The Epidemiology Of Urolithiasis And Study On Influential Factors Related To Extracorporeal Shock Wave Lithotripsy

ObjectiveTo examine the time distribution of urolithiasis and provide basic information for prevention of urolithiasis; To explore factors related to efficacy of extracorporeal shock wave lithotripsy.MethodsWe collected data of patients diagnosed as urolithiasis from January, 1, 2003 to December, 31, 2009 at the Fourth Municipal People's Hospital of Shenzhen. Muster analysis and circular distribution method were used to analyze the time distribution of urolithiasis. Furthermore, 1203 ureteral calculi patients were followed up to collect data regarding efficacy of extracorporeal shock wave lithotripsy (ESWL) from January,1, 2003 to December, 31, 2009 at the same hospital. Treatment effects were evaluated after three-month follow-up. We used chi-square test, t-test and analysis of variance to do univariate analyses. Single factors with statistical significance in the univariate analyses and important factors found in other studies were considered in the logistic regression model. We also fitted a regression model to predict the probability of effects of treatment. The significant level was set at 0.05 and two-sided test was used. All the statistical analyses were performed using SAS 9.1.3.ResultsThe results of both muster method and circular distribution method showed that the occurrence of urolithiasis was time aggregated. The occurrence of urolithiasis centralized on summer in July and August. Among the study on factors related to treatment, 1076 cases among 2151 patients were sucessfully treated, the total stone-free rate was 89.44%; Among them, 955 cases (88.75%) were treated with once ESWL; 121 cases (11.25%) underwent at least more than once. The stones of 127 cases were not fully expelled and the total failure rate was 10.56%. Complications were found in 118 patients (9.81%) after treatment. The extended efficiency quotient (EQb) was 0.80. Results of univariate analyses showed that nine factors had significant effects on expelling of stone. Multivariate analysis showed that four factors were statistically significant such as gender, location of location, hydrops levels and stone burden. These four factors were used to fit logistic regression models to predict the probability of stone-free rate after ESWL. The sensitivity of model was 84.2%, the specificity 40.9%, the overall accuracy 79.6%, the false positive rate 7.6%, the false negative rate 76.6%. The ROC area under the curve was 0.715. ConclusionsWe should strengthen relevant health education and implement prevention interventions during the high-incidence seasons. Gender, symptoms, hydrops levels and stone burden had a significant impact on the effect of ESWL treatment. We could predict the probability of success of treatment in patients using the regression model. It will be useful for screening suitable patients before treatment and improving the efficacy of ESWL.