First name
Neeta
Last name
D'Souza

Title

Assessing the utility of tamsulosin in delaying progression to clean intermittent catheterization and end-stage renal disease in patients with posterior urethral valves: Are we postponing the inevitable?

Year of Publication

2023

Date Published

06/2023

ISSN Number

1527-9995

Abstract

OBJECTIVE: To assess whether tamsulosin may aid emptying of the lower urinary tract in posterior urethral valves (PUV) patients, mitigating the likelihood of progressing to clean intermittent catheterization (CIC) or need for renal replacement therapy.

METHODS: We reviewed a prospective institutional database containing PUV patients treated between January 2000-January 2022. After assessing baseline characteristics, Kaplan-Meier survival curves and log-rank tests were generated to assess differences in clinically significant outcomes (progression to CIC, dialysis, or kidney transplantation) between those prescribed tamsulosin and those who were not.

RESULTS: A total of 179 patients were included. Fifty-nine patients received tamsulosin prior to initiation of CIC (Group 1), and 120 did not (Group 2). The baseline characteristics were similar between the two groups, except for anticholinergic use (tamsulosin group - 35/59 vs. no tamsulosin - 32/120, p<0.001). The median age at tamsulosin initiation was 26.0 months (IQR 15.5-48.6) and the median time from initiation of tamsulosin to progression to CIC was 52.6 months (IQR 10.1-69.3). Kaplan-Meier survival curves showed that patients on tamsulosin were less likely to progress to CIC (p=0.021), however, there was no difference in progression to dialysis or kidney transplantation. A Cox-regression analysis controlling for baseline characteristics, including age, anticholinergic use, VUR severity, and CKD stage at 1-year of life, showed a consistent effect of tamsulosin in delaying progression to CIC (HR 0.444 95%CI 0.218-0.902, p=0.025).

CONCLUSION: While tamsulosin may delay CIC, it does not appear to delay progression to end-stage renal disease. Additional studies exploring specific patient factors are required to determine the timing and subset who may benefit the most from tamsulosin.

DOI

10.1016/j.urology.2023.05.034

Alternate Title

Urology

PMID

37348660
Featured Publication
No

Title

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

Year of Publication

2022

Date Published

07/2022

ISSN Number

1432-198X

Abstract

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. Features of kidneys were extracted from initial postnatal kidney ultrasound images using a deep learning model. Three time-to-event prediction models were built using random survival forests. The Imaging Model included deep learning imaging features, the Clinical Model included clinical data, and the Ensemble Model combined imaging features and clinical data. Separate models were built to include time-dependent clinical data that were available at 6 months, 1 year, 3 years, and 5 years.

RESULTS: Two-hundred and twenty-five patients were included in the analysis. All models performed well with C-indices of 0.7 or greater. The Clinical Model outperformed the Imaging Model at all time points with nadir creatinine driving the performance of the Clinical Model. Combining the 6-month Imaging Model (C-index 0.7; 95% confidence interval [CI] 0.6, 0.79) with the 6-month Clinical Model (C-index 0.79; 95% CI 0.71, 0.86) resulted in a 6-month Ensemble Model that performed better (C-index 0.82; 95% CI 0.77, 0.88) than either model alone.

CONCLUSIONS: Deep learning imaging features extracted from initial postnatal kidney ultrasounds may improve early prediction of CKD progression among children with PUV. A higher resolution version of the Graphical abstract is available as Supplementary information.

DOI

10.1007/s00467-022-05677-0

Alternate Title

Pediatr Nephrol

PMID

35867160

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