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Urinary tract dilation classification system for predicting surgical management and urinary tract infection in neonates and young infants: a systematic review and meta-analysis

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Abstract

Background

The urinary tract dilation classification system has recently been developed to ensure a unified approach to describe urinary tract dilation in neonates and young infants. However, the predictive value of this system for surgical intervention or urinary tract infection (UTI) has not yet been evaluated in a meta-analysis.

Objective

This systematic review and meta-analysis aimed to evaluate the utility of a postnatal urinary tract dilation classification system for predicting surgical management or a UTI occurrence.

Materials and methods

As the urinary tract dilation classification system was introduced in 2014, we searched Embase and PubMed databases for studies published between January 2014 and December 2022. Original articles that reported surgical interventions or UTI episodes according to postnatal urinary tract dilation grades were included. The pooled odds ratio (OR) was calculated, using either the fixed-effects or random-effects model, given the lower urinary tract dilation grades as the base category. The quality of the included studies was evaluated using the Newcastle–Ottawa scale.

Results

Of the 285 articles reviewed, eight (comprising 2,165 children) were included in the analysis. The studies were of medium-to-high quality. Pooled analysis demonstrated that urinary tract dilation P3 (combined OR, 21.41; 95% confidence interval [CI], 15.72–29.17) and urinary tract dilation P2–P3 (combined OR, 65.17; 95% CI, 33.08–128.38) were associated with surgical intervention. The urinary tract dilation P3 (combined OR, 2.11; 95% CI, 1.56–2.85) and urinary tract dilation P2–P3 (combined OR, 3.36; 95% CI, 2.43–4.63) were associated with UTI episodes.

Conclusion

The postnatal urinary tract dilation classification system is useful for predicting the need for surgical management and UTI episodes in infants with hydronephrosis.

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Data availability

The datasets used during the current study are available from the corresponding author on reasonable request.

Change history

  • 04 February 2024

    supplemenary file has been updated.

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Acknowledgements

We thank Hee Mang Yoon (Department of Radiology and Research Institute of Radiology, Asan Medical Center) for providing representative figures during manuscript revisions.

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Authors and Affiliations

  1. Department of Healthcare, Kakao Brain Co., Seongnam, Republic of Korea

    Hae Won Kim

  2. Department of Radiology, Ajou University Hospital, Ajou University School of Medicine, 164 World Cup-Ro, Yeongtong-Gu, Suwon, 16499, Republic of Korea

    Jisun Hwang

  3. Department of Pediatrics, Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea

    Ki Soo Pai & Yoong-a Suh

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  1. Hae Won Kim
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Contributions

Material preparation, data collection, and analysis were performed by J.H. and H.W.K. The first draft of the manuscript was written by J.H., H.W.K., K.S.P., and Y.S. All authors reviewed and approved the final manuscript.

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Correspondence to Jisun Hwang.

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Kim, H.W., Hwang, J., Pai, K.S. et al. Urinary tract dilation classification system for predicting surgical management and urinary tract infection in neonates and young infants: a systematic review and meta-analysis. Pediatr Radiol 54, 795–804 (2024). https://doi.org/10.1007/s00247-024-05854-3

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