背景:评估泌尿外科超声在预测输尿管结石自发通过风险中的价值。
方法:连续收集输尿管结石保守治疗患者的临床和超声数据,随访1个月的自发传代结局。筛选与自发性结石通过风险独立相关的超声变量。基于独立危险因素构建Logistic回归预测模型,通过受试者工作特征(ROC)曲线评估预测模型在推断自发通过风险方面的判别效能和临床实用性,校准曲线和临床决策曲线。
结果:共有163名接受输尿管结石保守治疗的患者被纳入研究,平均年龄45.95±13.01岁。其中,47例(28.83%)自发性结石通道失败。多变量分析显示结石长度(OR:2.622,P=0.027),远端结石位置(OR:0.219,P=0.003),输尿管喷射频率(OR:6.541,P<0.001)是自发性结石通过的独立危险因素。结合石材长度的预测模型,石头位置,并制定了受影响的输尿管喷射频率,以评估自发性结石通过的风险。ROC曲线下面积为0.814(95%CI:0.747-0.882),具有良好的鉴别力。预测模型还显示出有利的净临床益处。
结论:基于超声衍生结石长度的预测模型,location,和输尿管喷射频率可以准确评估输尿管结石患者自发性结石通过的风险,为优化输尿管结石的临床决策提供依据,具有可靠的临床应用价值。
BACKGROUND: To assess the value of urological ultrasound in predicting the risk of spontaneous passage of ureteral stones.
METHODS: Clinical 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.
RESULTS: A 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.
CONCLUSIONS: A 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.