Comparison of the Luminex® NxTAG® Gastrointestinal Pathogen Panel to traditional diagnostic methods for detecting diarrhoea-associated gastroenteritis

<b>Introduction.</b> Gastrointestinal infections remain a leading cause of morbidity and mortality within the UK.<b>Hypothesis.</b> The Luminex^® NxTAG^® Gastrointestinal Pathogen Panel (NxTAG GPP) multiplex reverse transcriptase PCR assay performs equivalently to standard-of-care diagnostic approaches.<b>Aim.</b> To compare the analytical performance of the NxTAG GPP assay versus routine diagnostic testing methods in a district general hospital setting.<b>Methodology.</b> Gastrointestinal pathogens in 159 faecal specimens from hospital inpatients and outpatient clinics were comparatively analysed using the NxTAG GPP assay versus traditional culture, enzyme immunoassay and molecular methods.<b>Results.</b> Positive results were detected in 45 out of 159 specimens (28.3%) by NxTAG GPP, which was a higher positivity rate when compared with traditional diagnostic methods which detected 31 out of 159 (19.5%) positive infections (<i>P</i>=0.087 by Fisher's exact test). Infections were caused by a single organism in 40 out of 45 (88.9%) cases, but 5 out of 45 (11.1%) infections detected were due to coinfections. No coinfections were detected by traditional methods. <i>Campylobacter</i> Group was the most common enteropathogen detected with 15 out of 52 (28.9%) infections. Viruses caused 26.9% of infections, including 15.4% being norovirus. Overall sensitivity, specificity and accuracy for the NxTAG GPP assay were 97.6%, 99.7% and 99.5%, respectively, for enteropathogenic bacteria and viruses detected during this study. No parasites were detected during this study and were not included in comparisons.<b>Conclusions.</b> The NxTAG GPP assay demonstrated high sensitivity and specificity for identifying gastrointestinal pathogens, with comparable accuracy as more resource-intensive and time-consuming standard diagnostic approaches. The NxTAG GPP has the potential to enhance patient diagnosis, reduce turnaround time and improve clinical outcomes compared to routine diagnostic methods.