He Quanfang, Wang Peichang, Yang Huaxu, Tang Hua, Lan Lixiang, Chen Shaoting
Department of Urology, Fudan University Shanghai Cancer Center Xiamen Hospital, Xiamen, 361000, Fujian, China.
Department of Urology, Longyan People's Hospital, affiliated with Xiamen Medical College, Longyan, 364000, Fujian, China.
World J Urol. 2025 Sep 9;43(1):547. doi: 10.1007/s00345-025-05909-6.
To develop and validate a prognostic nomogram for predicting the risk of proximal ureteral impacted calculi, supporting personalized clinical management.
This retrospective, multicenter study employed a continuous cohort of 391 patients with proximal ureteral stones treated between January 2021 and April 2024. Data from Longyan People's Hospital (affiliated with Xiamen Medical College) comprised the training set, while independent external validation was performed using data from The Fifth Affiliated Hospital of Fujian University of Traditional Chinese Medicine. Independent predictors were ascertained via univariate and multivariate logistic regression analysis. A nomogram was subsequently developed, and its predictive performance and clinical utility were evaluated.
Hydronephrosis (OR = 3.911, 95% CI: 1.152-13.227, P = 0.044), maximum ureteral wall thickness (UWT) (OR = 9.574, 95% CI: 5.775-15.874, P < 0.001), maximum ureteral jet velocity (Vmax) (OR = 0.762, 95% CI: 0.677-0.858, P < 0.001), stone Hounsfield units (HU) (OR = 2.228, 95% CI: 1.207-4.114, P = 0.002), and stone size (OR = 2.069, 95% CI: 1.128-3.796, P = 0.019) emerged as significant independent predictors of impacted proximal ureteral calculi. The nomogram exhibited high predictive accuracy, with area under the receiver operating characteristic curve (AUC) values of 0.928 (training set) and 0.903 (validation set). Decision curve analysis indicated substantial net clinical benefit across a range of threshold probabilities for clinical use.
Hydronephrosis, UWT, Vmax, stone HU, and stone size constitute independent predictors of proximal ureteral impacted calculi. The nomogram incorporating these factors provides a reliable prognostic tool to assist in treatment planning and potentially enhance patient outcomes in clinical practice.
开发并验证一种用于预测近端输尿管结石嵌顿风险的预后列线图，以支持个性化临床管理。
这项回顾性多中心研究纳入了2021年1月至2024年4月期间接受治疗的391例近端输尿管结石患者的连续队列。来自龙岩市人民医院（厦门医学院附属）的数据构成训练集，同时使用福建中医药大学附属第五人民医院的数据进行独立外部验证。通过单因素和多因素逻辑回归分析确定独立预测因素。随后开发了列线图，并评估其预测性能和临床效用。
肾积水（OR = 3.911，95% CI：1.152 - 13.227，P = 0.044）、输尿管壁最大厚度（UWT）（OR = 9.574，95% CI：5.775 - 15.874，P < 0.001）、输尿管最大喷射速度（Vmax）（OR = 0.762，95% CI：0.677 - 0.858，P < 0.001）、结石亨氏单位（HU）（OR = 2.228，95% CI：1.207 - 4.114，P = 0.002）和结石大小（OR = 2.069，95% CI：1.128 - 3.796，P = 0.019）成为近端输尿管结石嵌顿的显著独立预测因素。列线图显示出高预测准确性，受试者工作特征曲线（AUC）下面积在训练集中为0.928，在验证集中为0.903。决策曲线分析表明，在一系列临床使用的阈值概率范围内具有显著的净临床效益。
肾积水、UWT、Vmax、结石HU和结石大小是近端输尿管结石嵌顿的独立预测因素。纳入这些因素的列线图提供了一种可靠的预后工具，有助于临床实践中的治疗规划并可能改善患者预后。
