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Antimicrobial susceptibility of Escherichia coli producers of community urinary tract infections in Galicia (Spain). Period: 2016-2017

Losada I, Barbeito G, García-Garrote F, Fernández-Pérez B, Malvar A, Hervada X, Grupo de trabajo de la SOGAMIC para el estudio de las resistencias en Galicia, Grupo de trabajo de la SOGAMIC Sociedad Gallega de Microbiología para el estudio de las resistencias

Atencion primaria, 2020

14 citations

Abstract

OBJECTIVE: Escherichia coli (E. coli) is responsible for the majority of community urinary tract infections. The objective of the study is to know the sensitivity spectrum of E. coli in urinary tract infections to be able to recommend the appropriate empirical antibiotic treatment.

DESIGN: Cross-sectional, multicentric, retrospective study.

LOCATION: Galician 8 public hospitals, practically the entire population of Galicia (Spain).

PARTICIPANTS: 43,137 outpatients with urinary tract infection due to E. coli isolated in urine in 2016/2017.

MAIN MEASUREMENTS: Analyzed variables: demographic, minimum inhibitory concentration and interpretation of sensitivity according to CLSI criteria and resistance mechanisms. The antibiotics studied were: ampicillin, amoxicillin-clavulanic acid, ciprofloxacin, cefotaxime, cefepime, gentamicin, nitrofurantoin, fosfomycin, cotrimoxazole, imipenem and ertapenem. The identification and sensitivity were made mainly by automated methods.

RESULTS: The percentages of non-sensitivity of E. coli isolates were: ampicillin 49.2%, amoxicillin-clavulanic acid 17.8%, cefotaxime 6.7%, cefepime 5.7%, ertapenem 0.04%, imipenem 0.05%, gentamicin 9,1%, ciprofloxacin 26.2%, fosfomycin 3.3%, nitrofurantoin 2.4% and cotrimoxazole 23.9%. The non-sensitivities were higher in men and as age increases. Six percent of E. coli were producers of extended-spectrum beta-lactamases.

CONCLUSIONS: The empirical treatment in Galicia for uncomplicated cystitis produced by E.…

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Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause.

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