# An Atlas of Nomograms, Scoring Systems, and Predictive Tools to Guide Investigation or Management in Patients with Suspected or Confirmed Vesicoureteral Reflux: A Comprehensive Review of the Literature

## TL;DR

This paper reviews existing tools for predicting outcomes and guiding treatment in children with vesicoureteral reflux, finding that no single tool is reliable enough for widespread use.

## Contribution

The paper provides the first comprehensive atlas of predictive tools for managing vesicoureteral reflux in children.

## Key findings

- Seventeen predictive tools were identified, but only five had external validation.
- Tools varied widely in design and reliability, limiting their general applicability.
- Future models should integrate clinical and radiological data with transparent methods for better risk stratification.

## Abstract

Background: Vesicoureteral reflux (VUR) contributes significantly to recurrent childhood urinary tract infections and renal scarring, yet predicting which patients will develop adverse outcomes or benefit from specific investigations or treatments remains challenging. Numerous prognostic tools have been proposed, but none have achieved widespread adoption. Methods: A comprehensive search of the literature available on MEDLINE, PUBMED, Embase, Emcare, CINAHL, and Google Scholar was performed to identify combinations of factors, scoring systems, ratios, models, and tools relating to VUR. This included predicting the spontaneous resolution of established vesicoureteral reflux, the risk of breakthrough urinary tract infections (UTIs), and guiding clinical decision making regarding the need for VCUG in patients with UTIs, continuous antibiotic prophylaxis (CAP), or surgical intervention in patients with confirmed VUR. Articles were included if they either described or validated a predictive tool that was designed to aid clinical decision making in patients with either suspected or confirmed VUR with regards to investigation or management strategies. All the studies included were then analysed, and the predictive tools have been summarised in a narrative format. Results: Seventeen predictive tools developed over thirty-nine years were identified: six predicting spontaneous resolution, four predicting breakthrough urinary tract infection (BTUTI) on CAP, two determining which children benefit from CAP, and five estimating the probability of VUR or high-grade VUR after a first febrile UTI. Approaches ranged from radiological ratios to multifactorial clinical–radiological scores and machine-learning models. Only five tools had any external validation, and none demonstrated sufficient reliability for universal clinical use. Significant heterogeneity in design, imaging interpretation, inclusion criteria, and outcome definitions limited comparison and wider applicability. Conclusions: This atlas provides the first consolidated overview of prognostic tools in paediatric VUR. Future development should prioritise multicentre, prospectively validated models that integrate established clinical and radiological predictors with transparent computational methods to create practical, generalisable risk-stratification frameworks for routine care.