Urinary tract infection after clean-contaminated pelvic surgery: a retrospective cohort study and prediction model

Postoperative urinary tract infection (UTI) leads to increased patient morbidity and health care costs. A prediction model may identify patients at highest risk for UTI development. Our primary objective was to determine the rate of UTI in the first 6 weeks after benign gynecologic surgery. Our secondary objective was to identify risk factors and build a predictive model for postoperative UTI.

We reviewed 310 patient records, which represent all patients who underwent clean-contaminated surgery at a tertiary center (2016-2017). UTI was defined as positive urine culture (> 100,000,000 CFU/l) in a symptomatic patient. Pre-, intra- and postoperative variables were collected. The relation between these variables and UTI was assessed through logistic regression. A clinical prediction model was built.

Patients' mean age was 58.5 years and mean body mass index was 27.5 kg/m². Most were inpatients (65.8%) and 269 had urogynecologic procedures, with the remainder undergoing pelvic surgery for other indications. The most common operation was vaginal reconstruction for prolapse (59.7%), associated with concomitant synthetic midurethral sling in 1/3 cases. Forty patients (12.9%) developed UTI. Multivariate prediction modeling showed increasing age (OR 1.33, CI 1.01-1.75), increasing number of procedures (OR 1.42, CI 1.14-1.78) and prolonged voiding dysfunction (OR 3.78, CI 1.66-8.60) to be significant UTI predictors.

Urinary tract infection in the first 6 weeks after complex pelvic surgery is common. Our prediction model identifies that patients who are older women, have prolonged voiding dysfunction and have a greater number of concomitant pelvic floor surgeries have higher risk of postoperative UTI.