ArticleBMC urology2024
Applying urinary ultrasound to predict the risk of spontaneous ureteral stone passage: a retrospective cohort study.
Article in BMC urology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Proximal/Distal ureteral diameter ratio as a predictor of spontaneous passage in <10 mm ureteral stones.The Canadian journal of urology · 2026Article
- Applying urinary ultrasound combined with CT to predict the risk of spontaneous ureteral stone passage.BMC urology · 2025Article
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Authors and funding
6 authors.
Funding
Abstract
backgroundTo assess the value of urological ultrasound in predicting the risk of spontaneous passage of ureteral stones.
methodsClinical and ultrasound data were collected consecutively from patients receiving conservative treatment for ureteral stones, and the outcome of spontaneous passage was followed up for 1 month. Ultrasound variables independently associated with the risk of spontaneous stone passage were screened. A logistic regression prediction model was constructed based on the independent risk factors, and the discriminative efficacy and clinical utility of the prediction model in inferring the risk of spontaneous passing were assessed by the receiver operating characteristic (ROC) curve, calibration curve and clinical decision curve.
resultsA total of 163 patients undergoing conservative treatment for ureteral stones were included in the study, with a mean age of 45.95 ± 13.01 years. Among them, 47 cases (28.83%) experienced failure of spontaneous stone passage. Multivariable analysis revealed that stone length (OR: 2.622, P = 0.027), distal stone location (OR: 0.219, P = 0.003), and ureteral jetting frequency (OR: 6.541, P < 0.001) were independent risk factors for spontaneous stone passage. A prediction model incorporating stone length, stone location, and affected ureteral jetting frequency was developed to assess the risk of spontaneous stone passage. The area under the ROC curve was 0.814 (95% CI: 0.747-0.882), indicating good discriminatory power. The prediction model also demonstrated favorable net clinical benefit.
conclusionA prediction model based on ultrasound-derived stone length, location, and ureteral jetting frequency can accurately evaluate the risk of spontaneous stone passage in patients with ureteral stones, providing a basis for optimizing the clinical decision-making on ureteral stones, and has reliable clinical application value.
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