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Diagnostic microbiology and infectious disease · 2026

Diagnostic accuracy of a multiplex nucleic acid amplification test for detecting gastrointestinal bacterial pathogens: A multicenter clinical study.

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McMillian Ray, Paradis Sonia, Lockamy Elizabeth, Garrett Elizabeth, Bobenchik April M, Young Jesse, Ermel Aaron C

Аннотация

BACKGROUND: Symptoms of many gastrointestinal infections are similar, making it difficult to differentiate the causative agents. Automated PCR-based diagnostic systems can rapidly detect and identify pathogens responsible for these infections.

METHODS: BD Enteric Bacterial Panel plus (EBP plus Assay) for BD COR System was assessed versus a single comparator (BioFire™ FilmArray™ GI Panel) or a composite reference (≥2 of 3 assays: BioFire FilmArray GI Panel, BioCode™ GPP, and BD MAX™ EBP/xEBP) for detecting enteric pathogens using patient stool specimens. Positive and negative percent agreement (PPA and NPA) between EBP plus Assay and comparator method(s) were calculated with 95% two-sided confidence intervals (CIs). Agreement ≥90% with CI lower bounds ≥80% was considered acceptable performance. Contrived specimens were included for low prevalence targets.

RESULTS: There were 1737 specimens analyzed. NPA met performance thresholds (≥98.4%) for all targets. PPA met performance thresholds for Salmonella spp., Campylobacter spp., and Shiga toxin. Due to low prevalence in the study population, the PPA lower bound of the 95% CI was below the threshold for Shigella spp./enteroinvasive Escherichia coli, Vibrio spp., and Yersinia enterocolitica, while PPA point estimates were not met for Plesiomonas shigelloides and enterotoxigenic E. coli (ETEC). PPA and NPA thresholds were met in contrived specimen testing for Shiga toxin, Vibrio spp., Plesiomonas shigelloides, Yersinia enterocolitica, and ETEC.

CONCLUSIONS: The EBP plus Assay implemented on the BD COR System demonstrated good concordance with the comparator method(s) for detecting enteric bacterial pathogens in stool and is suited for high-throughput laboratories seeking to enhance task automation without impacting accuracy.