1. Postnatal urinary tract dilatation classification: improvement of the accuracy in predicting kidney injury
- Author
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Fernanda Ferreira de Oliveira Melo, Mariana A. Vasconcelos, Ludmila R Silva, Eduardo A Oliveira, Maria Christina L. Oliveira, Robert H. Mak, Cristiane S. Dias, Ana Cristina Simões e Silva, and Enrico A. Colosimo
- Subjects
Nephrology ,medicine.medical_specialty ,business.industry ,Urinary system ,medicine.disease ,Fetal hydronephrosis ,Internal medicine ,Pediatrics, Perinatology and Child Health ,medicine ,Antenatal Hydronephrosis ,Kidney injury ,Radiology ,business ,Grading (tumors) ,Surgical interventions ,Hydronephrosis - Abstract
The grading of urinary tract dilatation (UTD) on postnatal sonography is a fundamental step to establish rational management for infants with antenatal hydronephrosis (ANH). The aim of this study was to compare the prediction accuracy of UTD grading systems for relevant clinical outcomes. In addition, we propose a refinement of the UTD classification by adding quantitative measurements and evaluate its impact on accuracy. Between 1989 and 2019, 447 infants diagnosed with isolated AHN were prospectively followed. The events of interest were surgical interventions and kidney injury. Comparison of performance of the grading systems and the impact on the accuracy of a modified UTD classification (including the size of the kidney parenchyma) was assessed by the area under the receiver-operating characteristic curve (AUC). Of 447 infants, 131 (29%) underwent surgical intervention and 26 (5.8%) had developed kidney injury. The median follow-up time was 9 years (IQ range, 7–12 years). The performance for detecting the need for surgical intervention was excellent for all grading systems (AUC > 0.90). However, for predicting kidney injury, the modified UTD classification exhibited significant improvement in accuracy (AUC = 0.913, 95%CI, 0.883–0.937) as compared with UTD classification (AUC = 0.887, 95%CI, 0.854–0.915) (P = 0.027). Our study confirms that the hydronephrosis grading systems provide excellent accuracy in discriminating patients who need surgical intervention among infants with AHN. Our findings suggest that the inclusion of kidney parenchymal thickness to UTD classification might increase the accuracy for predicting infants who may develop kidney injury. A higher resolution version of the Graphical abstract is available as Supplementary information.
- Published
- 2021
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