A simple predictive model with internal validation for assessment of stone-left after ureteroscopic lithotripsy in upper ureteral stones.

ABSTRACT:

Background

Stone free rate in upper ureteral stones is not as high. We sought to identify easily accessible risk factors attributing to stones left in the ureteroscopy in the treatment of upper ureteral calculi, and to build a simple and reliable predictive model.

Methods

Patients treating only for upper ureteral stones in 2018 were retrospectively analyzed. Correlations between factors and the stone free rate were analyzed using bidirectional stepwise regression, curve fitting and binary logistic regression. Stone shape was judged by the gap between length and width in the two-dimensional section. A predictive nomogram model was built based on those selected variables (P<0.05). The area under the receiver operator characteristic curve (AUC) and calibration curve were used t

SUBMITTER: Wu W 

PROVIDER: S-EPMC9262739 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature