Posterior Urethral Valves Outcomes Prediction (PUVOP): a machine learning tool to predict clinically relevant outcomes in boys with posterior urethral valves.

Background: Early kidney and anatomic features may be predictive of future progression and need for additional procedures in patients with posterior urethral valve (PUV). The objective of this study was to use machine learning (ML) to predict clinically relevant outcomes in these patients.

Methods: Patients diagnosed with PUV with kidney function measurements at our institution between 2000 and 2020 were included.

Understanding and Assessing Nontechnical Skills in Robotic Urological Surgery: A Systematic Review and Synthesis of the Validity Evidence.

Objective: Robotic urological surgery (RUS) has seen widespread adoption across institutions in the last decade. To match this rapid growth, it is imperative to develop a structured RUS curriculum that addresses both technical and nontechnical competencies. Emerging evidence has shown that nontechnical skills form a critical component of RUS training.