A practical formula to predict the stone-free rate of patients undergoing extracorporeal shock wave lithotripsy

Abstract

Objectives: We studied patients who underwent extracorporeal shock wave lithotripsy (SWL) to investigate the factors influencing the outcome, and built a logistic regression model to estimate the stone-free rate (SFR) after SWL. Material and methods: From January 2013 to December 2013, we retrospectively reviewed the clinical status of 641 patients with a solitary urinary calculus who underwent SWL in our hospital. Univariate logistic regression was used to identify the factors leading to a high SFR, and significant factors were further analyzed by multivariate logistic regression. After the optimal model had been developed, we placed it on the website so others could calculate the SFR at their institutions. Results: The overall SFR for all patients, patients with ureteral stones, and patients with renal stones were 54.8%, 67.8%, and 46.7%, respectively. Multivariate logistic regression showed that body mass index (BMI), stone length, stone width, and stone location were the independent factors that affected the overall successful rate. Stone length was the only significant factor to predict SFR for ureteral stones. BMI, stone length, and stone width were significant SFR predictors for renal stones. A logistic regression model was designed to estimate SFR, which has a sensitivity of 77.8% and specificity of 75.5%. Conclusion: BMI, stone length, stone width, and kidney and ureteral stones were all prognostic factors influencing the outcome of SWL. We built a logistic regression formula to predict the SFR, which helps urologists to select patients for SWL.

Keywords

• urolithiasis
• shock wave lithotripsy
• predictive formula