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从筛查到策略:内镜逆行胰胆管造影术(ERCP)后耐碳青霉烯类肠杆菌科细菌(CRE)感染的预测
Authors Wang J, Su K, Wang S, Yang Y
Received 13 May 2025
Accepted for publication 1 August 2025
Published 20 August 2025 Volume 2025:18 Pages 4189—4199
DOI https://doi.org/10.2147/IDR.S532928
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Yan Li
Jundi Wang,1 Kaisheng Su,1 Shuying Wang,2,3 Yanfei Yang2
1Department of Rheumatology and Immunology, Hangzhou First People’s Hospital Affiliated of Westlake University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 2Department of Hospital Infection Management, Hangzhou First People’s Hospital Affiliated of Westlake University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China; 3Infectious Disease Department, Hangzhou First People’s Hospital Affiliated of Westlake University School of Medicine, Hangzhou, Zhejiang, People’s Republic of China
Correspondence: Shuying Wang, Email wsy7310@163.com Yanfei Yang, Email yanfeiyang@zju.edu.cn
Background: Invariably, patients can be exposed to Carbapenem‐resistant Enterobacteriaceae (CRE) through contaminated device during Endoscopic retrograde cholangiopancreatography (ERCP). We aimed to identify the risk factors and establish a model for predicting subsequent CRE infections in patients with CRE-positive bile screening after ERCP.
Methods: Patients underwent ERCP were performed with bile active screening of CRE. Medical records were reviewed to identify patient demographics, comorbidities, microbiology and antimicrobial treatments. The results were grouped according to the occurrence of subsequent CRE infection, and the patients were divided into two groups: a CRE infection group and a non-CRE infection group. The diagnosis for CRE infection was confirmed by more than 2 physicians. Logistic regression methods were used to determine the risk factors for CRE infections. The risk prediction model was constructed by integrating the clinical data and the result of logistic regression, by a nomogram and forest plot. Finally, goodness of fit of the final model was tested using the likelihood ratio test.
Results: Central venous catheterization (OR=11.32; 95% CI 1.15– 40.62), cholecystitis (OR=3.82; 95% CI 1.12– 13.01), malignancy (OR=4.33; 95% CI 1.41– 13.35) and the antimicrobial drug use (OR=1.08; 95% CI 1.03– 1.14) were considered as highly relevant risk factors for subsequent CRE infections in bile active screening positive patients. The goodness of fit test indicated that the model was well-calibrated for both groups.
Conclusion: A targeted active screening in bile samples can be beneficial for patients with high risk factors of CRE infections. The nomogram developed in this study can help clinicians accurately predict the possibility of patients with subsequent CRE infections after ERCP, so as to facilitate more precise individualized treatment.
Keywords: bile active screening, nomogram, ERCP, CRE