{"title":"Integrative evaluation of shear wave elastography and renal function biomarkers for predicting renal fibrosis in chronic kidney disease patients.","authors":"Jiexin Wang, Honglian Zhou, Xiaohong Xu, Yuping Yang, Qiang Huang, Shixing Zheng, Qiurong Ye","doi":"10.1177/00368504251363483","DOIUrl":null,"url":null,"abstract":"<p><p>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 <i>P</i>-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.</p>","PeriodicalId":56061,"journal":{"name":"Science Progress","volume":"108 3","pages":"368504251363483"},"PeriodicalIF":2.9000,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12361741/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science Progress","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1177/00368504251363483","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/8/17 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
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 P-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.
期刊介绍:
Science Progress has for over 100 years been a highly regarded review publication in science, technology and medicine. Its objective is to excite the readers'' interest in areas with which they may not be fully familiar but which could facilitate their interest, or even activity, in a cognate field.