基于决策树的居家静脉留置针患儿静脉炎风险模型

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摘要 目的: 探讨居家静脉留置针患儿发生静脉炎的危险因素,并构建居家静脉留置针患儿发生静脉炎的决策树模型。方法: 选取2023年1月―2023年10月进入医院进行诊治的350例居家静脉留置针患儿作为研究对象,根据静脉炎的发生情况将患儿分为静脉炎组和无静脉炎组。应用Logistic回归分析筛选居家静脉留置针患儿发生静脉炎的危险因素,应用SPSS Modeler软件构建居家静脉留置针患儿发生静脉炎的决策树模型,并分析居家静脉留置针患儿发生静脉炎的决策树模型的预测效能。结果: 350例居家静脉留置针患儿中有62例患儿发生静脉炎,静脉炎的发生率为17.71%（62/350）。Logistic回归分析结果显示,未一次穿刺成功、输入刺激性药物、留置时间>5 d、每日输液量>250 mL、家属延期维护及生理盐水封管等是居家静脉留置针患儿发生静脉炎的危险因素。居家静脉留置针患儿发生静脉炎的决策树模型选择了一次穿刺成功、家属延期维护、每日输液量、输入药物类型、留置时间及封管液等6个临床特征作为模型的节点,其中一次穿刺成功是最重要的预测因子。居家静脉留置针患儿发生静脉炎的决策树模型的AUC是0.814（95%CI：0.785~0.843）,灵敏度是78.60%,特异度是84.20%,居家静脉留置针患儿发生静脉炎的Logistic回归模型的AUC是0.756（95%CI：0.683~0.829）,灵敏度是61.30%,特异度是80.20%,决策树模型的AUC高于Logistic回归模型的的AUC。结论: 未一次穿刺成功、输入刺激性药物、留置时间>5 d、每日输液量>250 mL、家属延期维护及生理盐水封管等是居家静脉留置针患儿发生静脉炎的危险因素,以上因素构建的预测模型对预测居家静脉留置针患儿发生静脉炎具有一定参考价值,临床可据此对居家静脉留置针患儿针对性的护理干预以降低静脉炎的发生风险。

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	郭红燕
	翟羽佳
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	陈忱

关键词 ：居家静脉留置针, 患儿, 静脉炎, 危险因素, 决策树

Abstract：Objective To investigate the risk factors of phlebitis in children with home intravenous catheter, and establish a decision tree model of phlebitis in children with home intravenous catheter. Methods A total of 350 children with home intravenous indent needles who were admitted to the hospital from January 2023 to October 2023 were selected as the study object. According to the occurrence of phlebitis, the children were divided into the phlebitis group and the non-phlebitis group. Logistic regression analysis was used to screen the risk factors for phlebitis in children with home intravenous indent needles, SPSS Modeler software was used to build a decision tree model for phlebitis in children with home intravenous indent needles, and the prediction efficiency of the decision tree model for phlebitis in children with home intravenous indent needles was analyzed. Results Among 350 children with intravenous indwelling needle at home, 62 cases developed phlebitis, and the incidence of phlebitis was 17.71% (62/350). Logistic regression analysis showed that the risk factors for phlebitis in children with home intravenous indentation were not successful puncture, input of stimulant drugs, indentation time >5d, daily infusion volume >250mL, family maintenance delay and saline tube sealing. The decision tree model of phlebitis in children with intravenous indenture at home selected six clinical characteristics as nodes of the model, including one successful puncture, family deferred maintenance, daily infusion volume, type of incoming drugs, indenture time and tube sealing fluid, among which one successful puncture was the most important predictor. The AUC of the decision tree model for phlebitis in children with home intravenous indent needles was 0.814(95%CI: 0.785~0.843), the sensitivity was 78.60%, and the specificity was 84.20%. The AUC of the Logistic regression model for phlebitis in children with home intravenous indent needles was 0.756(95%CI: 0.785~0.843) . Conclusion The risk factors for phlebitis in children with home intravenous indentation are not successful once, the infusion of stimulant drugs, indentation time >5 d, daily infusion volume >250 mL, delayed maintenance by family members, and saline tube sealing. The prediction model constructed by the above factors has certain reference value for predicting phlebitis in children with home intravenous indentation needles. In order to reduce the risk of phlebitis, targeted nursing interventions can be conducted for children with intravenous indwelling needles at home.

Key words： home intravenous indwelling needle children with children phlebitis risk factors decision tree

收稿日期: 2023-11-14

中图分类号:

543.6

基金资助:国家自然科学基金“HucMSC-exosomes促进AMI炎症期成纤维细胞表达型转化保护心肌损伤机制研究”（81800270）

通讯作者: 翟羽佳,E-mail：15052919402@163.com

引用本文:

郭红燕, 翟羽佳, 王文婷, 朱菊红, 陈忱. 基于决策树的居家静脉留置针患儿静脉炎风险模型[J]. 湖南师范大学学报(医学版), 2024, 21(3): 167-172. GUO Hongyan, ZHAI Yujia, WANG Wenting, ZHU Juhong, CHEN Chen. Risk model of phlebitis in children with home intravenous indwelling needles based on decision tree. HuNan ShiFan DaXue XueBao(YiXueBan), 2024, 21(3): 167-172.

链接本文:

http://yxb.hunnu.edu.cn/CN/ 或 http://yxb.hunnu.edu.cn/CN/Y2024/V21/I3/167

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