A Novel Machine-Learning Algorithm to Predict Stone Recurrence with 24-Hour Urine Data.

The absence of predictive markers for kidney stone recurrence poses a challenge for the clinical management of stone disease. The unpredictability of stone events is also a significant limitation for clinical trials, where many patients must be enrolled to obtain sufficient stone events for analysis. In this study, we sought to use machine learning methods to identify a novel algorithm to predict stone recurrence.

Voided volume may not impact stone outcomes: Review of a large institutional nephrolithiasis cohort.

Background: Urologic guidelines universally recommend increasing fluid intake for kidney stone prevention. Increased voided volume is thought to help reduce stone recurrence and severity, but supporting evidence is limited.

Patients And Methods: Nephrolithiasis outcomes and 24-h urine data for patients from the Registry for Stones of the Kidney and Ureter (ReSKU), a registry of nephrolithiasis patients collected between 2015 and 2020, were retrospectively analysed.

Ultrasound-Only Percutaneous Nephrolithotomy Is Safe and Effective Compared to Fluoroscopy-Directed Percutaneous Nephrolithotomy.

Outcomes after ultrasound-only percutaneous nephrolithotomy (PCNL), in which no fluoroscopy is used, are not well known. The goal of this study was to compare outcomes of ultrasound-only and fluoroscopy-directed PCNL. Prospectively collected data from the Registry for Stones of the Kidney and Ureter database were reviewed for all patients who underwent PCNL at one academic center from 2015 to 2021.