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Clinical risk factors and machine learning-assisted interpretation of ureteral access sheath insertion failure: a
Yiping Zong1, Fan Ouyang2, Xiang Gao2
1Department of Urology, The Affiliated Yixing Hospital of Jiangsu University, Yixing, China.
Background:
In patients undergoing retrograde ureteroscopic lithotripsy, the failure rate of ureteral access sheath insertion is approximately 10%. Temporary double-J stenting with delayed secondary intervention is usually required when insertion fails. However, such cases cannot be reliably identified based on routine preoperative imaging. This study aimed to identify risk factors associated with ureteral access sheath (UAS) insertion failure.
Methods:
This retrospective multicenter study included patients who underwent retrograde intrarenal surgery for urolithiasis between January 2025 and December 2025 at six urological centers. Multivariable logistic regression was used as the primary analysis to identify factors associated with UAS insertion failure. An XGBoost model was additionally constructed, and SHapley Additive exPlanations (SHAP) were used to visualize the contribution and direction of included predictors. A systematic review and meta-analysis were further performed to synthesize previous evidence regarding relevant risk factors.
Results:
A total of 792 patients were included, of whom 153 patients experienced UAS insertion failure. Multivariable logistic regression identified stone history length, hydronephrosis, age, and stone-size parameters as factors associated with UAS insertion failure. Stone location, particularly proximal ureteral location, showed a risk-increasing pattern in univariable analysis, SHAP interpretation, and meta-analysis. XGBoost and logistic regression showed comparable discrimination in the test cohort, with AUCs of 0.724 and 0.692, respectively. SHAP analysis provided complementary feature-level visualization of predictor contribution and direction. The meta-analysis further supported the association between proximal ureteral location and UAS insertion failure, while the effects of stone history and sex were less consistent.
Conclusions:
UAS insertion failure was associated with hydronephrosis, stone-size parameters, and stone history length, with age requiring cautious interpretation. Proximal ureteral stone location may provide additional clinical information when interpreted together with other stone-related factors. SHAP-based visualization and meta-analysis offered complementary evidence to the regression-based findings. These results may support individualized preoperative assessment before attempted placement of a planned 11/13F UAS.
