摘要
Abstract
Aim:To analyze the distribution characteristics of postoperative pathogens in patients with anorectal disea-ses and construct a predictive model for multidrug resistant organism(MDRO)infection.Methods:Clinical data of patients with anorectal diseases who developed bacterial infection after surgical treatment at Wuhan Eighth Hospital from March 2020 to December 2024 were retrospectively collected.According to drug susceptibility test results,patients with MDRO infection were included in the MDRO infection group(71 cases),and the remaining were included in the non-MDRO infection group(182 cases).The distribution characteristics of pathogens were analyzed.Logistic regression analysis was used to identify risk factors for postoperative MDRO infection.A predictive model for postoperative MDRO infection in patients with anorec-tal diseases was constructed.The ROC curve was used to evaluate model consistency,the calibration of the model was evalu-ated via the calibration curve,and decision curve analysis was used to assess the clinical net benefit of the model.Results:A total of 268 pathogenic strains were isolated from 253 patients,including 244 strains(91.04％)of Gram-negative bacteria and 24 strains(8.96％)of Gram-positive bacteria.Diabetes,diarrhea,types of antibacterial drugs,duration of antibacterial drug use,and operation time were all influencing factors for MDRO infection,with OR(95％CI)of 3.325(2.602-4.248),2.635(1.446-4.800),2.621(1.733-3.963),1.926(1.386-2.677),and 2.114(1.751-2.552),respectively.A nomogram predictive model was constructed based on the Logistic regression results,with AUC(95％CI)of 0.952(0.893-0.988).The model exhibited strong predictive performance,calibration capability,and promising potential for clinical appli-cation.Conclusion:The predictive model for postoperative MDRO infection in patients with anorectal diseases,constructed based on diabetes,diarrhea,types of antibacterial drugs,duration of antibacterial drug use,and operation time,possesses promising application value.关键词
肛肠疾病/多重耐药菌感染/病原菌分布/预测模型Key words
anorectal disease/multidrug resistant organism infection/distribution of pathogen/predictive model分类
医药卫生
