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剪切波弹性成像与肾功能生物标志物对慢性肾脏病患者肾纤维化预测的综合评估

Integrative evaluation of shear wave elastography and renal function biomarkers for predicting renal fibrosis in chronic kidney disease patients.

作者信息

Wang Jiexin, Zhou Honglian, Xu Xiaohong, Yang Yuping, Huang Qiang, Zheng Shixing, Ye Qiurong

机构信息

Department of Ultrasound, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.

出版信息

Sci Prog. 2025 Jul-Sep;108(3):368504251363483. doi: 10.1177/00368504251363483. Epub 2025 Aug 17.

Abstract

ObjectiveWe hypothesize that combining point shear wave elastography (PSWE) with clinical risk factors enables accurate renal fibrosis assessment. This retrospective study integrates PSWE with serum creatinine (Scr) and estimated glomerular filtration rate (eGFR) to develop and validate a nomogram for personalized renal fibrosis evaluation in chronic kidney disease (CKD) patients.MethodsA total of 157 patients underwent renal PSWE and kidney biopsy. PSWE measured cortical stiffness in the mid-portion of the right kidney. Feature importance was selected using elastic net regression, XGBoost, and random forest, with PSWE, Scr, and eGFR identified as key variables. Three models were established: Model 1 (PSWE + Scr + eGFR), Model 2 (Scr + eGFR), and Model 3 (PSWE). Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC) values. A nomogram based on PSWE, Scr, and eGFR was developed for precise fibrosis risk assessment. The Hosmer-Lemeshow test and K-fold cross-validation were used to evaluate the nomogram's generalizability.ResultsModel 1 achieved an AUC of 0.928, outperforming Model 2 (AUC = 0.878) and Model 3 (AUC = 0.824). The Hosmer-Lemeshow test yielded a -value of .7969, and K-fold cross-validation showed an accuracy of 0.8419 and a Kappa value of 0.6780.ConclusionPSWE combined with Scr and eGFR enhances diagnostic accuracy in differentiating renal fibrosis severity in CKD patients, aiding clinicians in making precise clinical decisions. The PSWE-based nomogram demonstrates excellent performance in predicting renal fibrosis severity.

摘要

目的

我们假设将点剪切波弹性成像(PSWE)与临床风险因素相结合能够实现准确的肾纤维化评估。这项回顾性研究将PSWE与血清肌酐(Scr)和估计肾小球滤过率(eGFR)相结合,以开发并验证用于慢性肾脏病(CKD)患者个性化肾纤维化评估的列线图。

方法

共有157例患者接受了肾脏PSWE检查和肾活检。PSWE测量右肾中部的皮质硬度。使用弹性网络回归、XGBoost和随机森林选择特征重要性,确定PSWE、Scr和eGFR为关键变量。建立了三个模型:模型1(PSWE + Scr + eGFR)、模型2(Scr + eGFR)和模型3(PSWE)。使用受试者操作特征(ROC)曲线和曲线下面积(AUC)值评估诊断性能。基于PSWE、Scr和eGFR开发了列线图用于精确的纤维化风险评估。使用Hosmer-Lemeshow检验和K折交叉验证来评估列线图的可推广性。

结果

模型1的AUC为0.928,优于模型2(AUC = 0.878)和模型3(AUC = 0.824)。Hosmer-Lemeshow检验的P值为0.7969,K折交叉验证显示准确率为0.8419,Kappa值为0.6780。

结论

PSWE与Scr和eGFR相结合可提高区分CKD患者肾纤维化严重程度的诊断准确性,有助于临床医生做出精确的临床决策。基于PSWE的列线图在预测肾纤维化严重程度方面表现出色。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b900/12361741/2462e391c5fe/10.1177_00368504251363483-fig1.jpg

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