Development of a risk prediction model for dialysis access steal syndrome: exploring the interaction and modifying role of BMI

Background: Dialysis access steal syndrome (DASS) is a severe complication of vascular access surgery. This study aimed to identify key risk factors and develop an interpretable prediction model for early risk assessment in patients with end-stage renal disease (ESRD). Methods: This retrospective study analyzed 324 ESRD patients (March 2023-June 2025). Feature selection was performed using LASSO regression combined with SHapley Additive exPlanations (SHAP). Independent risk factors were identified via multivariable logistic regression, with robustness confirmed by sensitivity analysis and E-values. Restricted cubic splines (RCS) explored non-linear associations, while BMI-stratified and interaction analyses evaluated effect modification. Model performance was validated using AUC, 1000-sample bootstrapping, and 10-fold cross-validation. Results: < 0.001). Conclusion: FFS, sarcopenia, BMI, DAP, and CKD duration are core predictors of DASS. BMI acts as a key effect modifier, particularly influencing the impact of functional and hemodynamic indicators. This high-performance model provides a scientific basis for personalized preoperative screening and clinical intervention.