Yin Xiaoming, Li Jia, Pan Chunyu, Liu Gang, Li Zhenhua, Bai Song
Department of Pediatric Urology, Shengjing Hospital of China Medical University, Shenyang, People's Republic of China.
Department of Urology, Shengjing Hospital of China Medical University, 36 Sanhao Street, Shenyang, 110004, Liaoning, People's Republic of China.
World J Urol. 2023 May;41(5):1431-1436. doi: 10.1007/s00345-023-04358-3. Epub 2023 Mar 13.
To develop and validate a nomogram for predicting stone-free failure after shock wave lithotripsy (SWL) guided by ultrasound in patients with ureteral stones.
The development cohort consisted of 1698 patients who underwent SWL guided by ultrasound at our center from June 2020 through August 2021. Multivariate unconditional logistic regression analysis was used for building a predictive nomogram with regression coefficients. An independent validation cohort consisted of 712 consecutive patients from September 2020 through April 2021. The performance of the predictive model was assessed in regard to discrimination, calibration, and clinical usefulness.
Predictors of stone-free failure included distal stone location (odds ratio = 1.540, P < 0.001), larger stone size (odds ratio = 1.722, P < 0.001), higher stone density (odds ratio = 1.722, P < 0.001), larger skin to stone distance (SSD) (odds ratio = 1.058, P < 0.001), and higher grade of hydronephrosis (odds ratio = 1.755, P = 0.010). For the validation cohort, the model showed good discrimination with an area under the receiver operating characteristic curve of 0.925 (95% confidence interval, 0.898, 0.953) and good calibration (unreliability test, P = 0.412). Decision curve analysis demonstrated that the model was also clinically useful.
This study demonstrated that stone location, stone size, stone density, SSD, and hydronephrosis grade were significant predictors of stone-free failure after SWL guided by ultrasound in patients with ureteral stones. This may guide clinical practice.
开发并验证一种列线图,用于预测输尿管结石患者在超声引导下进行冲击波碎石术(SWL)后结石清除失败的情况。
开发队列包括2020年6月至2021年8月在本中心接受超声引导下SWL的1698例患者。采用多变量无条件逻辑回归分析,利用回归系数构建预测列线图。独立验证队列包括2020年9月至2021年4月连续纳入的712例患者。从区分度、校准度和临床实用性方面评估预测模型的性能。
结石清除失败的预测因素包括结石位于远端(比值比=1.540,P<0.001)、结石体积较大(比值比=1.722,P<0.001)、结石密度较高(比值比=1.722,P<0.001)、皮肤至结石距离(SSD)较大(比值比=1.058,P<0.001)以及肾积水程度较高(比值比=1.755,P=0.010)。对于验证队列,该模型表现出良好的区分度,受试者操作特征曲线下面积为0.925(95%置信区间,0.898,0.953),校准度良好(失拟检验,P=0.412)。决策曲线分析表明该模型在临床上也具有实用性。
本研究表明,结石位置、结石大小、结石密度、SSD和肾积水程度是输尿管结石患者在超声引导下进行SWL后结石清除失败的重要预测因素。这可能会为临床实践提供指导。