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El Mammery A, Ramírez de Arellano E, Cañada-García JE, Cercenado E, Villar-Gómara L, Casquero-García V, García-Cobos S, Lepe JA, Ruiz de Gopegui Bordes E, Calvo-Montes J, Larrosa Escartín N, Cantón R, Pérez-Vázquez M, Aracil B, Oteo-Iglesias J. An increase in erythromycin resistance in methicillin-susceptible Staphylococcus aureus from blood correlates with the use of macrolide/lincosamide/streptogramin antibiotics. EARS-Net Spain (2004-2020). Front Microbiol 2023; 14:1220286. [PMID: 37822743 PMCID: PMC10562549 DOI: 10.3389/fmicb.2023.1220286] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Accepted: 09/08/2023] [Indexed: 10/13/2023] Open
Abstract
Objectives To describe and analyse erythromycin resistance trends in blood isolates of Staphylococcus aureus (EARS-Net Spain, 2004-2020) and the association of these trends with the consumption of macrolide, lincosamide, and streptogramin B (MLSB) antibiotics. To assess molecular changes that could be involved in erythromycin resistance trends by whole genome analysis of representative isolates. Materials and methods We collected antibiotic susceptibility data for all first-blood S. aureus isolates in patients from 47 Spanish hospitals according to EARS-Net criteria. MLSB antibiotic consumption was obtained from the Spanish Agency for Medicines and Medical Devices (2008-2020). We sequenced 137 representative isolates for core genome multilocus sequence typing, resistome and virulome analysis. Results For the 36,612 invasive S. aureus isolates, methicillin resistance decreased from 26.4% in 2004 to 22.4% in 2020. Erythromycin resistance in methicillin-susceptible S. aureus (MSSA) increased from 13.6% in 2004 to 28.9% in 2020 (p < 0.001); however, it decreased from 68.7 to 61.8% (p < 0.0001) in methicillin-resistant S. aureus (MRSA). Total consumption of MLSB antibiotics increased from 2.72 defined daily doses per 1,000 inhabitants per day (DID) in 2014 to 3.24 DID in 2016. By WGS, the macrolide resistance genes detected were erm (59.8%), msrA (46%), and mphC (45.2%). The erm genes were more prevalent in MSSA (44/57, 77.2%) than in MRSA (38/80, 47.5%). Most of the erm genes identified in MSSA after 2013 differed from the predominant ermC gene (17/22, 77.3%), largely because ermT was significantly associated with MSSA after 2013 (11/29, 37.9%). All 13 ermT isolates in this study, except one, belonged to ST398 and came from 10 hospitals and six Spanish provinces. Conclusion The significant increase in erythromycin resistance in blood MSSA correlated with the consumption of the MLSB antibiotics in Spain. These preliminary data seem support the hypothesis that the human ST398 MSSA clade with ermT-mediated resistance to erythromycin may be involved in this trend.
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Affiliation(s)
- Achraf El Mammery
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- Escuela Internacional de Doctorado, Ciencias Biomédicas y Salud Pública - IMIENS (UNED), Madrid, Spain
| | - Eva Ramírez de Arellano
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
| | - Javier E. Cañada-García
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- Escuela Internacional de Doctorado, Ciencias Biomédicas y Salud Pública - IMIENS (UNED), Madrid, Spain
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
| | - Emilia Cercenado
- Servicio de Microbiología, Hospital General Universitario Gregorio Marañón, Madrid, Spain
- CIBER de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III, Madrid, Spain
| | - Laura Villar-Gómara
- Agencia Española de Medicamentos y Productos Sanitarios (AEMPS), Madrid, Spain
| | - Verónica Casquero-García
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - Silvia García-Cobos
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
| | - José Antonio Lepe
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
- Servicio de Microbiología, Hospital Universitario Virgen del Rocío, Sevilla, Spain
| | - Enrique Ruiz de Gopegui Bordes
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
- Servicio de Microbiología, Hospital Universitario Son Espases, Palma de Mallorca, Spain
| | - Jorge Calvo-Montes
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
- Servicio de Microbiología, Hospital Universitario Marqués de Valdecilla-IDIVAL, Santander, Spain
| | - Nieves Larrosa Escartín
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
- Servicio de Microbiología, Hospital Universitario Vall d’Hebron, Barcelona, Spain
| | - Rafael Cantón
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
- Servicio de Microbiología, Hospital Universitario Ramón y Cajal, Madrid, Spain
| | - María Pérez-Vázquez
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
| | - Belén Aracil
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
| | - Jesús Oteo-Iglesias
- Laboratorio de Referencia e Investigación en Resistencia a Antibióticos e Infecciones Relacionadas con la Asistencia Sanitaria, Centro Nacional de Microbiología, Instituto de Salud Carlos III, Madrid, Spain
- CIBER de Enfermedades Infecciosas (CIBERINFEC), Instituto Salud Carlos III, Madrid, Spain
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Ayobami O, Willrich N, Suwono B, Eckmanns T, Markwart R. The epidemiology of carbapenem-non-susceptible Acinetobacter species in Europe: analysis of EARS-Net data from 2013 to 2017. Antimicrob Resist Infect Control 2020; 9:89. [PMID: 32560670 PMCID: PMC7304165 DOI: 10.1186/s13756-020-00750-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Accepted: 06/04/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Due to limited therapeutic options and their association with high mortality and morbidity, carbapenem-non-susceptible Acinetobacter spp. (CNA) are of significant public health importance. This study aimed to describe current epidemiological trends of CNA proportions in Europe and to identify factors that are associated with carbapenem non-susceptibility of isolates from patients with invasive Acinetobacter spp. infections. METHODS Data from routine carbapenem susceptibility testing of 18,412 invasive clinical Acinetobacter spp. isolates from 30 European countries in 2013-2017 were analysed using descriptive statistical analyses and uni- and multivariable regression analyses. These data were obtained from the European Antimicrobial Resistance Surveillance Network (EARS-Net). RESULTS The population-weighted mean proportion of carbapenem-non-susceptible Acinetobacter spp. in Europe is 35.6% (95% confidence interval [CI] 29.7-42.0%). With CNA proportions of 75.5% (95% CI 71.2-79.4%) and 71.5% (95% CI 66.7-75.9%) the burden of CNA is particularly high in Southern and Eastern European regions. In contrast, Northern and Western European regions recorded CNA proportions of 2.8% (95% CI 1.2-6.0%) and 6.3% (95% CI 4.5-8.9%), respectively. Population-weighted mean CNA proportions are especially high in Acinetobacter spp. isolates from intensive care units (54.0% [95% CI 47.6-60.3%]). Male gender, age above 20 years and ICU admission were identified as independent factors associated with an increased likelihood of CNA. CONCLUSION The burden of carbapenem-non-susceptible Acinetobacter spp. is particularly high in Southern and Eastern Europe. There is a risk that resistance could spread to other parts of Europe. Therefore, increased efforts in infection control and antibiotic stewardship, particularly in Intensive Care Units, are necessary to combat the spread of CNA in Europe.
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Affiliation(s)
- Olaniyi Ayobami
- Department 3: Infectious Disease Epidemiology, Unit 37: Healthcare-associated Infections, Surveillance of Antibiotic Resistance and Consumption, Robert Koch Institute, Nordufer 20, 13353, Berlin, Germany
| | - Niklas Willrich
- Department 3: Infectious Disease Epidemiology, Unit 37: Healthcare-associated Infections, Surveillance of Antibiotic Resistance and Consumption, Robert Koch Institute, Nordufer 20, 13353, Berlin, Germany
| | - Beneditta Suwono
- Department 3: Infectious Disease Epidemiology, Unit 37: Healthcare-associated Infections, Surveillance of Antibiotic Resistance and Consumption, Robert Koch Institute, Nordufer 20, 13353, Berlin, Germany.,Federal Institute for Risk Assessment, Unit Epidemiology, Zoonoses and Antimicrobial Resistance Department Biology Safety, Berlin, Germany
| | - Tim Eckmanns
- Department 3: Infectious Disease Epidemiology, Unit 37: Healthcare-associated Infections, Surveillance of Antibiotic Resistance and Consumption, Robert Koch Institute, Nordufer 20, 13353, Berlin, Germany
| | - Robby Markwart
- Department 3: Infectious Disease Epidemiology, Unit 37: Healthcare-associated Infections, Surveillance of Antibiotic Resistance and Consumption, Robert Koch Institute, Nordufer 20, 13353, Berlin, Germany.
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Ortega-Huedo R, Cuesta M, Hoefer A, Gonzalez-Zorn B. Econometric ARIMA methodology to elucidate the evolution of trends in nosocomial antimicrobial resistance rates in the European Union. Int J Antimicrob Agents 2020; 55:105800. [PMID: 31521811 DOI: 10.1016/j.ijantimicag.2019.09.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2019] [Revised: 08/20/2019] [Accepted: 09/07/2019] [Indexed: 11/22/2022]
Abstract
BACKGROUND Infections with bacteria harbouring resistance to cephalosporins or fluoroquinolones (FQ) constitute a serious hazard to human health. OBJECTIVES To establish a methodology based on econometric analysis and the largest European Union (EU) resistance database (EARS-Net), to model nosocomial antimicrobial resistance (AMR) in the EU and to detect tendency changes, steps or peaks. The contribution of legislation based on third-generation cephalosporin (3GC) and FQ class referrals to resistance rate patterns is evaluated. METHODS Resistance to 3GC and FQ was examined in nosocomial Escherichia coli, Klebsiella pneumoniae and Pseudomonas aeruginosa in at least 25 out of 30 EU countries (> 94% population coverage), weighted by their mean annual population, between 2006 and 2016. Autoregressive integrated moving average (ARIMA) model analysis, inspired by Box-Jenkins methodology, was prepared to adjust series to a mathematical model to detect hypothetical changes in the general behaviour. To the best of the authors' knowledge, this is the first study to use ARIMA with interventions to model overall nosocomial AMR data compiled in EARS-Net. RESULTS AND CONCLUSIONS Econometric ARIMA models statistically prove the occurence of slowdowns and reversions in the increasing trend of AMR prevalence in nosocomial E. coli and K. pneumoniae to 3GC and FQ, as well as resistance of P. aeruginosa to 3GC. The resistance of P. aeruginosa to FQ exhibited a descending slope. The presented decreasing trends constitute noteworthy milestones in tackling AMR in Europe.
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