Risk Factors Analysis of Urinary Tract Infection after Pelvic Floor Reconstruction and Its Risk Prediction Model Construction
10.11969/j.issn.1673-548X.2025.01.019
- VernacularTitle:盆底重建术后泌尿系感染的危险因素分析及预测模型构建
- Author:
Yun SHI
1
;
Xinyi GAO
;
Lei LI
Author Information
1. 450052 郑州大学第三附属医院妇科
- Publication Type:Journal Article
- Keywords:
Pelvic floor reconstruction;
Urinary system infection;
Risk factors;
Model construction
- From:
Journal of Medical Research
2025;54(1):102-105,110
- CountryChina
- Language:Chinese
-
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 hospital-ized 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,1 strain of fungi,and 1 strain 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 as-sess,continuously observe,and take preventive measures as soon as possible for high-risk patients to reduce the incidence of postopera-tive urinary system infections.
