ReviewOpen medicine (Warsaw, Poland)2026
Complementary mNGS and traditional testing for bloodstream infections.
Review in Open medicine (Warsaw, Poland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Authors and funding
5 authors.
Funding
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Abstract
Bloodstream infections (BSIs) require rapid and accurate etiological diagnosis to guide timely antimicrobial therapy. Conventional diagnostic approaches, particularly blood culture, remain indispensable for antimicrobial susceptibility testing; however, they are limited by prolonged turnaround time and reduced sensitivity, especially following prior antibiotic exposure. Metagenomic next-generation sequencing (mNGS) has emerged as a culture-independent and hypothesis-free diagnostic tool capable of detecting a broad spectrum of pathogens directly from clinical samples. This approach is particularly advantageous for identifying rare, fastidious, and polymicrobial infections, as well as infections in immunocompromised patients. However, its clinical application remains constrained by challenges in distinguishing infection from colonization, interpreting antimicrobial resistance signals, and variability in bioinformatics pipelines. Thus, in the era of integrated diagnosis, mNGS does not replace but powerfully complements traditional methods. Furthermore, we propose a dynamic evidence-weighted integrated diagnostic framework to guide real time clinical decision and improve the clinical applicability of mNGS in bloodstream infections.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.