Ofri Tsafrir, Hanan Rohana, Lior Bousani, Khatib Orsan, Said Abozaid, Maya Azrad, Avi Peretz
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引用次数: 0
Abstract
C.coli is a significant cause of foodborne gastroenteritis worldwide, with the majority of cases attributed to C.jejuni. Although most clinical laboratories do not typically conduct antimicrobial susceptibility testing for C.coli, the rise in resistant strains has underscored the necessity for such testing and epidemiological surveillance. The current study presents clinical isolate characteristics and demographics of 221 patients with C.coli (coli and jejuni) infections in Northern Israel, between 2015 and 2021. Clinical and demographic data were collected from patient medical records. Susceptibility to erythromycin, tetracycline, ciprofloxacin, and gentamicin was assessed using the standard E-test. No significant correlations were found between bacterial species and patient ethnicity, patient gender, or duration of hospitalization. In contrast, significant differences were found between infecting species and patient age and age subgroup (P < 0.001). Furthermore, erythromycin resistance was observed in only 0.5% of the study population, while resistance to ciprofloxacin, tetracycline, and gentamicin was observed in 95%, 93%, and 2.3% of the population, respectively. The presented study underscores the need for routine surveillance of C.coli antibiotic resistance.
期刊介绍:
Epidemiology & Infection publishes original reports and reviews on all aspects of infection in humans and animals. Particular emphasis is given to the epidemiology, prevention and control of infectious diseases. The scope covers the zoonoses, outbreaks, food hygiene, vaccine studies, statistics and the clinical, social and public-health aspects of infectious disease, as well as some tropical infections. It has become the key international periodical in which to find the latest reports on recently discovered infections and new technology. For those concerned with policy and planning for the control of infections, the papers on mathematical modelling of epidemics caused by historical, current and emergent infections are of particular value.