Evidence map›Paper›PMID 42177688›Full record

ArticleWorld journal of urology2026

Does vesicoureteral reflux severity impact breakthrough UTI risk: a multi-institutional analysis and risk stratification.

Adree Khondker, Jethro Cc Kwong, Priyank Yadav, Jin K Kim, Ihtisham Ahmad, M S Ansari, Emily MacNeil, Daniel T Keefe, Laura Lorenger, Isabella Reyes and 4 more

Abstract readMulticenter Study
PubMed Publisher
In one paragraph

Article in World journal of urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Adree KhondkerDivision of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada.
Jethro Cc KwongDivision of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada.
Priyank YadavDivision of Urology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada.
Jin K KimDivision of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada.
Ihtisham AhmadTemerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
M S AnsariDepartment of Urology and Renal Transplantation, Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India.
Emily MacNeilDepartment of Surgery, IWK Hospital, Halifax, NS, Canada.
Daniel T KeefeDepartment of Surgery, IWK Hospital, Halifax, NS, Canada.
Laura LorengerDepartment of Urology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Isabella ReyesDepartment of Urology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Lauren ErdmanDepartment of Computer Science, University of Toronto, Toronto, ON, Canada.
Christopher S CooperDepartment of Urology, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
Mandy RickardDivision of Urology, The Hospital for Sick Children, 555 University Avenue, Toronto, ON, M5G 1X8, Canada.
Armando J LorenzoDivision of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada. armando.lorenzo@sickkids.ca.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundVesicoureteral reflux (VUR) is a common urological disorder in children. To date, VUR severity is assessed by grading, and contemporary models have expanded on developing predictors for breakthrough UTI (bUTI) in VUR. Here, we developed models to predict the risk of bUTI in children with VUR using clinical features, combined with traditional VUR grading or novel quantitative VUR (qVUR) measures. MATERIALS AND

methodsAn international multi-institutional retrospective cohort database between 2015 and 2022, including four pediatric centers, was queried for VUR cases with available voiding cystourethrograms (VCUG). Each VCUG was reviewed, and VUR grade and qVUR features (including ureteral tortuosity and dilatation) were assigned by multiple raters. The outcome of interest, development of bUTI, was analyzed using multivariable Cox proportional hazards and boosted Cox regression. The models were trained and externally validated to provide individualized survival curves. Model performance, calibration, and net benefit were assessed.

resultsSix hundred eighty-four children were included in this study (308 training, 376 validation), of which 109 (16%) experienced a bUTI within the study period. Age, sex, VUR grade, and ureteral dilation were associated with bUTI on survival analysis. The qVUR-based Cox regression and boosted Cox models performed with c-indices of 0.64 (95%CI 0.60, 0.68) and 0.75 (95%CI 0.67, 0.80), both superior to VUR-based models. qVUR-based Cox models provided improved calibration, and net benefit. The bUTI risk algorithm, based on the Cox model, is available in a free-to-use web application ( https://sickkidsurology.shinyapps.io/qVUR-bUTI/ ).

conclusionsOur findings suggest that individualized bUTI risk assessment incorporating an objective measure of VUR severity can be modelled with modest performance. With further works, qVUR holds promise in refining predictive models in VUR.

Indexed as

Urinary Tract InfectionsVesico-Ureteral RefluxChildChild, PreschoolFemaleHumansInfantMaleRetrospective StudiesRisk AssessmentSeverity of Illness IndexAntibiotic prophylaxisArtificial intelligenceMachine learningUrinary tract infectionVesicoureteral reflux

Identifiers

PMID42177688

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.