Qi Qiao, Hu Yongtao, Hou Bingbing, Xia Kaiguo, Xu Yuexian, Liang Chaozhao, Hao Zongyao
Department of Urology, The First Affiliated Hospital of Anhui Medical University, Hefei, China.
Institute of Urology, Anhui Medical University, Hefei, China.
Transl Androl Urol. 2024 Sep 30;13(9):1946-1954. doi: 10.21037/tau-24-217. Epub 2024 Sep 26.
Urinary tract infection (UTI) is a common disease in urology and often occurs in patients with urolithiasis. This study aimed to identify the risk factors for UTI in patients with ureterolithiasis complicated with hydronephrosis, and to construct a simple and practical nomogram to predict the incidence of UTI for patients.
A total of 383 patients were enrolled from September 2019 to June 2022. The results from univariate and multivariate logistic regression showed the risk factors for predicting UTI and a prediction model was constructed. Subsequently, the differentiation, calibration, and clinical applicability of the model were estimated by receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA), respectively.
The study included 72 (18.80%) patients with UTI. Multivariate logistic regression showed that tissue rim sign (P=0.04), positive urinary nitrite (P<0.001), and positive urinary leukocyte esterase (P=0.005) were independent predictive indexes of UTI for patients with ureterolithiasis complicated with hydronephrosis, and a nomogram was constructed in accordance with these indicators. The area under the ROC curve was 0.773, which indicated good prediction ability. The Hosmer-Lemeshow test (P=0.97) indicated that the model fitted well. The calibration curve and DCA showed good consistency and clinical applicability, respectively.
The prediction model constructed with the risk factors including tissue rim sign, positive urinary nitrite, and positive urinary leukocyte esterase can better detect patients with UTI early and take timely intervention measures.
尿路感染（UTI）是泌尿外科的常见疾病，常发生于尿路结石患者。本研究旨在确定输尿管结石合并肾积水患者发生UTI的危险因素，并构建一个简单实用的列线图来预测患者UTI的发生率。
选取2019年9月至2022年6月期间的383例患者。单因素和多因素逻辑回归结果显示了预测UTI的危险因素，并构建了预测模型。随后，分别通过受试者工作特征（ROC）曲线分析、校准曲线和决策曲线分析（DCA）对模型的区分度、校准度和临床适用性进行评估。
该研究纳入了72例（18.80%）UTI患者。多因素逻辑回归显示，组织边缘征（P=0.04）、尿亚硝酸盐阳性（P<0.001）和尿白细胞酯酶阳性（P=0.005）是输尿管结石合并肾积水患者UTI的独立预测指标，并据此构建了列线图。ROC曲线下面积为0.773，表明预测能力良好。Hosmer-Lemeshow检验（P=0.97）表明模型拟合良好。校准曲线和DCA分别显示出良好的一致性和临床适用性。
由组织边缘征、尿亚硝酸盐阳性和尿白细胞酯酶阳性等危险因素构建的预测模型能够更好地早期检测出UTI患者，并及时采取干预措施。
