The 2-hour stool-screening test (SST) effectively identifies most bacterial stool pathogens but struggles to exclude non-pathogenic coliforms. Laboratories should consider pathogen prevalence and workflow when adopting this rapid screening method.
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Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases·2008
Area of Science:
Clinical microbiology
Diagnostic testing
Bacteriology
Background:
Accurate identification of bacterial pathogens in stool samples is crucial for patient management.
Rapid diagnostic methods are needed to improve laboratory efficiency and patient care.
The 2-hour stool-screening test (SST) was developed as a rapid method for pathogen detection.
Purpose of the Study:
To evaluate the diagnostic accuracy of the 2-hour stool-screening test (SST) for identifying potential bacterial pathogens in stool samples.
To assess the SST's ability to differentiate between pathogens and non-pathogenic commensal bacteria.
To compare the SST's performance with conventional screening methods.
Main Methods:
The SST was used to screen 231 bacterial isolates from stool samples.
Organisms included Salmonella, Shigella, Arizona, Yersinia enterocolitica, Aeromonas hydrophila, Plesiomonas shigelloides, Proteus, Morganella, Providencia, Pseudomonas aeruginosa, and coliforms.
Screening results were compared with definitive identification.
Main Results:
The SST correctly screened all 54 Salmonella isolates.
Shigella and Yersinia enterocolitica were often grouped together (SYS) or with other bacteria (SYA).
The SST effectively excluded Proteus, Morganella, Providencia, and Pseudomonas aeruginosa but had a high false-positive rate for coliforms, with 69/80 coliforms requiring further testing.
Conclusions:
The SST offers rapid, same-day identification of potential stool pathogens when combined with a quick identification method.
Its main limitation is the inability to effectively screen out coliforms, necessitating further testing.
Laboratory suitability depends on local pathogen prevalence, workflow, and technologist acceptance.