The aim of this study was to investigate the value of syndromic diagnostic testing for a better understanding of the epidemiology of gastrointestinal infections in Denmark. Here we evaluated the QIAstat-Dx® Gastrointestinal (GI) Panel 1 assay on 18,610 fecal samples requested for analysis for enteric pathogens in Region Zealand, Denmark, in 1 year (October 1, 2021, to September 30, 2022). In total, 6905 (37%) samples were detected positive for one or more diarrhoeal bacteria, viruses, and protozoa. The most common bacterial, viral, and parasitic pathogens detected with the QIAstat-Dx® Gastrointestinal Panel 1 were EPEC (in patients ≥ 2 years of age) (n = 1420 (20.6%)), rotavirus (n = 948 (13.7%)), and Cryptosporidium spp. (n = 196 (2.84%)). We identified a large diversity in infections likely reflecting substantial differences in the epidemiology including origin of infections, mode of transmission, seasonality, age-dependent susceptibility to disease, severity, and travel history. All pathogens were detected as both single and coinfections. Viral infections peaked in March with a positive rate of 31.6%, and bacterial infections peaked in August with a positive rate of 35.3%. ETEC, Shigella/EIEC, EAEC, and P. shigelloides were most related to travel activity, and coinfections were frequent. The distribution of C_t values varied significantly between the pathogens, with the lowest C_t values (median 17–18) observed in astrovirus, adenovirus, and rotavirus. Our results highlight the value of providing extensive diagnostic testing on fecal samples for sufficient detection of relevant diarrhoeal pathogens for optimal clinical care.

Background: Nosocomial pneumonia (NP) is a significant cause of morbidity and mortality in intensive care unit (ICU) patients. Prior antibiotic use, polymicrobial infections, and the limitations of conventional microbiological methods often complicate an accurate diagnosis. Bronchoalveolar lavage (BAL) and tracheal suction (TS) are commonly used methods for collecting respiratory samples; however, their diagnostic accuracy can vary. Additionally, microbiome analysis using 16S/18S rRNA gene sequencing provides an alternative approach for identifying pathogens that are difficult to culture. This study aimed to compare the diagnostic value of routine culturing and microbiome analysis in identifying pathogens in ICU patients with NP. Methods: A prospective cohort study was conducted in 23 critically ill patients at Zealand University Hospital. Samples from TS and BAL were collected from patients with suspected NP. Both culturing and 16S/18S rRNA gene amplicon-based microbiome analysis were performed to identify pathogens. Findings were compared between the two types of samples and between the two analysis methods. Results: A total of 46 samples were analyzed (23 TS and 23 BAL). Culture results showed complete concordance in 60.9% of cases and partial concordance in 21.7% between results from TS and BAL. Discrepancies often involved low-virulence organisms, such as Staphylococcus epidermidis and Candida albicans. Microbiome analysis revealed a broader spectrum of microbial diversity, detecting pathogens such as Pasteurella canis and Tropheryma whipplei that were previously missed by culture methods. In 34.8% of the samples, the pathogen identified by microbiome analysis was also detected by culture. However, microbiome analysis also identified additional microorganisms in 17.4% of the cases, which were not detected by culture. When comparing microbiome results between TS and BAL, 16 out of 23 (69.5%) showed complete concordance. Conclusions: The findings were similar in TS and BAL, both for culture and 16S/18S amplicon-based microbiome analyses. Microbiome analysis using 16S/18S rRNA gene sequencing provided new insights into NP patients, identifying pathogens that were previously undetected by conventional culturing methods. Combining microbiome analysis with traditional culture techniques could enhance the diagnostic accuracy for NP. Further studies are needed to refine diagnostic thresholds and assess the clinical impact of microbiome-based diagnostics.