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Background Ventilator-associated lower respiratory tract infection (VA-LRTI) is common among critically ill patients and has been associated with increased morbidity and mortality. In acute critical illness, respiratory microbiome disruption indices (MDIs) have been shown to predict risk for VA-LRTI, but their utility beyond the first days of critical illness is unknown. We sought to characterize how MDIs previously shown to predict VA-LRTI at initiation of mechanical ventilation change with prolonged mechanical ventilation, and if they remain associated with VA-LRTI risk. Methods We developed a cohort of 83 subjects admitted to a long-term acute care hospital due to their prolonged dependence on mechanical ventilation; performed dense, longitudinal sampling of the lower respiratory tract, collecting 1066 specimens; and characterized the lower respiratory microbiome by 16S rRNA sequencing as well as total bacterial abundance by 16S rRNA quantitative polymerase chain reaction. Results Cross-sectional MDIs, including low Shannon diversity and high total bacterial abundance, were associated with risk for VA-LRTI, but associations had wide posterior credible intervals. Persistent lower respiratory microbiome disruption showed a more robust association with VA-LRTI risk, with each day of (base e) Shannon diversity <2.0 associated with a VA-LRTI odds ratio of 1.36 (95% credible interval, 1.10–1.72). The observed association was consistent across multiple clinical definitions of VA-LRTI. Conclusions Cross-sectional MDIs have limited ability to discriminate VA-LRTI risk during prolonged mechanical ventilation, but persistent lower respiratory tract microbiome disruption, best characterized by consecutive days with low Shannon diversity, may identify a population at high risk for infection and may help target infection-prevention interventions. [ABSTRACT FROM AUTHOR]

Objective: Little is known about temporal changes in nasal bacteria in granulomatosis with polyangiitis (GPA). This study was undertaken to examine longitudinal changes in the nasal microbiome in association with relapse in GPA patients. Methods: Bacterial 16S ribosomal RNA gene sequencing was performed on nasal swabs from 19 patients with GPA who were followed up longitudinally for a total of 78 visits, including 9 patients who experienced a relapse and 10 patients who remained in remission. Relative abundance of bacteria and ratios between bacteria were examined. Generalized estimating equation models were used to evaluate the association between bacterial composition and 1) disease activity and 2) levels of antineutrophil cytoplasmic antibody (ANCA) with specificity for proteinase 3 (PR3), adjusted for medication. Results: Corynebacterium and Staphylococcus were the most abundant bacterial genera across all nasal samples. Patients with quiescent disease maintained a stable ratio of Corynebacterium to Staphylococcus across visits. In contrast, in patients who experienced a relapse, a significantly lower ratio was observed at the visit prior to relapse, followed by a higher ratio at the time of relapse (adjusted P < 0.01). Species‐level analysis identified an association between a higher abundance of nasal Corynebacterium tuberculostearicum and 1) relapse (adjusted P = 0.04) and 2) higher PR3‐ANCA levels (adjusted P = 0.02). Conclusion: In GPA, significant changes occur in the nasal microbiome over time and are associated with disease activity. The occurrence of these changes months prior to the onset of relapse supports a pathogenic role of nasal bacteria in GPA. Our results uphold existing hypotheses implicating Staphylococcus as an instigator of disease and have generated a novel finding involving Corynebacterium as a potential mediator of disease in GPA. [ABSTRACT FROM AUTHOR]