ArticleInfection2026
Evaluating Seqstant LiveGene Analysis in real-time assessment of metagenomic next-generation sequencing (mNGS) data from respiratory samples.
Article in Infection, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Meeting the future at the Munich conference ESCMID-Global 2026.Infection · 2026Article
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Authors and funding
11 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe detection of pathogens causing infections by conventional diagnostic methods can be challenging and next-generation sequencing (NGS) technology offers a promising alternative method. In this study, we evaluated the performance of real-time metagenomic next-generation sequencing (rt-mNGS) for the detection of pathogens in respiratory samples.
methodWe used rt-mNGS, using the Seqstant LiveGene Analysis platform, on 335 respiratory samples in comparison to conventional culture results.
resultsWe observed an overall good concordance in 71.64% (240/335) of the methods. The rt-mNGS outperformed the gold standard culture in 16.12% (54/335) of the samples, while the culture was superior in detecting the clinically relevant pathogen in 12.24% (41/335) of the samples. The non-inferiority of rt-mNGS was statistically significant (δ = 10, α = 0.05, 1 - β = 0.8). We also observed that the real-time analysis of NGS data is beneficial in obtaining reliable, timely results, as the initial report at cycle 46 exhibits a Positive Predictive Value (PPV) of 93.75% at the species-level with a sensitivity of 32.09%.
conclusionOverall, our study showed the non-inferiority of rt-mNGS compared to the standard-of-care microbiology for respiratory samples with statistical significance. Moreover, the rt-mNGS method exhibited superior sensitivity and superior overall performance. It also uniquely detected certain organisms that are typically hard to culture. However, rt-mNGS reported a higher number of false positives and faced limitations in detecting Aspergillus spp. In conclusion, the study highlights the potential of rt-mNGS as a powerful tool in clinical diagnostics of respiratory infections and beyond.
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