ArticleFrontiers in medicine2026
Development and validation of an interpretable prediction model for high-grade vesicoureteral reflux in children with urinary tract infections.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: High-grade vesicoureteral reflux (VUR) is prone to causing adverse clinical outcomes such as kidney damage, recurrent urinary tract infections, and hypertension. Early identification of the risk of developing high-grade VUR in children with urinary tract infections is of great significance for reducing unnecessary voiding cystourethrography (VCUG), guiding clinical decisions, and optimizing antibiotic management strategies. Methods: A total of 434 children with urinary tract infections who completed VCUG examination were retrospectively enrolled in this study. They were randomly divided into a training set ( Results: Among the 434 patients, 156 individuals (35.9%) were diagnosed with grade ≥ 3 VUR. Seven predictive features were identified: delayed treatment response, annual UTI episodes, hydronephrosis, abnormal renal signal on MRU, febrile UTI (fUTI)/UTI ratio, age at first UTI, and non-Escherichia coli UTI episodes. Discrimination performance was comparable across the six models (test AUC range: 0.810-0.832; all pairwise DeLong tests Conclusions: We developed and validated a prediction model based on XGBoost, which can be used to assess the risk of high-grade vesicoureteral reflux in children with urinary tract infections. This model has good discrimination, acceptable calibration, and considerable clinical application potential. Additionally, based on this model, we developed and deployed a free online calculator at https://vur-prediction.yezhiqiu.cn, which can assist in real-time individualized risk assessment.
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