Caprini评分联合凝血指标构建PICC相关性血栓风险可视化模型

doi:10.16460/j.issn1008-9969.2023.13.006

护理学报 ›› 2023, Vol. 30 ›› Issue (13): 6-12.doi: 10.16460/j.issn1008-9969.2023.13.006

Caprini评分联合凝血指标构建PICC相关性血栓风险可视化模型

项晓婷^1,2,3, 张会^2,3,1, 苏畅^2,3, 胡桑^2,3, 张真^2,3, 许静¹, 仲蕾¹, 陆雅维¹

1.安徽医科大学护理学院,安徽合肥 230601;
2.安徽医科大学第一附属医院,安徽合肥 230032;
3.安徽省公共卫生临床中心,安徽合肥 230032

收稿日期:2023-02-15 出版日期:2023-07-10 发布日期:2023-08-04
通讯作者: 张会（1973-）,女,安徽合肥人,硕士,硕士研究生导师,主任护师。E-mail：zhanghui310@126.com
作者简介:项晓婷（1997-）,女,安徽六安人,本科学历,硕士研究生在读。
基金资助:
2021年安徽省护理学会科研课题立项项目（AHHLb202104）; 2023年度安徽医科大学护理学院研究生青苗培育项目（hl12023060）

Construction of PICC-catheter related thrombosis risk visualization model with Caprini Score and coagulation index

XIANG Xiao-ting^1,2,3, ZHANG Hui^2,3,1, SU Chang^2,3, HU Sang^2,3, ZHANG Zhen^2,3, XU Jing¹, ZHONG Lei1,LU Ya-wei¹

1. School of Nursing, Anhui Medical University, Hefei 230601,China;
2. the First Affiliated Hospital of Anhui Medical University,Hefei 230032,China;
3. Anhui Provincial Public Health Clinical Center, Hefei 230032,China

Received:2023-02-15 Online:2023-07-10 Published:2023-08-04

摘要/Abstract

摘要： 目的联合Caprini评分和凝血指标D-二聚体构建PICC相关性血栓可视化模型。方法回顾性纳入了2018年9月—2022年9月在我院行PICC置管并维护的413例患者,收集患者的人口学资料、置管资料、Caprini评分以及D-二聚体等相关指标,通过多因素Logistic回归模型分析独立危险因素,MedCalc软件分别绘制Caprini评分、D-二聚体以及两者联合的受试者工作特征曲线（ROC曲线）并对比曲线下面积（AUC）,采用R软件绘制列线图。结果本研究共纳入413例患者,发生PICC相关性血栓患者为38例（9.2%）。多因素Logistic回归分析结果显示,年龄、Caprini评分、D-二聚体、BMI、既往病史、化疗、导管规格、肢体选择为发生PICC相关性血栓发生的独立危险因素。对比ROC曲线下面积（AUC）：Caprini评分单独预测为0.714,D-二聚体单独预测为0.636,两者联合预测为0.876,（95%CI：0.840-0.906）。通过对分析结果的可视化处理,显示联合预测模型的区分度较高,Brier评分和校正曲线都表现了较好的校准度。H-L检验（χ²=3.505,P>0.05）结果显示,该模型的拟合度较好。结论 Caprini评分联合凝血指标D-二聚体构建的PICC相关性血栓可视化模型具有较好的预测效果,可以有效地预测PICC相关性血栓的早期风险,为临床治疗提供有力的参考依据。

关键词: 经外周静脉置入中心静脉导管, PICC相关性血栓, Caprini评分, D-二聚体, 可视化模型

Abstract: Objective To construct a visualization model of PICC-catheter related thrombosis risk with Caprini score and D-dimer. Methods A total of 413 patients who received PICC catheterization and maintenance in our hospital from September 2018 to September 2022 were retrospectively included. Demographic data, catheterization data, Caprini score, D-dimer and other related indicators of patients were collected. Independent risk factors were analyzed by using multiple logistic regression. Caprini score, D-dimer and their combined receiver operating characteristic curve (ROC curve) were drawn respectively by MedCalc software, and the area under the curve (AUC) was compared. Results The incidence of PICC-associated thrombosis was 9.2% (38 patients). Multiple logistic regression showed that age, Caprini score, D-dimer, BMI, past medical history, chemotherapy, catheter size, and limb selection were independent risk factors for PICC-catheter related thrombosis. The AUC of Caprini score alone was 0.714; that of D-dimer alone 0.636, and that of the combined 0.876 (95%CI: 0.840~0.906). Visualization processing showed that the joint prediction model had a high degree of differentiation, and the Brier score and correction curve both showed a good calibration degree. H-L inspection (χ²=3.505,P>0.05) showed good fitting of the model. Conclusion The visualization model of PICC-catheter related thrombosis constructed by Caprini score combined with D-dimer can effectively predict the early risk of PICC-catheter related thrombosis, and provide reference for clinical treatment.

Key words: peripherally inserted central catheter, PICC-catheter related thrombosis, Caprini score, D-dimer, visualization model

中图分类号:

R473

项晓婷, 张会, 苏畅, 胡桑, 张真, 许静, 仲蕾, 陆雅维. Caprini评分联合凝血指标构建PICC相关性血栓风险可视化模型[J]. 护理学报, 2023, 30(13): 6-12.

XIANG Xiao-ting, ZHANG Hui, SU Chang, HU Sang, ZHANG Zhen, XU Jing, ZHONG Lei1, LU Ya-wei. Construction of PICC-catheter related thrombosis risk visualization model with Caprini Score and coagulation index[J]. Journal of Nursing, 2023, 30(13): 6-12.

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Caprini评分联合凝血指标构建PICC相关性血栓风险可视化模型

Construction of PICC-catheter related thrombosis risk visualization model with Caprini Score and coagulation index

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