【摘要】 目的 探讨影响肿瘤患者外周静脉穿刺中心静脉导管(peripherally inserted central catheter,PICC)堵塞发生的危险因素，构建肿瘤患者PICC堵塞风险预测模型，并进行外部验证。方法 便利抽取2023年1月至10月浙江省丽水市人民医院收治的经PICC的368例肿瘤患者为研究对象，按照7∶3的比例，选取2023年11月至2024年2月的159例置管患者作为验证组。运用单因素及多因素Logistic回归建立风险预测模型并绘制相应的列线图，采用ROC曲线、Hosmer-Lemeshow检验、校准曲线及临床决策曲线分别评估模型的区分度、拟合优度及模型的临床运用价值。结果 多因素Logistic回归均显示，合并糖尿病、D-二聚体升高、肠外营养、导管维护时间≥7 d、剧烈咳嗽是肿瘤患者发生PICC堵塞的危险因素。建模组ROC曲线下面积(AUC)为0.863，特异度和灵敏度分别为0.639和0.948,Hosmer-Lemeshow检验4.679,0.861，表明型具有良好的预测性能。外部验证组AUC为0.890，特异度和灵敏度分别为0.681和0.958。结论 本研究构建的风险预测模型具有较好的预测性能，可有效预测肿瘤患者PICC堵塞的发生概率，为护理工作者早期识别高风险人群并制定干预措施提供参考依据。更多还原

【Abstract】 Objective To develop a prediction model for peripherally inserted central catheter(PICC) occlusion risk in cancer patients, and to validate it externally. Methods By convenience sampling, this study selected 368 cancer patients who had undergone PICC placement in Lishui People’s Hospital from January to October 2023 as the study subjects.A total of 159 patients who had PICC placement from November 2023 to February 2024 were included in the validation group at a ratio of 7:3.Univariate and multivariate Logistic regression analyses were used to establish a risk prediction model. The discriminating ability, consistency, net benefit and clinical utility of the prediction model were assessed by the receiver operating characteristic(ROC) curves,Hosmer-Lemeshow test,calibration curves and decision curve analysis(DCA), respectively. Results Multivariate logistic regression showed that diabetes, elevated D-dimer,parenteral nutrition,catheter maintenance time≥7 d,and violent coughing were risk factors for PICC occlusion in cancer patients.The area under the curve(AUC) of the model was 0.863 in the training group,with a specificity of 0.639 and a sensitivity of 0.948.The Hosmer-Lemeshow test showed the results of 4.679,and 0.861.The calibration curve showed that the predicted probability was well matched with the actual probability, indicating that the model had good calibration.DCA showed that the model had good clinical utility.The AUC of the model in the validation group was 0.890,with a sensitivity of 0.958 and a specificity of 0.681. Conclusion The constructed risk prediction model has good predictive performance, which can effectively predict the probability of PICC occlusion in cancer patients. It can provide references for nursing staff to identify high-risk groups in advance and formulate intervention measures.更多还原