Brett A Faine1, Kari K Harland2, Blake Porter3, Stephen Y Liang4, Nicholas Mohr2. 1. University of Iowa Hospitals and Clinics, Iowa City, IA, USA brett-faine@uiowa.edu. 2. University of Iowa Hospitals and Clinics, Iowa City, IA, USA. 3. University of Iowa College of Pharmacy, Iowa City, IA, USA. 4. Washington University in St Louis School of Medicine, MO, USA.
Abstract
BACKGROUND: Identifying patients at high risk for multidrug-resistant urinary tract infections (UTIs) is important for guiding empirical antimicrobial therapy. Clinical risk factors associated with antimicrobial-resistant urinary pathogens and the derivation of a simple clinical decision rule could help define health care-associated UTI. OBJECTIVE: To derive a simple clinical decision rule to identify clinical risk factors associated with antimicrobial-resistant urinary pathogens. METHODS: This was a retrospective case-control study of all emergency department (ED) patients from July 1, 2011, to July 1, 2012, who presented to the ED with UTI and a positive urine culture. Candidate risk factors were collected retrospectively from medical record review. We compared differences in patient characteristics stratified by the presence of an antimicrobial-resistant urinary pathogen. RESULTS: A total of 360 patients with UTI had a positive, noncontaminated urine culture during the study period. About 6.7% of patients (n = 24) had a multidrug-resistant (MDR) urinary infection. Logistic regression modeling identified 3 clinical factors associated with the identification of a MDR pathogen: male sex, chronic hemodialysis, and nursing home residence. A scoring system was created to identify patients with MDR pathogens. Test characteristics were calculated using bootstrapping for internal validation, with a sensitivity of 74.7% (95% CI = 55.1%-91.3%) and specificity of 85.1% (95% CI = 77.8%-86.2%), positive likelihood ratio of 4.3, and a negative likelihood ratio of 0.3. CONCLUSIONS: Clinical factors can be used to identify UTI patients at high risk of MDR urinary pathogens.
BACKGROUND: Identifying patients at high risk for multidrug-resistant urinary tract infections (UTIs) is important for guiding empirical antimicrobial therapy. Clinical risk factors associated with antimicrobial-resistant urinary pathogens and the derivation of a simple clinical decision rule could help define health care-associated UTI. OBJECTIVE: To derive a simple clinical decision rule to identify clinical risk factors associated with antimicrobial-resistant urinary pathogens. METHODS: This was a retrospective case-control study of all emergency department (ED) patients from July 1, 2011, to July 1, 2012, who presented to the ED with UTI and a positive urine culture. Candidate risk factors were collected retrospectively from medical record review. We compared differences in patient characteristics stratified by the presence of an antimicrobial-resistant urinary pathogen. RESULTS: A total of 360 patients with UTI had a positive, noncontaminated urine culture during the study period. About 6.7% of patients (n = 24) had a multidrug-resistant (MDR) urinary infection. Logistic regression modeling identified 3 clinical factors associated with the identification of a MDR pathogen: male sex, chronic hemodialysis, and nursing home residence. A scoring system was created to identify patients with MDR pathogens. Test characteristics were calculated using bootstrapping for internal validation, with a sensitivity of 74.7% (95% CI = 55.1%-91.3%) and specificity of 85.1% (95% CI = 77.8%-86.2%), positive likelihood ratio of 4.3, and a negative likelihood ratio of 0.3. CONCLUSIONS: Clinical factors can be used to identify UTI patients at high risk of MDR urinary pathogens.
Authors: P Garcinuño; M Santibañez; L Gimeno; A Sánchez-Bautista; J Coy; J Sánchez-Paya; V Boix; E Merino; J Portilla; J C Rodríguez Journal: Eur J Clin Microbiol Infect Dis Date: 2016-08-09 Impact factor: 3.267
Authors: Nicolò Capsoni; Pietro Bellone; Stefano Aliberti; Giovanni Sotgiu; Donatella Pavanello; Benedetto Visintin; Elena Callisto; Laura Saderi; Davide Soldini; Luca Lardera; Valter Monzani; Anna Maria Brambilla Journal: Multidiscip Respir Med Date: 2019-07-05
Authors: Raghad Saadi; Navaneeth Narayanan; Pamela Ohman-Strickland; Eric Zhu; Jonathan McCoy; Grant Wei; Thomas J Kirn; Patrick Bridgeman Journal: J Am Coll Emerg Physicians Open Date: 2021-01-14
Authors: Manuel Madrazo; Ana Esparcia; Ian López-Cruz; Juan Alberola; Laura Piles; Alba Viana; José María Eiros; Arturo Artero Journal: BMC Infect Dis Date: 2021-12-07 Impact factor: 3.090