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Updated: Oct 25, 2025

Murine Oropharyngeal Aspiration Model of Ventilator-associated and Hospital-acquired Bacterial Pneumonia
Published on: June 28, 2018
Respiratory Microbiome Disruption and Risk for Ventilator-Associated Lower Respiratory Tract Infection
James J Harrigan1, Hatem O Abdallah1, Erik L Clarke2
1Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
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.
Insights
Persistent disruption of the respiratory microbiome, indicated by low Shannon diversity over consecutive days, predicts ventilator-associated lower respiratory tract infection (VA-LRTI) risk in prolonged mechanical ventilation. This finding may help target infection prevention strategies.
Area of Science:
- Critical Care Medicine
- Infectious Diseases
- Microbiome Research
Background:
- Ventilator-associated lower respiratory tract infection (VA-LRTI) is a significant complication in critically ill patients, increasing morbidity and mortality.
- Microbiome disruption indices (MDIs) predict VA-LRTI risk in acute illness, but their role in prolonged mechanical ventilation is unclear.
Purpose of the Study:
- To investigate changes in respiratory microbiome disruption indices (MDIs) during prolonged mechanical ventilation.
- To determine if these MDIs remain associated with VA-LRTI risk over time.
Main Methods:
- A cohort of 83 subjects on prolonged mechanical ventilation was studied.
- Longitudinal lower respiratory tract samples were collected and analyzed using 16S rRNA sequencing and qPCR.
- Microbiome disruption indices (MDIs) were calculated, including Shannon diversity and bacterial abundance.
Main Results:
- Cross-sectional MDIs showed weak associations with VA-LRTI risk.
- Persistent lower respiratory microbiome disruption, defined by consecutive days with low Shannon diversity (<2.0), robustly predicted VA-LRTI risk (OR 1.36 per day).
- The association was consistent across different VA-LRTI definitions.
Conclusions:
- Cross-sectional MDIs have limited utility for predicting VA-LRTI risk in prolonged mechanical ventilation.
- Persistent lower respiratory tract microbiome disruption, particularly low Shannon diversity over consecutive days, identifies patients at high risk for VA-LRTI.
- This understanding can inform targeted infection prevention interventions.
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