人工肝经股静脉置管患者导管相关性血栓形成累积风险预测模型的构建及验证

doi:10.3761/j.issn.0254-1769.2026.17.010

中华护理杂志 ›› 2026, Vol. 61 ›› Issue (17): 2374-2382.DOI: 10.3761/j.issn.0254-1769.2026.17.010

人工肝经股静脉置管患者导管相关性血栓形成累积风险预测模型的构建及验证

留俊霞¹(), 徐敏¹, 郭思言¹, 杨树慧¹, 王华芬²^,^*()

¹ 浙江大学医学院附属第一医院感染病科杭州市 310003
² 浙江大学医学院附属第一医院护理部杭州市 310003

收稿日期:2026-01-19 出版日期:2026-09-10 发布日期:2026-09-03
*通讯作者: 王华芬，E-mail：2185015@zju.edu.cn
作者简介:留俊霞：女，本科（硕士在读），主管护师，E-mail：1709028@zju.edu.cn
第一联系人：作者贡献声明
留俊霞：研究方案实施、数据整理与统计分析、论文撰写；徐敏：研究设计、研究指导、论文审阅及修改；郭思言：研究设计、数据收集、统计分析、论文修改；杨树慧：数据收集、论文修改；王华芬：研究设计、研究指导、论文审阅及修改
基金资助:
浙江省中医药科技计划项目(2024ZL544)

Development and validation of a risk prediction model for catheter-related thrombosis in patients undergoing artificial liver therapy via femoral vein catheterization

LIU Junxia¹(), XU Min¹, GUO Siyan¹, YANG Shuhui¹, WANG Huafen²^,^*()

¹ Department of Infectious Diseases， the First Affiliated Hospital，Zhejiang University School of Medicine， Hangzhou 310003
² Nursing Department， the First Affiliated Hospital，Zhejiang University School of Medicine， Hangzhou 310003

Received:2026-01-19 Online:2026-09-10 Published:2026-09-03
* Corresponding author: WANG Huafen，E-mail：2185015@zju.edu.cn
Funding program:
Traditional Chinese Medicine Science and Technology Project，Zhejiang Province(2024ZL544)

摘要/Abstract

摘要：

目的探讨人工肝经股静脉置管患者导管相关性血栓（catheter-related thrombosis，CRT）形成的高风险特征组合规律，构建并验证累积风险预测模型，为实施精准的预见性护理提供参考。方法连续纳入2024年1—12月杭州市某三级甲等医院收治的人工肝经股静脉置管患者作为调查对象，采集相关资料。运用Apriori算法挖掘CRT形成的核心高风险关联规则，通过分组矩阵聚类及网络拓扑图对核心高风险关联规则进行聚类与可视化分析，并基于分析结果构建累积风险预测模型，采用Logistic回归分析验证模型的预测效能。结果共纳入206例患者，CRT发生率为53.39%。运用Apriori算法，提取出1 712条核心高风险关联规则。对提升度排序前15位的核心高风险关联规则进行聚类分析，提炼出5类核心特征组合，其中有意识障碍且人工肝治疗次数≥3次的平均提升度最高。网络拓扑图分析结果显示，人工肝治疗次数≥3次、Caprini评分为3~4分、治疗前纤维蛋白原浓度<1.5 g/L是网络中连接度较高的3个枢纽节点。依据5类核心特征组合构建累积风险预测模型，Logistic回归分析结果显示，模型评分与CRT的发生风险呈正相关（OR=1.689，P<0.001）。结论该研究构建的模型能有效量化人工肝经股静脉置管患者CRT形成中多风险因素的叠加效应，对高风险患者的识别准确率较高。

关键词: 人工肝, 导管相关性血栓, 关联规则, 预测模型, 护理

Abstract:

Objective To explore the combination patterns of high-risk characteristics for catheter-related thrombosis（CRT） formation in patients undergoing artificial liver support therapy via femoral vein catheterization，and to develop and validate a cumulative risk prediction model，so as to provide a reference for implementing precise and anticipatory nursing care. Methods Patients who underwent artificial liver support therapy via femoral vein catheterization in a tertiary hospital in Hangzhou from January to December 2024 were consecutively included as the study population，and their relevant clinical data were collected. The Apriori algorithm was applied to mine the core high-risk association rules for CRT formation. Clustering and visualization analyses of these core rules were performed using grouping matrix clustering and network topology graphs. Based on the analytical results，a cumulative risk prediction model was constructed，and logistic regression analysis was employed to validate the predictive performance of the model. Results A total of 206 patients were included，and the incidence of CRT was 53.39%. Using the Apriori algorithm，1，712 core high-risk association rules were extracted. Cluster analysis was performed on the top 15 core rules ranked by lift，and 5 clusters of core characteristic combinations were identified. Among these，the combination of “impaired consciousness and number of artificial liver support therapy sessions ≥3” showed the highest average lift. Network topology analysis revealed that “number of artificial liver support therapy sessions ≥3”，“Caprini score of 3-4”，and “pre-treatment fibrinogen concentration <1.5 g/L” were the 3 hub nodes with higher connectivity in the network. Based on the 5 clusters，a cumulative risk prediction model was constructed. Logistic regression analysis showed that the model score was positively associated with the risk of CRT（OR=1.689，P<0.001）. Conclusion The model can effectively quantify the cumulative effect of multiple risk factors for CRT formation in patients undergoing artificial liver support therapy via femoral vein catheterization，and demonstrates a relatively high accuracy in identifying high-risk patients.

Key words: Artificial Liver, Catheter-Related Thrombosis, Association Rules, Predictive Model, Nursing Care

留俊霞, 徐敏, 郭思言, 杨树慧, 王华芬. 人工肝经股静脉置管患者导管相关性血栓形成累积风险预测模型的构建及验证[J]. 中华护理杂志, 2026, 61(17): 2374-2382.

LIU Junxia, XU Min, GUO Siyan, YANG Shuhui, WANG Huafen. Development and validation of a risk prediction model for catheter-related thrombosis in patients undergoing artificial liver therapy via femoral vein catheterization[J]. Chinese Journal of Nursing, 2026, 61(17): 2374-2382.

图/表 7

表1 人工肝经股静脉置管患者血栓组与非血栓组的一般资料比较

Table 1 Comparison of baseline characteristics between the thrombosis and non-thrombosis groups in patients undergoing artificial liver support system treatment

续表1 人工肝经股静脉置管患者血栓组与非血栓组的一般资料比较

Table 1（Continued） Comparison of baseline characteristics between the thrombosis and non-thrombosis groups in patients undergoing artificial liver support system treatment

表2 连续型变量的截断值

Table 2 Cut-off of continuous variables

表3 人工肝经股静脉置管患者导管相关性血栓形成前15位核心高风险关联规则

Table 3 Top 15 association rules for the risk of catheter-related thrombosis in patients undergoing artificial liver support system treatment

表4 人工肝经股静脉置管患者导管相关性血栓形成前15项核心高风险关联规则的聚类特征

Table 4 Clustering characteristics of the top 15 association rules for catheter-related thrombosis in patients undergoing artificial liver support system treatment

图1 人工肝经股静脉置管患者导管相关性血栓形成前15位核心高风险关联规则的网络拓扑图注：为结局事件；为关联规则；为临床风险特征。Rule 1~15对应表3中第1~15条核心高风险关联规则。A1为导管相关性血栓；B1为人工肝治疗次数≥3次；B2为Caprini评分为3~4分；B3为治疗前纤维蛋白原浓度<1.5 g/L；B4为治疗后纤维蛋白原浓度<1.5 g/L；B5为治疗后白蛋白浓度为30~40 g/L；B6为治疗后总胆红素浓度>205 μmol/L；B7为未使用抗凝药物；B8为治疗后血小板计数<83×109 /L；B9为治疗前国际标准化比值为1.5~2.5；B10为无饮酒史；B11为男性；B12为右侧股静脉置管；B13为治疗前血小板计数≥83×109 /L；B14为治疗前总胆红素浓度≥205 μmol/L；B15为有意识障碍。

Figure 1 Network topology of the top 15 core high-risk association rules for catheter-related thrombosis in patients undergoing artificial liver therapy via femoral vein catheterization

表5 不同累积风险评分值下人工肝经股静脉置管患者的导管相关性血栓发生率（n=206）

Table 5 Incidence of catheter-related thrombosis in patients undergoing artificial liver therapy via femoral vein catheterization at different cumulative risk scores（n=206）

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人工肝经股静脉置管患者导管相关性血栓形成累积风险预测模型的构建及验证

Development and validation of a risk prediction model for catheter-related thrombosis in patients undergoing artificial liver therapy via femoral vein catheterization

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