ArticleResearch and reports in urology2025
Assessing the Predictive Accuracy of the S.T.O.N.E. Score for Stone-Free Rates in Semirigid Pneumatic Ureteral Lithotripsy: Implications for Validation.
Article in Research and reports in urology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Can AI and predictive models accurately predict stone-free status? a systematic review and meta-analysis.The Canadian journal of urology · 2026Pooled it
- Article
- Enhancing Percutaneous Access: The «GENOA» Prone Modified Position.Research and reports in urology · 2026Article
- Predictive value of the S.T.O.N.E. score for stone-free rate in impacted ureteral stones.Urolithiasis · 2025Article
- Review
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6 authors.
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Abstract
Background: The lack of reliable predictive tools for outcomes following ureteral lithotripsy (ULT) presents significant challenges in clinical decision-making. This study evaluates the efficacy of the S.T.O.N.E. score-an assessment incorporating Size, Topography, Obstruction, Number, and Hounsfield units (HU)-in predicting the likelihood of achieving a stone-free rate (SFR) in patients undergoing semirigid pneumatic ULT. Methods: This retrospective analysis involved 266 patients with ureteral stones who underwent ULT at IBB University Hospitals from April 2021 to September 2023. The S.T.O.N.E. score was derived from preoperative CT scans, and a nomogram was created to predict SFR failure. Discrimination and calibration were assessed using the area under the receiver operating characteristic curve (AUC) and calibration curve, while decision curve analysis (DCA) evaluated clinical utility. Results: The cohort's mean age was 47.7 ± 15 years, with a predominance of males (72.2%). The mean S.T.O.N.E. score was 7.8 ± 1.8. The overall SFR of 85.3% and residual stones were detected in 39 patients (14.7%). Multivariate analysis identified higher HU (AOR: 1.01; 95% CI: 1.00-1.01; P < 0.001), proximal stone location (AOR: 15.13; 95% CI: 1.52-51.13; P = 0.020), moderate (AOR: 34.23; 95% CI: 8.28-141.45; P < 0.001) and severe hydronephrosis (AOR: 33.75; 95% CI: 4.55-250.36; P = 0.0006), and larger stone size (AOR: 1.51; 95% CI: 1.30-1.75; P < 0.0001) as significant predictors of SFR failure. The S.T.O.N.E. score effectively predicts SFR failure, with an optimal threshold of > 8 achieving 85.0% accuracy. The model demonstrated 72.0% sensitivity, 81.0% specificity, and strong calibration. DCA indicated clinical utility, differentiating between low- and high-risk patients based on their S.T.O.N.E. scores. Conclusion: The S.T.O.N.E. score is a valuable tool for predicting post-ULT SFR, aiding preoperative decision-making and potentially improving surgical outcomes by identifying high-risk patients. Further validation in diverse populations is needed to confirm its clinical utility.
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