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Predicting outcomes in children with congenital anomalies of the kidney and urinary tract

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Abstract

Background

Congenital anomalies of the kidney and urinary tract (CAKUT) are the most frequent causes of childhood chronic kidney disease (CKD). Using a large CAKUT cohort, we sought to identify the predictors of CKD and to develop a prediction model that informs a risk-stratified clinical pathway.

Methods

This was a retrospective cohort study including cases with multicystic dysplastic kidneys (MCDK), unilateral kidney agenesis (UKA), kidney hypoplasia (KH), and posterior urethral valves (PUV). We identified risk factors for CKD (estimated glomerular filtration rate [eGFR] <60 ml/min/1.73 m2) and tested their performance in an adjusted multivariate binary regression model. Prediction probability scores for CKD were used to separate cases likely to develop complications from those not needing specialist follow-up.

Results

We identified 452 eligible cases of CAKUT with 22% developing CKD. Strongest associations with CKD included primary diagnosis (OR 3.5, 95% CI 2.6–4.6), preterm delivery (OR 2.3, 95% CI 1.2–4.4), non-kidney anomalies (OR 1.8, 95% CI 1.1–3), first eGFR<90 (OR 8.9, 95% CI 4.4–18.1), small kidney size (OR 9, 95% CI 4.9–16.6), and additional kidney anomalies (OR 1.6, 95% CI 1.2–2.8). PUV (OR 4.7, 95% CI 1.5–15.3), first eGFR <90 (OR 4.4, 95% CI 2–9.7), and kidney length to body length ratio <7.9 (OR 4.2, 95% CI 1.9–9.2) were independent predictors of CKD. The regression model had a prediction accuracy of 80% and a prediction probability c-statistic of 0.81.

Conclusion

Using a large combined CAKUT cohort we identified risk factors for CKD. Our prediction model provides the first steps towards a risk-stratified clinical pathway.

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Data availability

The data that support the findings of this study are not openly available due to reasons of sensitivity and patient confidentiality. Anonymized and de-identified data are available from the corresponding author upon reasonable request.

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Funding

B.B. is supported by 5R01DK125469 (U.S. National Institutes of Health, NIDDK).

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Authors and Affiliations

  1. University of British Columbia, British Columbia Children’s Hospital Research Institute, Vancouver, BC, Canada

    Douglas G. Matsell & Marisa Catapang

  2. Kidney and Urinary Tract Center, Abigail Wexner Research Institute at Nationwide Children’s Hospital, Columbus, Ohio, USA

    Brian Becknell

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  1. Douglas G. Matsell
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  2. Marisa Catapang
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Correspondence to Douglas G. Matsell.

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Matsell, D.G., Catapang, M. & Becknell, B. Predicting outcomes in children with congenital anomalies of the kidney and urinary tract. Pediatr Nephrol 38, 3407–3415 (2023). https://doi.org/10.1007/s00467-023-05992-0

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