Establishment of a risk prediction model for catheter-associated urinary tract infection in elderly critically ill patients
- VernacularTitle:老年重症患者导尿管相关尿路感染风险预测模型的构建
- Author:
Rui ZHU
1
;
Yali TIAN
;
Min HUANG
;
Minjuan CHU
Author Information
- Publication Type:Research Article
- Keywords: elderly critically ill people; catheter-associated urinary tract infection; Nomogram; prediction model
- From: Journal of Clinical Medicine in Practice 2024;28(24):143-148
- CountryChina
- Language:Chinese
-
Abstract:
Objective To analyze the risk factors for catheter-associated urinary tract infection (CAUTI) in elderly critically ill patients and construct a related risk prediction model. Methods Clinical materials of 8 905 patients with catheterization in the geriatric ICU ward of Jiangsu Provincial People's Hospital from January 2014 to June 2024 were retrospectively collected. The patients were divided into infection group (
n =114) and non-infection group (n =8 791) based on the occurrence of CAUTI. Multivariate Logistic regression analysis was used to identify the risk factors for CAUTI, and a Nomogram prediction model was constructed. Internal validation was performed by the receiver operating characteristic (ROC) curve, calibration curve, and Hosmer-Lemeshow goodness-of-fit test to assess the discrimination and calibration of the prediction model. Results In this study, the incidence of CAUTI in elderly critically ill patients was 2.55‰. Multivariate Logistic regression analysis showed that age, consciousness status, renal dysfunction, duration of catheterization, and the number of catheter insertions were independent influencing factors for CAUTI in elderly critically ill patients. A Nomogram model was constructed based on the results of the regression analysis. Area under the curve (AUC) of ROC curve for internal validation by the Bootstrap method was 0.802 (95%CI, 0.796 to 0.809). The calibration curve was close to the standard curve, and the predicted values were generally consistent with the actual values, demonstrating good predictive performance of the model. Conclusion Age, renal dysfunction, consciousness status, duration of catheterization, and the number of catheter insertions are independent influencing factors for CAUTI in elderly critically ill patients. Nomogram prediction model established based on these factors is simple and feasible, with reliable predictive performance.
