Storz Medical Lithotripsy Index Predicts Success of Shock Wave Lithotripsy in Ureteric Stones

 The aim of this study is to evaluate the factors affecting treatment success in patients who underwent Shock wave lithotripsy (SWL) for ureter stones and to investigate the effect of Storz Medical Lithotripsy Index (SMLI) on treatment effectiveness in ureteric stones.

 Prospective data were collected on patients undergoing SWL treatment for ureter stones between January 2013 and May 2021. Stone location, number, and size were determined with Non contrast CT (NCCT) for all patients. All patients underwent SWL with a Storz Modulith SLK lithotripsy machine with local anaesthesia. The total amount of energy applied to the stone was calculated using the Storz Medical Lithotripsy Index (SMLI). All patients were evaluated for stone-free status by X-ray at least 2 weeks after treatment. The success of the procedure was defined as the patient being completely stone free (SF) or detection of residual fragments < 4 mm that did not require further treatment

 A total of 1199 patients with ureter stones were included in the study. The mean age of the patients was 43.11 ± 10.65 (18-73), and the mean BMI was 27.87±8.12(19.02-38.65). During SWL, 89.3% of patients demonstrated excellent pain tolerance (1070/1199). A total of 119 patients could not tolerate pain during SWL (10.7%).Treatment success was associated with fewer treatment sessions (2.04±1.64 vs. 2.50 ± 1.48; p < 0.001), smaller stone size (7.35±2.99 vs. 9.02 ± 3.81; p < 0.001) and higher SMLI/stone size (29.70 ± 17.48 vs. 24.98±16.01; p < 0.001). In the univariate and multivariate regression analysis, the factors affecting the success of the treatment were the number of sessions (OR: 1.147), stone size (OR: 1.112), SMLI/stone size (OR: 1.115) and pain tolerance (OR: 0.740).

 In the treatment of ureteral stones with SWL, number of sessions, stone size, SMLI/stone size, and pain tolerance are the factors affecting success. SMLI per stone size is a statistically significant factor for predicting SWL success.