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

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Abstract

Introduction and hypothesis

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.

Methods

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.

Results

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.

Conclusions

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.

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Funding

Funding for this study was provided by institutional funding; a competitive Providence Health Care Foundation grant and a University of British Columbia Faculty of Medicine Summer Student Research Program grant.

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Authors and Affiliations

  1. Department of Obstetrics and Gynecology, University of Alberta, 5S118 Lois Hole Hospital for Women, 10240 Kingsway Avenue, Edmonton, AB, T5H 3V9, Canada

    May Sara Sanaee

  2. Department of Obstetrics and Gynecology, University of British Columbia, Vancouver, Canada

    Kathy Pan, Nicole A. Koenig & Roxana Geoffrion

  3. Faculty of Medicine, University of British Columbia, Vancouver, Canada

    Kathy Pan & Roxana Geoffrion

  4. Centre for Health Evaluation and Outcome Sciences, University of British Columbia, Vancouver, Canada

    Terry Lee & Roxana Geoffrion

Authors
  1. May Sara Sanaee
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  2. Kathy Pan
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  3. Terry Lee
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  4. Nicole A. Koenig
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  5. Roxana Geoffrion
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Contributions

MS Sanaee: Protocol/project development, data collection, data management, data analysis, manuscript writing/editing.

K Pan: Data collection, data management, manuscript editing.

T Lee: Data analysis, manuscript editing.

N Koenig: Protocol/project development, data collection, data management, data analysis, manuscript writing/editing.

R Geoffrion: Protocol/project development, data collection, data management, data analysis, manuscript writing/editing.

Corresponding author

Correspondence to May Sara Sanaee.

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Conflict of interest

M. Sanaee, K. Pan, T. Lee and N. Koenig: None.

R. Geoffrion reports personal fees from Boston Scientific and from Duchesnay Canada, outside the submitted work.

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Sanaee, M.S., Pan, K., Lee, T. et al. Urinary tract infection after clean-contaminated pelvic surgery: a retrospective cohort study and prediction model. Int Urogynecol J 31, 1821–1828 (2020). https://doi.org/10.1007/s00192-019-04119-0

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  • DOI: https://doi.org/10.1007/s00192-019-04119-0

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