Background: We analyse the distribution of ESBL infections in Dammam Medical Complex, Eastern Province, Saudi Arabia with respect to patient demographics, wards, infection site, bacterial species, and antibiotic resistance. We also gauged hospital staff understanding of ESBLs, the procedures in place to identify, treat and infections containing.

Methods: Hospital records from 2016 were analysed and 352 ESBL from several samples types were identified using VITEK® 2 system and by phenotypic confirmation using a disk diffusion test. HCWs attitudes and knowledge were assessed using a paper questionnaire.

Results: The percentage of ESBL isolates were Klebsiella pneumoniae(n=148; 42.1%) or Escherichia coli(n=176; 50%), Proteus mirabilis(n=7; 2%), Morganella morganii(n=13; 3.7%), Enterobacter (n=7; 2%) and Citrobacter freundii (n=1; 0.3%). Overall tigecycline susceptibility was 82.2%, however P. mirabilis and M. morganii isolates were uniformly resistant and K. pneumoniae susceptibility levels were significantly lower than for E. coli in urine samples (72.3% v 100%; Chi square=13.76, p=0.0002); for blood samples there was also apparently higher resistance among K. pneumoniae isolates. Overall susceptibility to the carbapenems imipenem, meropenem and ertapenam was high. There were overall high levels of uncertainty among healthcare workers on hospital policies on reporting or prescribing with respect to ESBL-expressing infections.

Conclusions: ESBL control strategies should consider variations among sample types, wards, and antibiotic resistance variability. There is a need to specifically address staff training and communication procedures for infection prevention and control with respect to ESBLs.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jiph.2019.12.001DOI Listing

Publication Analysis

Top Keywords

antibiotic resistance
12
saudi arabia
8
esbl
5
esbl expression
4
expression antibiotic
4
resistance
4
resistance patterns
4
hospital
4
patterns hospital
4
hospital saudi
4

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!