Kayar Kemal, Kayar Ridvan, Tuncel Kayhan Gorkem, Tosun Cagatay, Yucebas Omer Ergin
Department of Urology, Haydarpasa Numune Training and Research Hospital, University of Health Sciences, Tibbiye Street. No: 23, Uskudar, Istanbul, 34668, Türkiye.
World J Urol. 2025 Jun 10;43(1):369. doi: 10.1007/s00345-025-05742-x.
Residual stone after Retrograde Intrarenal Surgery (RIRS) is a major challenge. This study evaluates key predictors of residual stones and develops a nomogram-based risk stratification model.
A retrospective analysis of 274 patients undergoing RIRS for renal calculi (2021-2024) was conducted. Demographic, clinical and radiological variables were assessed. Multivariate logistic regression and ROC curve analysis were used to identify predictors. A nomogram was developed and validated using Python libraries, with performance assessed via concordance index (C-index) and calibration plots.
Stone volume > 498 mm³ (AUC: 0.819, OR: 6.34, p < 0.001), IPA ≤ 44° (OR: 7.81, p = 0.005) and multiple stony calyces (OR: 2.38, p < 0.001) were the strongest predictors of residual stones. The nomogram demonstrated excellent discrimination (C-index: 0.839) and stratified patients into four risk categories (0-150 + points), with stone-free rates ranging from > 85% (low-risk) to < 40% (high-risk). ROC analysis highlighted stone volume (AUC: 0.819) as superior to stone size (AUC: 0.793).
The nomogram integrating stone volume, IPA and calyceal involvement provides a clinically usable tool for predicting residual stones post-RIRS. Preoperative use of this model may enhance surgical outcomes by guiding personalized treatment strategies and enables the surgeon to inform the patient more accurately about the expected outcome of the procedure.
逆行性肾内手术(RIRS)后残留结石是一项重大挑战。本研究评估残留结石的关键预测因素,并开发基于列线图的风险分层模型。
对2021年至2024年接受RIRS治疗肾结石的274例患者进行回顾性分析。评估人口统计学、临床和放射学变量。采用多因素逻辑回归和ROC曲线分析来识别预测因素。使用Python库开发并验证列线图,通过一致性指数(C指数)和校准图评估其性能。
结石体积>498 mm³(AUC:0.819,OR:6.34,p<0.001)、肾盂内移行角(IPA)≤44°(OR:7.81,p = 0.005)和多个结石性肾盏(OR:2.38,p<0.001)是残留结石的最强预测因素。列线图显示出良好的区分度(C指数:0.839),并将患者分为四个风险类别(0 - 150 +分),无结石率范围从>85%(低风险)到<40%(高风险)。ROC分析突出显示结石体积(AUC:0.819)优于结石大小(AUC:0.793)。
整合结石体积、IPA和肾盏受累情况的列线图为预测RIRS术后残留结石提供了一种临床可用工具。术前使用该模型可通过指导个性化治疗策略提高手术效果,并使外科医生能够更准确地告知患者手术的预期结果。