76 research outputs found
Extraintestinal pathogenic Escherichia coli (ExPEC) ST221 isolated in the microbiome of swine in South Africa
High prevalence of multidrug resistant ESBL- and plasmid mediated AmpC-producing clinical isolates of Escherichia coli at Maputo Central Hospital, Mozambique
Background: Epidemiological data of cephalosporin-resistant Enterobacterales in Sub-Saharan Africa is still restricted,and in particular in Mozambique. The aim of this study was to detect and characterize extended-spectrum β-lactamase (ESBL) - and plasmid-mediated AmpC (pAmpC)-producing clinical strains of Escherichia coli at Maputo Central Hospital (MCH), a 1000-bed reference hospital in Maputo, Mozambique.
Methods: A total of 230 clinical isolates of E. coli from urine (n = 199) and blood cultures (n = 31) were collected at MCH during August–November 2015. Antimicrobial susceptibility testing was performed by the disc diffusion
method and interpreted according to EUCAST guidelines. Isolates with reduced susceptibility to 3rd generation
cephalosporins were examined further; phenotypically for an ESBL−/AmpC-phenotype by combined disc methods
and genetically for ESBL- and pAmpC-encoding genes by PCR and partial amplicon sequencing as well as genetic
relatedness by ERIC-PCR.
Results: A total of 75 isolates with reduced susceptibility to cefotaxime and/or ceftazidime (n = 75) from urine (n = 58/199; 29%) and blood (n = 17/31; 55%) were detected. All 75 isolates were phenotypically ESBL-positive and 25/75
(33%) of those also expressed an AmpC-phenotype. ESBL-PCR and amplicon sequencing revealed a majority of
blaCTX-M (n = 58/75; 77%) dominated by blaCTX-M-15. All AmpC-phenotype positive isolates (n = 25/75; 33%) scored
positive for one or more pAmpC-genes dominated by blaMOX/FOX. Multidrug resistance (resistance ≥ three antibiotic classes) was observed in all the 75 ESBL-positive isolates dominated by resistance to trimethoprimsulfamethoxazole, ciprofloxacin and gentamicin. ERIC-PCR revealed genetic diversity among strains with minor clusters indicating intra-hospital spread.
Conclusion: We have observed a high prevalence of MDR pAmpC- and/or ESBL-producing clinical E. coli isolates
with FOX/MOX and CTX-Ms as the major β-lactamase types, respectively. ERIC-PCR analyses revealed genetic
diversity and some clusters indicating within-hospital spread. The overall findings strongly support the urgent need for accurate and rapid diagnostic services to guide antibiotic treatment and improved infection control measures
Genomic characterisation of Staphylococcus aureus ST121 isolated from hospitalised patients in South Africa
Extended-spectrum beta-lactamase-producing Escherichia coli harbouring mcr-1 gene isolated from pigs in South Africa
Genomic characterisation of Klebsiella michiganensis co-producing OXA-181 and NDM-1 carbapenemases isolated from a cancer patient in uMgungundlovu District, KwaZulu-Natal Province, South Africa
Statistical Methods Used to Test for Agreement of Medical Instruments Measuring Continuous Variables in Method Comparison Studies: A Systematic Review
BACKGROUND: Accurate values are a must in medicine. An important parameter in determining the quality of a medical instrument is agreement with a gold standard. Various statistical methods have been used to test for agreement. Some of these methods have been shown to be inappropriate. This can result in misleading conclusions about the validity of an instrument. The Bland-Altman method is the most popular method judging by the many citations of the article proposing this method. However, the number of citations does not necessarily mean that this method has been applied in agreement research. No previous study has been conducted to look into this. This is the first systematic review to identify statistical methods used to test for agreement of medical instruments. The proportion of various statistical methods found in this review will also reflect the proportion of medical instruments that have been validated using those particular methods in current clinical practice. METHODOLOGY/FINDINGS: Five electronic databases were searched between 2007 and 2009 to look for agreement studies. A total of 3,260 titles were initially identified. Only 412 titles were potentially related, and finally 210 fitted the inclusion criteria. The Bland-Altman method is the most popular method with 178 (85%) studies having used this method, followed by the correlation coefficient (27%) and means comparison (18%). Some of the inappropriate methods highlighted by Altman and Bland since the 1980s are still in use. CONCLUSIONS: This study finds that the Bland-Altman method is the most popular method used in agreement research. There are still inappropriate applications of statistical methods in some studies. It is important for a clinician or medical researcher to be aware of this issue because misleading conclusions from inappropriate analyses will jeopardize the quality of the evidence, which in turn will influence quality of care given to patients in the future
Exploiting genomics for antimicrobial resistance surveillance at One Health interfaces.
The intersection of human, animal, and ecosystem health at One Health interfaces is recognised as being of key importance in the evolution and spread of antimicrobial resistance (AMR) and represents an important, and yet rarely realised opportunity to undertake vital AMR surveillance. A working group of international experts in pathogen genomics, AMR, and One Health convened to take part in a workshop series and online consultation focused on the opportunities and challenges facing genomic AMR surveillance in a range of settings. Here we outline the working group's discussion of the potential utility, advantages of, and barriers to, the implementation of genomic AMR surveillance at One Health interfaces and propose a series of recommendations for addressing these challenges. Embedding AMR surveillance at One Health interfaces will require the development of clear beneficial use cases, especially in low-income and middle-income countries. Evidence of directionality, risks to human and animal health, and potential trade implications were also identified by the working group as key issues. Addressing these challenges will be vital to enable genomic surveillance technology to reach its full potential for assessing the risk of transmission of AMR between the environment, animals, and humans at One Health interfaces.
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