Construction of a predictive model for pelvic infection after gynecological malignant tumor surgery
10.3760/cma.j.cn115682-20210315-01133
- VernacularTitle:妇科恶性肿瘤术后患者盆腔感染预测模型的构建
- Author:
Jingping LI
1
;
Qinmei FENG
;
Fang YANG
Author Information
1. 山西省人民医院妇科，太原 030002
- Keywords:
Pelvic infection;
After Gynecological malignant tumor surgery;
Risk factors;
Predictive model
- From:
Chinese Journal of Modern Nursing
2021;27(35):4824-4828
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the risk factors of pelvic infection after gynecological malignant tumor surgery and construct a predictive model.Methods:The convenient sampling method was used to collect the clinical data of 278 patients who underwent gynecological malignant tumor surgery in Shanxi Provincial People's Hospital from June 2018 to June 2020. According to the occurrence of postoperative pelvic infection, the patients were divided into the infection group ( n=29) and the non-infection group ( n=249) . Univariate and binomial Logistic regression analysis was used to investigate the risk factors of pelvic infection after gynecological malignant tumor surgery, and ROC curve was used to analyze the predictive value of the prediction model. Results:The incidence of pelvic infection in 278 patients with gynecological malignancies after surgery was 10.43% (29/278) . Binary logistic regression analysis showed that whether there were diabetes, chronic pelvic pain, history of preoperative pelvic infection and operation method, operation duration, and hospital stay were the influencing factors of pelvic infection after gynecological malignant tumor surgery ( P<0.05) . ROC curve analysis showed that diabetes mellitus, chronic pelvic pain, history of preoperative pelvic infection, surgical method, surgical duration and length of hospital stay all had certain predictive value for pelvic infection after gynecological malignant tumor surgery, while the predictive value of combined application was higher than that of each index alone. The area under the ROC curve was 0.821 (95% CI: 0.729-0.915) , and the accuracy was 0.817. Conclusions:The presence of diabetes mellitus, chronic pelvic pain, preoperative history of pelvic infection, surgical method, duration of surgery and length of hospital stay are the influential factors for pelvic infection after gynecological malignant tumor surgery. The combined prediction model established based on the above factors has good prediction ability.
