Case-based surveillance of antimicrobial resistance in the ACORN (A Clinically Oriented Antimicrobial Resistance Surveillance Network) study

The scope of the antimicrobial resistance challenge

Each year, an estimated 7·7 million deaths are attributed to bacterial infections, of which 4.95 million are associated with drug-resistant pathogens, and 1·27 million are caused by bacterial pathogens resistant to the antibiotics available. Access to effective antibiotics when indicated prolongs life, reduces disability, reduces health-care expenses, and enables access to other life-saving medical innovations. Antimicrobial resistance undoes these benefits and is a major barrier to attainment of the Sustainable Development Goals, including targets for newborn survival, progress on healthy ageing, and alleviation of poverty. Adverse consequences from antimicrobial resistance are seen across the human life course in both health-care-associated and community-associated infections, as well as in animals and the food chain. The small set of effective antibiotics has narrowed, especially in resource-poor settings, and people who are very young, very old, and severely ill are particularly susceptible to resistant infections. This paper, the first in a Series on the challenge of antimicrobial resistance, considers the global scope of the problem and how it should be measured. Robust and actionable data are needed to drive changes and inform effective interventions to contain resistance. Surveillance must cover all geographical regions, minimise biases towards hospital-derived data, and include non-human niches.

Examining pharmacoepidemiology of antibiotic use and resistance in first-line antibiotics: a self-controlled case series study of Escherichia coli in small companion animals

Background

Clinicians need to prescribe antibiotics in a way that adequately treats infections, while simultaneously limiting the development of antibiotic resistance (ABR). Although there are abundant guidelines on how to best treat infections, there is less understanding of how treatment durations and antibiotic types influence the development of ABR. This study adopts a self-controlled case study (SCCS) method to relate antibiotic exposure time to subsequent changes in resistance patterns. This SCCS approach uses antibiotic exposure as a risk factor, and the development of ABR as an incidence rate ratio (IRR), which can be considered as the multiplicative change in risk for bacteria to become or maintain resistance.

Aim

To investigate the IRR of extensive (more than 7 antibiotic classes), revert, persistent, and directed antibiotic resistance according to the duration and type of antibiotic exposures in Escherichia coli (E. coli).

Methods and material

We use anonymized veterinary clinical data from dog and cat patients older than 6 months between 2015 and 2020. Patients were considered suitable cases if they received antibiotics and had a minimum of two urinary antibiograms within a 12-month period (the first prior to antibiotics exposure and the second from 1 week to 6 months after exposure). The first antibiogram is conducted before antibiotic exposure (case n=20).

Findings

From 20 individuals and 42 paired antibiograms we found that the IRR = 2 for extensive drug resistance in patients who received short-course antibiotic treatment compared to longer treatments. In contrast, multi-drug resistance IRR = 2.6 for long-course compared to short-course antibiotic treatment. The ratio of E. coli isolates that reverted from resistant to sensitive was 5.4 times more likely in patients who received antibiotics for longer than 10 days.

A Clinically Oriented antimicrobial Resistance surveillance Network (ACORN): pilot implementation in three countries in Southeast Asia, 2019-2020

Background: Case-based surveillance of antimicrobial resistance (AMR) provides more actionable data than isolate- or sample-based surveillance. We developed A Clinically Oriented antimicrobial Resistance surveillance Network (ACORN) as a lightweight but comprehensive platform, in which we combine clinical data collection with diagnostic stewardship, microbiological data collection and visualisation of the linked clinical-microbiology dataset. Data are compatible with WHO GLASS surveillance and can be stratified by syndrome and other metadata. Summary metrics can be visualised and fed back directly for clinical decision-making and to inform local treatment guidelines and national policy. Methods: An ACORN pilot was implemented in three hospitals in Southeast Asia (1 paediatric, 2 general) to collect clinical and microbiological data from patients with community- or hospital-acquired pneumonia, sepsis, or meningitis. The implementation package included tools to capture site and laboratory capacity information, guidelines on diagnostic stewardship, and a web-based data visualisation and analysis platform. Results: Between December 2019 and October 2020, 2294 patients were enrolled with 2464 discrete infection episodes (1786 community-acquired, 518 healthcare-associated and 160 hospital-acquired). Overall, 28-day mortality was 8.7%. Third generation cephalosporin resistance was identified in 54.2% (39/72) of E. coli and 38.7% (12/31) of K. pneumoniae isolates . Almost a quarter of S. aureus isolates were methicillin resistant (23.0%, 14/61). 290/2464 episodes could be linked to a pathogen, highlighting the level of enrolment required to achieve an acceptable volume of isolate data. However, the combination with clinical metadata allowed for more nuanced interpretation and immediate feedback of results. Conclusions: ACORN was technically feasible to implement and acceptable at site level. With minor changes from lessons learned during the pilot ACORN is now being scaled up and implemented in 15 hospitals in 9 low- and middle-income countries to generate sufficient case-based data to determine incidence, outcomes, and susceptibility of target pathogens among patients with infectious syndromes.

Epidemiology of Extended-Spectrum Beta-Lactamase and Carbapenemase-Producing Enterobacterales in the Greater Mekong Subregion: A Systematic-Review and Meta-Analysis of Risk Factors Associated With Extended-Spectrum Beta-Lactamase and Carbapenemase Isolation

Background: Despite the rapid spread of extended-spectrum beta-lactamase (ESBL) producing-Enterobacterales (ESBL-E) and carbapenemase-producing Enterobacterales (CPE), little is known about the extent of their prevalence in the Greater Mekong Subregion (GMS). In this systematic review, we aimed to determine the epidemiology of ESBL-E and CPE in clinically significant Enterobacterales: Escherichia coli and Klebsiella pneumoniae from the GMS (comprising of Cambodia, Laos, Myanmar, Thailand, Vietnam and Yunnan province and Guangxi Zhuang region of China). Methods: Following a list of search terms adapted to subject headings, we systematically searched databases: Medline, EMBASE, Scopus and Web of Science for articles published on and before October 20th, 2020. The search string consisted of the bacterial names, methods involved in detecting drug-resistance phenotype and genotype, GMS countries, and ESBL and carbapenemase detection as the outcomes. Meta-analyses of the association between the isolation of ESBL from human clinical and non-clinical specimens were performed using the "METAN" function in STATA 14. Results: One hundred and thirty-nine studies were included from a total of 1,513 identified studies. Despite the heterogeneity in study methods, analyzing the prevalence proportions on log-linear model scale for ESBL producing-E. coli showed a trend that increased by 13.2% (95%CI: 6.1-20.2) in clinical blood specimens, 8.1% (95%CI: 1.7-14.4) in all clinical specimens and 17.7% (95%CI: 4.9-30.4) increase in carriage specimens. Under the log-linear model assumption, no significant trend over time was found for ESBL producing K. pneumoniae and ESBL-E specimens. CPE was reported in clinical studies and carriage studies past 2010, however a trend could not be determined because of the small dataset. Twelve studies were included in the meta-analysis of risk factors associated with isolation of ESBL. Recent antibiotic exposure was the most studied variable and showed a significant positive association with ESBL-E isolation (pooled OR: 2.9, 95%CI: 2.3-3.8) followed by chronic kidney disease (pooled OR: 4.7, 95%CI: 1.8-11.9), and other co-morbidities (pooled OR: 1.6, 95%CI: 1.2-2.9). Conclusion: Data from GMS is heterogeneous with significant data-gaps, especially in community settings from Laos, Myanmar, Cambodia and Yunnan and Guangxi provinces of China. Collaborative work standardizing the methodology of studies will aid in better monitoring, surveillance and evaluation of interventions across the GMS.

Antimicrobial susceptibility testing results from 13 hospitals in Viet Nam: VINARES 2016-2017

OBJECTIVE

To analyse data from 2016-17 from a hospital-based antimicrobial resistance surveillance with national coverage in a network of hospitals Viet Nam.

METHODS

We analysed data from 13 hospitals, 3 less than the dataset from the 2012-13 period. Identification and antimicrobial susceptibility testing data from the clinical microbiology laboratories from samples sent in for routine diagnostics were used. Clinical and Laboratory Standards Institute 2018 guidelines were used for antimicrobial susceptibility testing interpretation. WHONET was used for data entry, management and analysis.

RESULTS

42,553 deduplicated isolates were included in this analysis; including 30,222 (71%) Gram-negative and 12,331 (29%) Gram-positive bacteria. 8,793 (21%) were from ICUs and 7,439 (18%) isolates were from invasive infections. Escherichia coli and Staphylococcus aureus were the most frequently detected species with 9,092 (21%) and 4,833 isolates (11%), respectively; followed by Klebsiella pneumoniae (3,858 isolates - 9.1%) and Acinetobacter baumannii (3,870 isolates - 9%). Bacteria were mainly isolated from sputum (8,798 isolates - 21%), blood (7,118 isolates - 17%) and urine (5,202 isolates - 12%). Among Gram-positives 3,302/4,515 isolates (73%) of S. aureus were MRSA; 99/290 (34%) of Enterococcus faecium were resistant to vancomycin; and 58% (663/1,136) of Streptococcus pneumoniae proportion were reduced susceptible to penicillin. Among Gram-negatives 59% (4,085/6,953) and 40% (1,186/2,958) of E. coli and K. pneumoniae produced ESBL and 29% (376/1,298) and 11% (961/8,830) were resistant to carbapenems, respectively. 79% (2855/3622) and 45% (1,514/3,376) of Acinetobacter spp. and Pseudomonas aeruginosa were carbapenem resistant, respectively. 88% (804/911) of Haemophilus influenzae were ampicillin resistant and 18/253 (7%) of Salmonella spp. and 7/46 (15%) of Shigella spp. were resistant to fluoroquinolones. The number of isolates from which data were submitted in the 2016-2017 period was twice as high as in 2012-2013. AMR proportions were higher in 2016-2017 for most pathogen-antimicrobial combinations of interest including imipenem-resistant A. baumannii, P. aeruginosa and Enterobacterales.

CONCLUSIONS

The data show alarmingly high and increasing resistant proportions among important organisms in Viet Nam. AMR proportions varied across hospital types and should be interpreted with caution because existing sampling bias and missing information on whether isolates were community or hospital acquired. Affordable and scalable ways to adopt a sample- or case-based approach across the network should be explored and clinical data should be integrated to help provide more accurate inferences of the surveillance data.