CPHLN recommendations for the laboratory detection of Shiga toxin-producing Escherichia coli (O157 and non-O157).
Can Commun Dis Rep
; 44(11): 304-307, 2018 Nov 01.
Article
em En
| MEDLINE
| ID: mdl-30996693
Shiga toxin-producing Escherichia coli (STEC) are important enteric pathogens responsible for sporadic cases and outbreaks of gastroenteritis. E.coli O157:H7/NM (STEC O157) are the most commonly known STEC serotypes but it is now increasingly apparent that non-O157 STEC serotypes have been underreported in the past because they were not part of routine screening in many front-line laboratories. The Canadian Public Health Laboratory Network (CPHLN) has identified the need for improved detection and surveillance of non-O157 STEC and has developed the following recommendations to assist in the decision-making process for clinical and reference microbiology laboratories. These recommendations should be followed to the best of a laboratory's abilities based on the availability of technology and resources. The CPHLN recommends that when screening for the agents of bacterial gastroenteritis from a stool sample, front-line laboratories use either a chromogenic agar culture or a culture-independent diagnostic test (CIDT). CIDT options include nucleic acid amplification tests (NAATs) to detect Shiga toxin genes or enzyme immunoassays (EIAs) to detect Shiga toxins. If either CIDT method is positive for possible STEC, laboratories must have a mechanism to culture and isolate STEC in order to support both provincial and national surveillance as well as outbreak investigations and response. These CPHLN recommendations should result in improved detection of STEC in patients presenting with diarrhea, especially when due to the non-O157 serotypes. These measures should enhance the overall quality of healthcare and food safety, and provide better protection of the public via improved surveillance and outbreak detection and response.
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1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2018
Tipo de documento:
Article