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Table 1_An NGS-assisted diagnostic workflow for culture-independent detection of bloodstream pathogens and prediction of antimicrobial resistances in sepsis.docx

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Table_1_An_NGS-assisted_diagnostic_workflow_for_culture-independent_detection_of_bloodstream_pathogens_and_prediction_of_antimicrobial_resistances_in_sepsis_docx/30021472
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BackgroundTimely and accurate identification of bloodstream pathogens is critical for targeted antimicrobial therapy in sepsis. Conventional blood cultures remain the Standard-of-Care (SoC) for pathogen identification but are limited by low sensitivity and prolonged turnaround times, hampering timely and targeted antimicrobial stewardship. Advances in next-generation sequencing (NGS) offer potential for culture-independent, rapid, and comprehensive detection of pathogens and prediction of antimicrobial resistance. This study evaluated the diagnostic performance of PISTE™ technology, an NGS-based diagnostic workflow combining full-length 16S rRNA gene sequencing and metagenomic analysis for the diagnosis of circulating bacteria in sepsis. MethodsIn this prospective, multicenter, phase IIa proof-of-concept study, adult patients with suspected sepsis were enrolled from four hospitals in Athens, Greece. Blood samples were collected prior to antibiotic initiation and processed using SoC cultures and PISTE platform. PISTE integrates automated DNA purification (KingFisher, Thermo Fisher Scientific), full-length 16S rRNA gene sequencing, metagenomics analysis (SQK-PRB114.24, Oxford Nanopore Technologies), and real-time sequencing using Oxford Nanopore GridION Mk1b device. A dedicated analysis pipeline was developed for accurate pathogen detection and prediction of antimicrobial resistance profiles. The primary endpoint was the diagnostic concordance between PISTE and SoC cultures. ResultsA total of 100 patients (median age 79 years, median Charlson’s Comorbidity Index 5) were enrolled. Of these, 71 patients met Sepsis-3 criteria. In this subgroup, PISTE showed an overall accuracy of 95.7%, with a sensitivity of 91.7%, specificity of 96.5%, positive predictive value of 84.6%, and negative predictive value of 98.2% compared to SoC. The median time to pathogen identification and Antimicrobial Susceptibility Testing (AST) with PISTE was 12.0 hours, significantly faster than in SoC cultures (30.4 hours, p < 0.0001). Resistance gene profiling showed strong agreement with SoC AST results, particularly for β-lactam and carbapenem resistance. ConclusionsPISTE technology exhibited high diagnostic accuracy and significantly reduced turnaround time compared to conventional cultures, supporting its potential as a short turnaround time and reliable diagnostic tool for bloodstream infections. Further optimization and validation in larger cohorts are warranted to enhance clinical implementation and improve antimicrobial stewardship in sepsis management.
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2025-09-01
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