The incidence of antimicrobial resistance among urinary E. coli isolates is increasing in both hospital and community settings in Australia

By Pooja Toshniwal PahariaReviewed by Danielle Ellis, B.Sc.Dec 1 2022

In a recent study published in the Journal of Global Antimicrobial Resistance, researchers comparatively evaluated trends in antimicrobial resistance (AMR) among urinary Escherichia coli strains from a private, commercial community-based (CB) laboratory [Southern.IML Pathology (S.IML)] and a public HB (hospital-based) laboratory [part of the New South Wales Health Pathology (NSWHP) network] in the Illawarra Shoalhaven area located in NSW, Australia.

Background

Antibiotics are commonly prescribed for UTIs (urinary tract infections), most of which are caused by E. coli. In Australia, the prevalence of antimicrobial resistance in urine Escherichia coli strains has increased significantly in the previous decade, raising important public health concerns. In Australia, AMR data is derived primarily from hospitals. However, most laboratory tests are performed, and antibiotic prescriptions are issued for urinary tract infections in community-based settings.

AGAR (Australian group on antimicrobial resistance) surveys have documented greater AMR in HB isolates; however, the trends or volumes between CB and HB laboratories were not compared. Ever since, Australian national surveillance strategies have emphasized serological isolates, most of which are CB-onset.

About the study

In the present study, researchers assessed trends and levels of antimicrobial resistance among strains of urinary Escherichia coli over 12 years by comparing data from HB and CB laboratories located in the Illawarra Shoalhaven region of Australia.

In total, 108,262 urinary Escherichia coli strains were analyzed, of which 34,103 isolates and 74,159 isolates were obtained from the public HB laboratory and the private CB laboratory, respectively, between January 1, 2007, and December 31, 2019. Linear regression modeling was performed to independently evaluate changes in antimicrobial resistance rates among the two laboratory datasets and identify significant interactions of each laboratory setting in proportionate changes during the course of the study.

Differences between resistance to each antibiotic in the HB and CB laboratories were assessed. To test for antimicrobial susceptibility, disc diffusion techniques such as the CDS (calibrated dichotomous susceptibility) and the EUCAST (European committee on antimicrobial susceptibility testing) were performed for the period up to 2014 and from 2015 to 2019, respectively. The initially obtained isolate for every patient over 12 years was analyzed. Data obtained between November 30, 2013, and January 31, 2015, encompassing change in the testing method, were excluded from the study.

Information, including patient identification numbers, accession numbers, isolation dates, antimicrobial susceptibility, and sites of organism detection, were retrieved from both pathology providers. Antimicrobial agents analyzed included ampicillin (representative of amoxicillin), cephalexin, amoxicillin-clavulanate, trimethoprim, and norfloxacin.

Results

Antimicrobial patterns were comparable for urine Escherichia coli strains analyzed in the two laboratories during the 12 years. The rates of antimicrobial resistance were expectedly and consistently greater in HB settings, whereas the volumes of resistant Escherichia coli strains for commonly prescribed antibiotics such as ampicillin and trimethoprim was considerably greater in the CB laboratory.

The only included antimicrobial, for which AMR trends among Escherichia coli did not change significantly, was ampicillin over 12 years in the HB or CB laboratories, and significantly elevated AMR rates were observed for all the other antibiotics during the period in the two laboratory settings. However, the rates of change significantly differed between the two laboratories, with convergence for trimethoprim and divergence for norfloxacin and cephalexin.

Amoxicillin-clavulanate and ampicillin did not show any significant interactions between the two laboratories for the differences in the rates of change during the 12-year duration of the study. HB data was skewed toward individuals with elevated AMR rates because of treatment failure in community-based settings, hospital readmissions, and prolonged lengths of hospital stays. The finding was displayed in the lesser resistance of E. coli trimethoprim (15%) documented in the CB data, in comparison to the AGAR survey data for urinary E. coli isolates in Australia (23%) and NSW (24%).

The difference in resistance rates could likely be generalized to the population of Australia on the basis of census data for the Illawarra region as a denotive of the population of the country. Community-based laboratory setting data showed more numerous resistant E. coli isolates compared to the HB laboratory data for norfloxacin, trimethoprim, and ampicillin.

In addition, the elevated rates for trimethoprim resistance over 12 years were higher in the community-based laboratory dataset. Most of the E. coli isolates in the HB laboratory dataset, and slightly greater than 40.0% of isolates in the CB laboratory dataset showed ampicillin resistance. On the other hand, trends of increased norfloxacin and cefalexin resistance rates were greater in the HB laboratory dataset.

Conclusion

Overall, the study findings showed that AMR rates in the private CB laboratory and public HB laboratory settings elevated with time and were consistently greater in the HB setting dataset. Given that the greatest volumes were reported in outpatient settings and that most of the antibiotics are prescribed in primary healthcare settings, interventions incorporating outpatient setting data are critical for addressing antimicrobial resistance.