Pathogen status, risk factors and prediction model construction for catheter-related infection in patients with maintenance hemodialysis
- VernacularTitle:维持性血液透析患者导管相关感染的病原菌情况、危险因素与预测模型构建
- Author:
Ting PANG
1
;
Weili WU
;
Binjiao YANG
Author Information
- Publication Type:Research Article
- Keywords: maintenance hemodialysis; catheter-related infections; pathogens; risk factors; prediction model
- From: Journal of Clinical Medicine in Practice 2024;28(21):60-65
- CountryChina
- Language:Chinese
-
Abstract:
Objective To explore the pathogens status and risk factors for catheter-related infection in patients with maintenance hemodialysis (MHD), and to establish a prediction model. Methods A case-control study design was adopted, and clinical materials of 208 MHD patients treated in Suzhou Ninth People's Hospital of Suzhou University from June 2022 to March 2024 were retrospectively collected. The catheter-related infection status of the patients was analyzed, and they were divided into infection group and non-infection group based on the occurrence of catheter-related infections. The clinical materials were compared between the two groups. To avoid overfitting, the least absolute shrinkage and selection operator (LASSO) regression analysis was used for initial variable screening, followed by multivariate Logistic regression analysis to explore the risk factors for catheter-related infections in MHD patients. A predictive model was constructed based on the risk factors, and the area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess discrimination of the model. The
K -fold cross-validation method was applied for in-depth validation of the model. Results The incidence rate of catheter-related infection in the 208 MHD patients was 24.52% (51/208), including 22 cases of local catheter infections, 17 cases of tunnel infections, and 12 cases of catheter-related bloodstream infections. A total of 36 Gram-positive bacteria, 28 Gram-negative bacteria, and 1 fungus were isolated and cultured. Significant differences were observed between the infection and non-infection groups in terms of complicating diabetes, albumin level, catheter insertion site, catheter indwelling time, and catheter maintenance frequency (P < 0.05). LASSO regression analysis and multivariate Logistic regression analysis revealed that complicating diabetes (OR=3.651, 95%CI, 2.056 to 7.508), low albumin level (OR=1.782, 95%CI, 1.129 to 2.815), catheter insertion in the internal femoral vein (OR=2.298, 95%CI, 1.269 to 4.162), long catheter indwelling time (OR=2.959, 95%CI, 1.327 to 6.599), and catheter maintenance frequency ≤2 times per month (OR=2.373, 95%CI, 1.316 to 4.276) were independent risk factors for catheter-related infections in MHD patients (P < 0.05). The AUC of the predictive model based on independent risk factors was 0.885 (95%CI, 0.838 to 0.931), with a sensitivity of 0.875 and a specificity of 0.847. A hundred rounds ofK -fold cross-validation demonstrated good generalization ability of the model. Conclusion MHD patients have a high risk of catheter-related infections, and the constructed prediction model can effectively assess the risk of catheter-related infections in MHD patients.
