Stratification of kidney damage severity in children with vesicoureteral reflux based on cluster analysis of imaging data

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Abstract

BACKGROUND: Vesicoureteral reflux is one of the most important risk factors for the development of urinary tract infections in children, leading to renal parenchymal injury. Assessment of the severity of vesicoureteral reflux based on imaging modalities does not always correlate with the reflux grade, which complicates the selection of patient management strategies.

AIM: The work aimed to evaluate the feasibility of using cluster analysis for stratification of the degree of structural and kidney function damage in children with vesicoureteral reflux based on imaging data.

METHODS: The study included 101 patients (143 renal units) aged 1 month to 7 years. Renal imaging methods were used, including Doppler ultrasound, static renal scintigraphy, and excretory urography. Clustering of the diagnostic dataset was performed using the TwoStep cluster method (SPSS Statistics, version 23.0; IBM, USA), which allows for simultaneous analysis of quantitative and qualitative variables. The optimal number of clusters was determined using the silhouette coefficient.

RESULTS: Cluster analysis identified four clusters of renal units (RUs): cluster 1, with no changes in renal structure, hemodynamics, or function (34 RUs); cluster 2, with minor changes and early signs of nephrosclerosis (55 RUs); cluster 3, with moderate impairment (45 RUs); and cluster 4, with pronounced changes in the renal parenchyma (9 RUs). A trend toward an increase in the number of renal units in clusters 3 and 4 with increasing grade of vesicoureteral reflux was observed: at grades 1–2, clusters 1 and 2 predominated; at grade 3, clusters 2 and 3; and at grades 4–5, cluster 4 predominated.

CONCLUSION: Cluster analysis of imaging data enabled stratification of the severity of kidney damage in children with vesicoureteral reflux using a multidimensional analytical approach.

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About the authors

Karmina N. Demidova

I.M. Sechenov First Moscow State Medical University

Author for correspondence.
Email: negmatova.karmina@mail.ru
ORCID iD: 0000-0002-2243-7073
SPIN-code: 9281-4273

MD, Cand. Sci. (Medicine)

Russian Federation, Moscow

Vera V. Rostovskaya

I.M. Sechenov First Moscow State Medical University; Speransky Children’s Hospital No. 9

Email: rostovskaya_vera@mail.ru
ORCID iD: 0000-0002-3718-8911
SPIN-code: 6989-5041

MD, Dr. Sci. (Medicine)

Russian Federation, Moscow; Moscow

Galina I. Kuzovleva

I.M. Sechenov First Moscow State Medical University; Speransky Children’s Hospital No. 9

Email: dr.gala@mail.ru
ORCID iD: 0000-0002-5957-7037
SPIN-code: 7990-4317

MD, Cand. Sci. (Medicine)

Russian Federation, Moscow; Moscow

Irina E. Starostina

DocMed Evidence-Based Medicine Clinic

Email: irinamadness1@gmail.com
ORCID iD: 0000-0002-3251-6904
Russian Federation, Moscow

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2. Fig. 1. Silhouette analysis of clustering quality of renal units at K = 4. The dashed line indicates the silhouette coefficient (s = 0.54).

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