Introduction: In urological surgery antimicrobial prophylaxis is recommended, in order to decrease infective complications. Even more, asymptomatic bacteriuria should be ruled out before surgery, and treated, before the procedure is performed. But the urine culture gives delayed information of the bacteriuria status. So it would be important to have a good estimation of the bacteriuria status in the moment of the surgery.Objectives: Develop a predictive model of preoperative bacteriuria, based on clinical data and urine analysis. Evaluate the accuracy of the prediction. Validate the model in a patient population different from the one used to elaborate it.
Material and methods:Both clinical and urine analysis from 700 patients were extracted for the elaboration of a predictive model of bacteriuria, using binary logistic regression. Data from 150 patients more were used for the validation of the model.
Results:The predictive model included the presence and kind of foreign body in the urine track, presence of nitrites in urine, and presence and level of leukocyte esterase in urine. The model has an AUC of the ROC curve of 0,906, showing an excellent predictive capacity. In the validation sample the model has an AUC of 0,872, demonstrating a very good internal validity.