Development and validation of a risk prediction model for non-cuffed catheter dysfunction in hemodialysis patients
10.3761/j.issn.0254-1769.2025.19.002
- VernacularTitle:血液透析患者无涤纶套透析导管功能不良风险预测模型的构建与验证研究
- Author:
Haiqiang JIANG
1
;
Juan GONG
;
Shuang WU
;
Jia PENG
;
Chuanfang WU
Author Information
1. 421000 湖南省衡阳市 南华大学护理学院
- Publication Type:Journal Article
- Keywords:
Hemodialysis;
Non-Cuffed Catheter;
Dysfunction;
Risk Prediction Model;
Nursing Care
- From:
Chinese Journal of Nursing
2025;60(19):2313-2320
- CountryChina
- Language:Chinese
-
Abstract:
Objective To develop and validate a risk prediction model for non-cuffed catheter(NCC)dysfunction in hemodialysis patients,aiming to provide a reference for early clinical identification and warning.Methods A prospective study design was adopted.A total of 569 patients with indwelling NCC from the hemodialysis center of a tertiary hospital in Nanchang between December 1,2023 to May 20,2024,were included as a modeling cohort.An additional 172 patients from the hemodialysis center of a tertiary hospital in Changsha,enrolled between May 30 to October 20,2024,formed a validation cohort.Data were collected on general patient characteristics,dialysis information,catheterization details,and clinical parameters.The risk prediction model was constructed using a combination of variables identified through univariate analysis,Lasso regression,logistic regression,and the Boruta algorithm.Model performance was evaluated accordingly.Results The incidence of NCC dysfunction in hemodialysis patients was 44.94％.A total of 5 common predictors were identified by both algorithms,including age,ultrafiltration volume,catheter insertion site,catheter indwelling time,and C-reactive protein.The area under the receiver operating characteristic curve(AUC)was 0.720 for internal validation and 0.766 for external validation.The Brier scores for curve calibration were 0.213 and 0.203,respectively.The decision curve analysis showed clinical benefit within risk threshold ranges of 22％～82％and 22％～96％,respectively.Conclusion The risk prediction model developed in this study demonstrates good predictive performance and can serve as a screening and assessment tool for identifying the risk of NCC dysfunction in hemodialysis patients.
