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Optimizing reflex urine cultures: Using a population-specific approach to diagnostic stewardship

Published online by Cambridge University Press:  10 January 2023

Sonali D. Advani*
Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
Nicholas A. Turner
Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
Kenneth E. Schmader
Division of Geriatrics, Department of Medicine, Duke and Durham VA Medical Center, Durham, North Carolina
Rebekah H. Wrenn
Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
Rebekah W. Moehring
Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
Christopher R. Polage
Department of Pathology, Duke University School of Medicine, Durham, North Carolina
Valerie M. Vaughn
Division of General Internal Medicine, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah
Deverick J. Anderson
Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
Author for correspondence: Sonali D. Advani, MBBS, MPH, FIDSA, Division of Infectious Diseases, Duke University School of Medicine, 315 Trent Drive, Hanes House, Suite 154, Durham, NC 27710. E-mail:



Clinicians and laboratories routinely use urinalysis (UA) parameters to determine whether antimicrobial treatment and/or urine cultures are needed. Yet the performance of individual UA parameters and common thresholds for action are not well defined and may vary across different patient populations.


In this retrospective cohort study, we included all encounters with UAs ordered 24 hours prior to a urine culture between 2015 and 2020 at 3 North Carolina hospitals. We evaluated the performance of relevant UA parameters as potential outcome predictors, including sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV). We also combined 18 different UA criteria and used receiver operating curves to identify the 5 best-performing models for predicting significant bacteriuria (≥100,000 colony-forming units of bacteria/mL).


In 221,933 encounters during the 6-year study period, no single UA parameter had both high sensitivity and high specificity in predicting bacteriuria. Absence of leukocyte esterase and pyuria had a high NPV for significant bacteriuria. Combined UA parameters did not perform better than pyuria alone with regard to NPV. The high NPV ≥0.90 of pyuria was maintained among most patient subgroups except females aged ≥65 years and patients with indwelling catheters.


When used as a part of a diagnostic workup, UA parameters should be leveraged for their NPV instead of sensitivity. Because many laboratories and hospitals use reflex urine culture algorithms, their workflow should include clinical decision support and or education to target symptomatic patients and focus on populations where absence of pyuria has high NPV.

Original Article
© The Author(s), 2023. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America

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PREVIOUS PRESENTATION: These data were presented as a poster at IDWeek 2022 on October 20, 2022 at Washington, DC (abstract no. 1261422).


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