Objectives: To create a relational database for monitoring lithiasic patients. We describe the architectural details and the initial results of the statistical analysis.
Methods and materials: Microsoft Access 2002 was used as template. Four different tables were constructed to gather demographic data (table 1), clinical and laboratory findings (table 2), stone features (table 3) and therapeutic approach (table 4). For a reliability analysis of the database the number of correctly stored data was gathered. To evaluate the performance of the database, a prospective analysis was conducted, from May 2004 to August 2009, on 171 stone free patients after treatment (EWSL, surgery or medical) from a total of 511 patients stored in the database. Lithiasic status (stone free or stone relapse) was used as primary end point, while demographic factors (age, gender), lithiasic history, upper urinary tract alterations and characteristics of the stone (side, location, composition and size) were considered as predictive factors. An univariate analysis was conducted initially by chi square test and supplemented by Kaplan Meier estimates for time to stone recurrence. A multiple Cox proportional hazards regression model was generated to jointly assess the prognostic value of the demographic factors and the predictive value of stones characteristics.
Results: For the reliability analysis 22,084 data were available corresponding to 702 consultations on 511 patients. Analysis of data showed a recurrence rate of 85.4% (146/171, median time to recurrence 608 days, range 70-1758). In the univariate and multivariate analysis, none of the factors under consideration had a significant effect on recurrence rate (p=ns).
Conclusions: The relational database is useful for monitoring patients with urolithiasis. It allows easy control and update, as well as data storage for later use. The analysis conducted for its evaluation showed no influence of demographic factors and stone features on stone recurrence.