在透析领域中的研究逐渐趋于成熟，借助AI技术进行动静脉内瘘管理可能成为解决问题的新方法。本文综述了AI在动静脉内瘘管理中的应用和进展，包括动静脉内瘘部位选择决策、手术后成熟度预测、功能监测、声学特征监测、血栓及狭窄预测及动脉瘤分级等6个方面，以期为AI在维持性血液透析患者动静脉内瘘管理中的应用提供借鉴。

关键词: 人工智能, 维持性血液透析, 动静脉内瘘, 机器学习

Abstract: End-stage renal disease has become one of the important public health problems due to its long-term and incurable nature. Maintenance hemodialysis is the most effective renal replacement therapy for patients with end-stage renal disease, and arteriovenous fistula (AVF) is the frequently used blood access for hemodialysis. However, maturation of newly established AVF and maintenance of AVF patency are two critical obstacles required to be solved. Recently, artificial intelligence (AI) has been successfully used in the field of dialysis. AI provides a novel alternative for the management of AVF. This article reviews recent advances in the application of AI for management of AVF dealing with six aspects: decision-making of AVF site, postoperative maturity prediction, functional monitoring, acoustic feature monitoring, thrombosis and stenosis prediction, and aneurysm grading, aiming to provide references for the application of AI for management of AVF in maintenance hemodialysis patients.

Key words: Artificial intelligence, Maintenance hemodialysis, Arteriovenous fistula, Machine learning

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