Dataset Information

Global forecast of antimicrobial resistance in invasive isolates of Escherichia coli and Klebsiella pneumoniae.

ABSTRACT:

Objectives

To project future antimicrobial resistance (AMR) in Escherichia coli and Klebsiella pneumoniae.

Methods

Mixed linear models were constructed from a sample of countries with AMR data in the ResistanceMap database. Inverse probability weighting methods were used to account for countries without AMR data.

Results

The estimated prevalence of AMR in 2015 was 64.5% (95% confidence interval (CI) 42-87%) for third-generation cephalosporin-resistant (3GCR) Escherichia coli, 5.8% (95% CI 1.8-9.7%) for carbapenem-resistant (CR) E. coli, 66.9% (95% CI 47.1-86.8%) for 3GCR Klebsiella pneumoniae, and 23.4% (95% CI 7.4-39.4%) for CR K. pneumoniae. The projected AMR prevalence in 2030 was 77% (95% CI 55-99.1%) for 3GCR E. coli, 11.8% (95% CI 3.7-19.9%) for CR E. coli, 58.2% (95% CI 50.2-66.1%) for 3GCR K. pneumoniae, and 52.8% (95% CI 16.3-89.3%) for CR K. pneumoniae.

Conclusions

The models suggest that third-generation cephalosporins and carbapenems could be ineffective against a sizeable proportion of infections by E. coli and K. pneumoniae in most parts of the world by 2030, supporting both the need to enhance stewardship efforts and to prioritize research and development of new antibiotics for resistant Enterobacteriaceae.

SUBMITTER: Alvarez-Uria G

PROVIDER: S-EPMC5889426 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Publications

Global forecast of antimicrobial resistance in invasive isolates of Escherichia coli and Klebsiella pneumoniae.

Alvarez-Uria Gerardo G Gandra Sumanth S Mandal Siddhartha S Laxminarayan Ramanan R

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases 20180202

<h4>Objectives</h4>To project future antimicrobial resistance (AMR) in Escherichia coli and Klebsiella pneumoniae.<h4>Methods</h4>Mixed linear models were constructed from a sample of countries with AMR data in the ResistanceMap database. Inverse probability weighting methods were used to account for countries without AMR data.<h4>Results</h4>The estimated prevalence of AMR in 2015 was 64.5% (95% confidence interval (CI) 42-87%) for third-generation cephalosporin-resistant (3GCR) Escherichia col ...[more]

PMID: 29410253

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Project description:OBJECTIVES:Whole-genome sequencing potentially represents a single, rapid and cost-effective approach to defining resistance mechanisms and predicting phenotype, and strain type, for both clinical and epidemiological purposes. This retrospective study aimed to determine the efficacy of whole genome-based antimicrobial resistance prediction in clinical isolates of Escherichia coli and Klebsiella pneumoniae. METHODS:Seventy-four E. coli and 69 K. pneumoniae bacteraemia isolates from Oxfordshire, UK, were sequenced (Illumina HiSeq 2000). Resistance phenotypes were predicted from genomic sequences using BLASTn-based comparisons of de novo-assembled contigs with a study database of >100 known resistance-associated loci, including plasmid-associated and chromosomal genes. Predictions were made for seven commonly used antimicrobials: amoxicillin, co-amoxiclav, ceftriaxone, ceftazidime, ciprofloxacin, gentamicin and meropenem. Comparisons were made with phenotypic results obtained in duplicate by broth dilution (BD Phoenix). Discrepancies, either between duplicate BD Phoenix results or between genotype and phenotype, were resolved with gradient diffusion analyses. RESULTS:A wide variety of antimicrobial resistance genes were identified, including blaCTX-M, blaLEN, blaOKP, blaOXA, blaSHV, blaTEM, aac(3')-Ia, aac-(3')-IId, aac-(3')-IIe, aac(6')-Ib-cr, aadA1a, aadA4, aadA5, aadA16, aph(6')-Id, aph(3')-Ia, qnrB and qnrS, as well as resistance-associated mutations in chromosomal gyrA and parC genes. The sensitivity of genome-based resistance prediction across all antibiotics for both species was 0.96 (95% CI: 0.94-0.98) and the specificity was 0.97 (95% CI: 0.95-0.98). Very major and major error rates were 1.2% and 2.1%, respectively. CONCLUSIONS:Our method was as sensitive and specific as routinely deployed phenotypic methods. Validation against larger datasets and formal assessments of cost and turnaround time in a routine laboratory setting are warranted.

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Dataset Information

Global forecast of antimicrobial resistance in invasive isolates of Escherichia coli and Klebsiella pneumoniae.

Objectives

Methods

Results

Conclusions

Publications

Global forecast of antimicrobial resistance in invasive isolates of Escherichia coli and Klebsiella pneumoniae.

Similar Datasets

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