Renal failure · 2025
Analysis of arteriovenous fistula failure factors and construction of nomogram prediction model in patients with maintenance hemodialysis.
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Guo Shengjie, Wang Yurou, Zou Chao, Liu Liping, He Tingting, Sun Chengcheng, Gan Xiaosu, Tian Xiaofang, Yuan Liying
Аннотация
OBJECTIVES: Autogenous arteriovenous fistula (AVF) is a commonly used vascular access for maintenance hemodialysis (MHD), and its failure significantly impacts the quality of dialysis and patient prognosis. The purpose of this study was to analyze the factors associated with AVF failure in MHD patients and to establish a nomogram prediction model.
METHODS: Data on end-stage renal disease (ESRD) patients undergoing MHD at our hemodialysis center were retrospectively collected and analyzed. Lasso regression analysis was employed to identify independent risk factors, and a nomogram model was developed to predict the risk of AVF failure in MHD patients. ROC curve analysis, the Hosmer-Lemeshow test, and decision curve analysis were utilized for model validation.
RESULTS: The study ultimately included 223 patients, and 6 independent factors influencing AVF failure were analyzed. The constructed nomogram model demonstrated good predictive power, with areas under the curve of 0.834 (95% CI 0.762-0.907) and 0.806 (95% CI 0.701-0.911) for the training and validation sets, respectively. The p-values obtained for the Hosmer-Lemeshow test were 0.896 and 0.257. The nomograms exhibited a higher net clinical benefit in both clinical decision curves.
CONCLUSIONS: This study identifies the key factors influencing AVF failure in MHD patients and establishes a validated prediction model using nomogram, providing clinical practice with an accurate visualization tool for the early identification and guidance of clinical decisions.
METHODS: Data on end-stage renal disease (ESRD) patients undergoing MHD at our hemodialysis center were retrospectively collected and analyzed. Lasso regression analysis was employed to identify independent risk factors, and a nomogram model was developed to predict the risk of AVF failure in MHD patients. ROC curve analysis, the Hosmer-Lemeshow test, and decision curve analysis were utilized for model validation.
RESULTS: The study ultimately included 223 patients, and 6 independent factors influencing AVF failure were analyzed. The constructed nomogram model demonstrated good predictive power, with areas under the curve of 0.834 (95% CI 0.762-0.907) and 0.806 (95% CI 0.701-0.911) for the training and validation sets, respectively. The p-values obtained for the Hosmer-Lemeshow test were 0.896 and 0.257. The nomograms exhibited a higher net clinical benefit in both clinical decision curves.
CONCLUSIONS: This study identifies the key factors influencing AVF failure in MHD patients and establishes a validated prediction model using nomogram, providing clinical practice with an accurate visualization tool for the early identification and guidance of clinical decisions.