【摘要】 目的 分析盆底重建术后患者出现泌尿系统感染的危险因素并构建风险预测模型，为临床预防提供参考依据。方法 纳入2020年1月～2021年12月在郑州大学第三附属医院妇科住院的盆底重建术后患者296例，针对其病历资料进行回顾性分析，根据术后是否发生泌尿系统感染，分为感染组(n=13)和未感染组(n=283)。采用单因素分析和Logistic回归分析探讨盆底重建术后患者泌尿系统感染的危险因素，建立风险预测模型。结果 296例患者中发生术后泌尿系统感染13例(4.4%)。13例泌尿系感染患者的尿液培养中分离出病原菌15株，其中革兰阴性菌8株，革兰阳性菌5株，真菌1株，支原体1株。Logistic回归分析结果显示，住院时长≥14天、有尿路感染史、产次≥3次、留置尿管≥3天以及合并糖尿病是盆底重建术后泌尿系统感染的危险因素(P<0.05);ROC分析结果显示，曲线下面积为0.870(95%CI:0.726～1.000),P<0.001,约登指数最大值为0.720,敏感度为76.9%,特异性为95.1%。结论 本研究构建的模型有较好的预测能力，医护人员可以为参考，对于高危患者做好评估、持续观察、尽早采取预防措施，减少术后泌尿系统感染的发生。更多还原

【Abstract】 Objective To analyze the risk factors of urinary tract infection after pelvic floor reconstruction and build a risk prediction model to provide a reference for clinical prevention. Methods A total of 296 patients with pelvic floor reconstruction who were hospitalized in the Department of Gynecology of the Third Affiliated Hospital of Zhengzhou University from January 2020 to December 2021 were included. Their medical records were analyzed retrospectively. According to whether urinary tract infections occurred after the operation, they were divided into an infected group(n=13) and an uninfected group(n=283). Univariate analysis and Logistic regression analysis were used to explore the risk factors of urinary tract infection after pelvic floor reconstruction and a risk prediction model was established. Results Among the 296 patients, 13(4.4%) had postoperative urinary tract infections. A total of 15strains of pathogenic bacteria were isolated from the urine culture of 13 patients with urinary tract infections, including 8strains of Gram-negative bacteria, 5strains of Gram-positive bacteria, 1strain of fungi, and 1strain of mycoplasma. Logistic regression analysis showed that hospitalization time ≥ 14days, a history of urinary tract infection, parity ≥3 times, indwelling catheter ≥ 3days, and diabetes mellitus were the risk factors of urinary tract infection after pelvic floor reconstruction(P< 0.05). ROC analysis showed that the area under the curve was 0.870(95% CI: 0.726-1.000), P< 0.001, and the maximum value of the Jordan Index was 0.720, with a sensitivity of 76.9% and a specificity of 95.1%. Conclusion The model constructed in this study has good prediction ability. Medical staff can take this as a reference to assess, continuously observe, and take preventive measures as soon as possible for high-risk patients to reduce the incidence of postoperative urinary system infections.更多还原