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