Abstract
BACKGROUND: In patients with end-stage renal disease (ESRD), vascular calcification significantly impairs hemodialysis (HD) vascular access functionality, compromising both dialysis efficacy and long-term patency. Early risk prediction of vascular calcification facilitates timely clinical interventions to preserve vascular access integrity. METHODS: A cross-sectional analysis was performed. Risk factors for vascular calcification in CKD patients were identified from the literature and Kidney Disease: Improving Global Outcomes guidelines. All variable selection and model training procedures were conducted on the training set. Univariate logistic regression was performed for all candidate variables. A nomogram was then constructed based on the final multivariate logistic model to facilitate clinical interpretation. RESULT: A total of 136 HD patients were included. The predictive model, relying on arteriovenous (AV) access usage time, hip circumference, and diabetes status, is reliable and clinically actionable tool for predicting AV access calcification. Its robust performance across validation and subgroup analyses supports its potential for integration into routine clinical practice. CONCLUSION: This study developed a nomogram-based predictive model for calcification, providing a simple, cost-effective, and reliable tool for early risk assessment. Monitoring hip circumference may serve as a practical approach for identifying high-risk patients, allowing for timely intervention and improved vascular access outcomes.