2021
DOI: 10.1038/s41598-021-02755-5
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Antimicrobial resistance in commensal opportunistic pathogens isolated from non-sterile sites can be an effective proxy for surveillance in bloodstream infections

Abstract: Antimicrobial resistance (AMR) surveillance in bloodstream infections (BSIs) is challenging in low/middle-income countries (LMICs) given limited laboratory capacity. Other specimens are easier to collect and process and are more likely to be culture-positive. In 8102 E. coli BSIs, 322,087 E. coli urinary tract infections, 6952 S. aureus BSIs and 112,074 S. aureus non-sterile site cultures from Oxfordshire (1998–2018), and other (55,296 isolates) rarer commensal opportunistic pathogens, antibiotic resistance tr… Show more

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Cited by 7 publications
(2 citation statements)
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“…This study investigated the fungi associated with dried samples of Tomatoes using the two developed dryers Hybrid (PVT) and Solar Thermal (ST) solar Thermal respectively, the result revealed the presence of some fungi. The fungi isolated were S.cereviceae, S.pombe, F.oxyspurum and F.solani, the result revelled that F.solani has the highest frequency of occurrence with 28 % while S. pombe has the lowest occurrence of 3.45.The result in table 5and shows the frequency occurrence of fungi in the two different samples (Karina et al, 2021).…”
Section: Identification and Isolation Of Fungimentioning
confidence: 86%
“…This study investigated the fungi associated with dried samples of Tomatoes using the two developed dryers Hybrid (PVT) and Solar Thermal (ST) solar Thermal respectively, the result revealed the presence of some fungi. The fungi isolated were S.cereviceae, S.pombe, F.oxyspurum and F.solani, the result revelled that F.solani has the highest frequency of occurrence with 28 % while S. pombe has the lowest occurrence of 3.45.The result in table 5and shows the frequency occurrence of fungi in the two different samples (Karina et al, 2021).…”
Section: Identification and Isolation Of Fungimentioning
confidence: 86%
“…We designed a flexible R script to convert minimum inhibitory concentrations (MIC) in the monitoring systems to resistant/susceptible labels using CLSI and EUCAST thresholds and aggregate AMR estimates across monitoring systems for any chosen combination of countries, years, bacteria, and antibiotics. All isolates were aggregated regardless of the sample source (blood, urine, stool etc…), as previous work has suggested resistance profiles are similar for commensal opportunistic pathogens across different sample sources [15].…”
Section: Data Reformatting and Combinationmentioning
confidence: 99%