ReviewCurrent opinion in infectious diseases2026
Harnessing next-generation microbial diagnostics to optimize infection management in immunocompromised hosts.
Review in Current opinion in infectious diseases, 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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3 authors.
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Abstract
purpose of reviewConventional microbiological tests have limitations in the microbial diagnosis of immunocompromised patients. Next-generation sequencing (NGS) technologies have the potential to overcome some of these challenges by enabling rapid, comprehensive, and hypothesis-free pathogen detection, potentially improving the speed and accuracy of microbial diagnosis and subsequent clinical outcomes. This review summarizes current evidence for the use of NGS technologies in immunocompromised populations, highlights areas of demonstrated clinical impact, and identifies key priorities for broader clinical integration. RECENT
findingsCase reports and series have demonstrated the utility of NGS in diagnosing unusual or atypical infections amongst immunocompromised patients that were initially missed by conventional methods. Retrospective observational studies indicate that NGS can achieve higher sensitivity and greater pathogen detection rates than conventional diagnostics, although performance may be limited for certain pathogens, such as Aspergillus and Mycobacterial species. The clinical impact of NGS-guided interventions varies, reflecting both differences in study design and challenges in interpreting metagenomic data. SUMMARY: NGS technologies have the potential to enhance microbial diagnosis in immunocompromised patients, particularly in complex, polymicrobial, or atypical infections where conventional methods fail. However, widespread clinical adoption is limited by high costs, complex workflows, and the need for advanced bioinformatics infrastructure and expertise. Further research is required to define clinical impact, cost-effectiveness, and to standardize workflows and guide optimal time for implementation, in order to inform evidence-based integration of NGS into routine clinical practice.
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