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Published on: June 21, 2024
Predictive value of the S.T.O.N.E. score for stone-free rate in impacted ureteral stones
Ahmet Burak Yilmaz1, Kamal Karimzada2, Tanju Keten2
1Department of Urology, Ministry of Health, Sincan Training and Research Hospital, Ankara, Turkey.
Abstract:
This study aims to evaluate the discriminative ability of the S.T.O.N.E. score for residual fragments following ureteroscopy and laser lithotripsy in patients with surgically confirmed impacted ureteral stones. We retrospectively analyzed 272 adult patients who underwent laser lithotripsy via semirigid ureteroscopy for impacted ureteral stones between January 2019 and January 2025. Preoperative computed tomography imaging was used to calculate the S.T.O.N.E. score, incorporating five parameters: stone size, location, hydronephrosis, number, and Hounsfield Unit value. Statistical analyses included ROC curve analysis and logistic regression to identify predictors of residual fragments. Among 272 patients, 202 (74.3%) achieved stone-free status, while 70 (25.7%) had residual fragments. Residual stone group had significantly higher median stone size, stone burden, Hounsfield Unit value, ureteral wall thickness, and hydronephrosis grade (all p < 0.001). Proximal location was more frequent in the residual stone group (p = 0.008). The S.T.O.N.E. score was significantly higher in residual stone group (p < 0.001). ROC analysis demonstrated good discriminative ability (AUC: 0.767; p < 0.001), with an optimal cut-off of > 9 provided optimal sensitivity (78%) and specificity (61%). In multivariate logistic regression, both the S.T.O.N.E. score (OR: 2.008; p < 0.001) and proximal/mid-ureteral stone location (OR: 4.107 and 3.543, respectively) were identified as independent predictors of residual fragments. The S.T.O.N.E. score is a reliable predictor of surgical outcomes in impacted ureteral stones treated with ureteroscopy and laser lithotripsy, and proximal or mid-ureteral locations are independently associated with lower stone free rate. These findings may support the integration of anatomical and composite scoring parameters into preoperative planning to optimize patient-specific surgical strategies.
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