PKRP术后尿路感染发生风险可视化预测模型构建与验证  

Construction and validation of a visual prediction model for the risk of urinary tract infection after PKRP surgery

作　　者：叶帆 万玉英 涂萍[3] 徐春桃 YE Fan;WAN Yuying;TU Ping;XU Chuntao(Department of Urology,the Second Affiliated Hospital of Nanchang University,Nanchang 330036,Jiangxi,China;Department of Hospital Infection Control,the Second Affiliated Hospital of Nanchang University,Nanchang 330036,Jiangxi,China;Department of Anesthesiology and Perioperative Medicine,the Second Affiliated Hospital of Nanchang University,Nanchang 330036,Jiangxi,China)

机构地区：[1]南昌大学第二附属医院泌尿外科,江西南昌330036 [2]南昌大学第二附属医院医院感染控制处,江西南昌330036 [3]南昌大学第二附属医院麻醉与围术期医学科,江西南昌330036

出　　处：《中国现代医生》2024年第12期19-23,共5页China Modern Doctor

基　　金：江西省教育厅科学技术研究项目(GJJ2200163);江西省卫生健康委科技计划项目(202130465)。

摘　　要：目的分析经尿道前列腺等离子电切术(transurethral resection of the prostate with plasmakinetic energy,PKRP)术后尿路感染的影响因素,建立风险预测列线图模型。方法选取2020年12月至2021年9月南昌大学第二附属医院泌尿外科行PKRP的患者资料为建模集,应用单因素分析和Logistic多因素回归分析筛选高危因素,构建风险预测列线图模型并进行内部、外部验证。结果PKRP术后尿路感染发生率为15.38%。多因素分析显示,年龄、其他部位感染、糖尿病、术前导尿、尿道损伤、留置导尿管材质、留置导尿管更换次数、留置导尿时长等是尿路感染发生的危险因素(P<0.05)。内部验证(曲线下面积0.875)和外部验证(曲线下面积0.869)显示构建的风险预测列线图模型具有良好的区分度和准确性。结论PKRP术后尿路感染影响因素复杂,构建的风险预测列线图模型具有良好预测性能,可为PKRP术后尿路感染的防治提供依据。Objective To analyze the influencing factors of postoperative urinary tract infection in patients undergoing transurethral resection of the prostate with plasmakinetic energy(PKRP)and establish a risk prediction nomogram model.Methods The data of PKRP patients in Department of Urology,the Second Affiliated Hospital of Nanchang University from December 2020 to September 2021 were selected as the modeling set,and the high-risk factors were screened by univariate analysis and Logistic regression analysis.The risk prediction nomogram model was constructed and verified internally and externally.Results The incidence of urinary tract infection after PKRP surgery was 15.38%.Multivariate analysis showed that age,other location infection,diabetes,preoperative catheterization,urethral injury,indwelling catheter material,hair coloring catheter replacement times and number of indwelling catheterization were risk factors for urinary tract infection(P<0.05).Internal verification(area under the curve was 0.875)and external verification(area under the curve was 0.869)show that the risk prediction nomogram model has good discrimination and accuracy.Conclusion The influencing factors of urinary tract infection after PKRP are complex.The risk prediction nomogram model has good prediction performance,which can provide a basis for the prevention and treatment of urinary tract infection after PKRP.

关 键 词：前列腺增生 尿路感染 预测 列线图 

分 类 号：R699[医药卫生—泌尿科学]