Deep learning imaging features derived from kidney ultrasounds predict chronic kidney disease progression in children with posterior urethral valves.

Background: We sought to use deep learning to extract anatomic features from postnatal kidney ultrasounds and evaluate their performance in predicting the risk and timing of chronic kidney disease (CKD) progression for boys with posterior urethral valves (PUV). We hypothesized that these features would predict CKD progression better than clinical characteristics such as nadir creatinine alone.

Methods: We performed a retrospective cohort study of boys with PUV treated at two pediatric health systems from 1990 to 2021.

The new epidemiology of nephrolithiasis.

Historically nephrolithiasis was considered a disease of dehydration and abnormal urine composition. However, over the past several decades, much has been learned about the epidemiology of this disease and its relation to patient demographic characteristics and common systemic diseases. Here we review the latest epidemiologic studies in the field.