关键词: 膀胱癌； 经尿道膀胱肿瘤切除术； 尿道感染； 病原菌； 风险预测

Abstract: Objective To explore the pathogen characteristics and risk prediction model verification of urinary tract infection after transurethral bladder cancer tumor resection.Methods This study adopted a retrospective analysis method to conduct an in-depth analysis of the data from 150 bladder cancer patients collected by our hospital between January 2022 and December 2024.Patients were divided into two groups based on whether they developed urinary tract infections post-surgery:the non-infected group (n=127) and the infected group (n=23).A preliminary single-factor screening was conducted to identify potential factors that may influence the occurrence of urinary tract infections in bladder cancer patients after surgery.Based on the results of the single-factor screening,a multivariate logistics regression was performed to determine independent influencing factors.The R software was used to construct a predictive model for postoperative urinary tract infections in bladder cancer patients,and the area under the curve (AUC),sensitivity,and specificity were calculated to evaluate the performance of the predictive model.Results In 150 bladder cancer patients,23 cases developed urinary tract infections.Among these infected cases,Gram-negative bacteria accounted for 16 cases,representing as high as 69.57%.Univariate analysis showed that age,history of diabetes,pelvic radiation therapy,surgery duration,and catheter retention time were significantly associated with postoperative urinary tract infections (P<0.05).Variables with significant differences were included in a binary Logistic regression model,which identified diabetes,history of pelvic radiation therapy,older age,and longer catheter retention time as independent factors influencing urinary tract infections after transurethral resection of bladder tumors in bladder cancer patients（P＞0.05）.Additionally,based on these independent influencing factors,a logistic regression model was established with an C-index of 0.99,indicating excellent discrimination.There was no significant difference between the actual observed values and predicted values (χ²=8.999，P=0.342 4),suggesting good model fit.The AUC of the predictive model was 0.977,with a 95%CI ranging from 0.952 to 1.000,further confirming the accuracy of the model.Conclusion Patients with bladder cancer have a higher chance of developing urinary tract infections after transurethral resection of bladder tumors,primarily due to Gram-negative bacteria.Further analysis revealed that prolonged catheterization,age,history of pelvic radiation therapy,and diabetes are significant risk factors for urinary tract infections.Targeted preventive measures for these risk factors can reduce infection rates and improve patient outcomes.

Key words: bladder cancer; transurethral bladder tumor resection; urinary tract infection; pathogenic bacteria; risk prediction