护理研究2025，Vol.39Issue(15)：2525-2534,10.DOI:10.12102/j.issn.1009-6493.2025.15.004
肺癌病人治疗期输液港医用粘胶相关皮肤损伤风险预测模型的构建
Construction of a risk prediction model for medical adhesive related skin injury in infusion ports during the treatment period of lung cancer patients
摘要
Abstract
Objective:To analyze the risk factors for medical adhesive related skin injury(MARSI)in infusion ports during the treatment period of lung cancer patients.And to establish a risk prediction model,so as to provide reference for clinical nursing intervention.Methods:A retrospective collection of 650 patients with implantable chest wall ports who were hospitalized in the respiratory and critical care medicine department of a tertiary grade A general hospital from January 2023 to April 2024 was conducted.Logistic regression model,decision tree classification regression(CART)model,and random forest models were used to establish risk prediction models for medical adhesive related skin injury in infusion ports during the treatment period of lung cancer patients.The accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Kappa coefficient,and area under the receiver operating characteristic(ROC)curve(AUC)of the three models were compared to evaluate their performance.Results:The accuracy of Logistic regression model,decision tree CART model,and random forest models were 84%,86%,and 86%,respectively.The specificity were 97%,98%,and 97%.The sensitivity were 54%,59%,and 61%.The positive predictive values were 54%,59%,and 61%.The negative predictive values were 97%,98%,and 97%.The Kappa values were 0.57,0.63,and 0.64.The AUC were 0.83,0.87,and 0.86.There were statistically significant in the AUC differences among Logistic regression model,decision tree CART model,and random forest(P<0.05).Skin toxicity was a common predictor for three models.Conclusions:Compared with Logistic regression model,decision tree CART model and random forest model had better performance in constructing a risk prediction model for in infusion ports during the treatment period of lung cancer patients,it could provide reference for clinical nurses to predict the risk of medical adhesive related skin injury in infusion ports during the treatment period of lung cancer patients.关键词
输液港/医用粘胶相关皮肤损伤/预测模型/Logistic回归/决策树分类回归树/随机森林法Key words
infusion port/medical adhesive related skin injuries/predictive model/Logistic regression/decision tree CART/random forest method引用本文复制引用
吴珊珊,刘扣英,汤婷..肺癌病人治疗期输液港医用粘胶相关皮肤损伤风险预测模型的构建[J].护理研究,2025,39(15):2525-2534,10.基金项目
江苏省人民医院2021年度临床能力提升工程护理项目,编号:JSPH-NC-2021-17 （）
