Predictive factors for multidrug-resistant gram-negative bacteria among hospitalised patients with complicated urinary tract infections

Aina Gomila-Grange ,Nienke Cuperus,Cristian Tebé,Jordi Carratalà,Alasdair Macgowan,Christiane Vank,Joan Miquel Vigo ,Evelyn Shaw,Leonard Leibovici,Ibironke Addy,Irith Wiegand,Laura Vallejo-Torres,Leonard Van Den Heuvel,Stephen Morris,Noa Eliakim‐Raz ,Sally Grier,Cuong Vuong,Margaret Stoddart,Miquel Pujol

doi:10.1186/s13756-018-0401-6

Abstract

BackgroundPatients with complicated urinary tract infections (cUTIs) frequently receive broad-spectrum antibiotics. We aimed to determine the prevalence and predictive factors of multidrug-resistant gram-negative bacteria in patients with cUTI.MethodsThis is a multicenter, retrospective cohort study in south and eastern Europe, Turkey and Israel including consecutive patients with cUTIs hospitalised between January 2013 and December 2014. Multidrug-resistance was defined as non-susceptibility to at least one agent in three or more antimicrobial categories. A mixed-effects logistic regression model was used to determine predictive factors of multidrug-resistant gram-negative bacteria cUTI.ResultsFrom 948 patients and 1074 microbiological isolates, Escherichia coli was the most frequent microorganism (559/1074), showing a 14.5% multidrug-resistance rate. Klebsiella pneumoniae was second (168/1074) and exhibited the highest multidrug-resistance rate (54.2%), followed by Pseudomonas aeruginosa (97/1074) with a 38.1% multidrug-resistance rate. Predictors of multidrug-resistant gram-negative bacteria were male gender (odds ratio [OR], 1.66; 95% confidence interval [CI], 1.20–2.29), acquisition of cUTI in a medical care facility (OR, 2.59; 95%CI, 1.80–3.71), presence of indwelling urinary catheter (OR, 1.44; 95%CI, 0.99–2.10), having had urinary tract infection within the previous year (OR, 1.89; 95%CI, 1.28–2.79) and antibiotic treatment within the previous 30 days (OR, 1.68; 95%CI, 1.13–2.50).ConclusionsThe current high rate of multidrug-resistant gram-negative bacteria infections among hospitalised patients with cUTIs in the studied area is alarming. Our predictive model could be useful to avoid inappropriate antibiotic treatment and implement antibiotic stewardship policies that enhance the use of carbapenem-sparing regimens in patients at low risk of multidrug-resistance.

Highlights

Patients with complicated urinary tract infections frequently receive broad-spectrum antibiotics
Considering the lack of contemporary data on hospitalised patients with complicated urinary tract infections (cUTIs), we aimed to determine the prevalence of MDR among hospitalised patients with cUTIs in countries with high MDR-gram-negative bacteria (GNB) prevalence and develop a predictive model to determine the risk of MDR-GNB infections, which would be useful to select more targeted antibiotic regimens avoiding the frequent treatment with broad-spectrum antibiotics
Data was collected from patients who were diagnosed with cUTI as the primary cause of hospitalisation and from patients who were hospitalised for other reasons but who developed cUTIs during their hospitalization [9]

Summary

Introduction

Patients with complicated urinary tract infections (cUTIs) frequently receive broad-spectrum antibiotics. Data from the most recent point prevalence survey of healthcare-associated infections (HAIs) in European acute care hospitals showed that UTI was the third most common cause, accounting for 19% of estimated 3.2 million overall cases of HAIs [3]. This figure, huge, clearly underestimates the overall cUTI incidence in Europe because it did not include patients developing cUTIs in the community and in long-term care facilities (LTCFs). Comorbidities, and an increasing number of invasive urologic procedures for both diagnosis and treatment have been related to this high prevalence of cUTIs in the European population

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