Publication:
Lung microbiota predict clinical outcomes in critically ill patients

dc.contributor.authorRobert P. Dicksonen_US
dc.contributor.authorMarcus J. Schultzen_US
dc.contributor.authorTom Van Der Pollen_US
dc.contributor.authorLaura R. Schoutenen_US
dc.contributor.authorNicole R. Falkowskien_US
dc.contributor.authorJenna E. Luthen_US
dc.contributor.authorMichael W. Sjodingen_US
dc.contributor.authorChristopher A. Brownen_US
dc.contributor.authorRishi Chanderrajen_US
dc.contributor.authorGary B. Huffnagleen_US
dc.contributor.authorLieuwe D.J. Bosen_US
dc.contributor.otherUniversity of Michigan Medical Schoolen_US
dc.contributor.otherMahidol Universityen_US
dc.contributor.otherUniversiteit van Amsterdamen_US
dc.contributor.otherAmsterdam UMC - University of Amsterdamen_US
dc.contributor.otherMichigan Center for Integrative Research in Critical Careen_US
dc.date.accessioned2020-03-26T04:53:48Z
dc.date.available2020-03-26T04:53:48Z
dc.date.issued2020-03-01en_US
dc.description.abstract© 2020 by the American Thoracic Society. Rationale: Recent studies have revealed that, in critically ill patients, lung microbiota are altered and correlate with alveolar inflammation. The clinical significance of altered lung bacteria in critical illness is unknown. Objectives: To determine if clinical outcomes of critically ill patients are predicted by features of the lung microbiome at the time of admission. Methods: We performed a prospective, observational cohort study in an ICU at a university hospital. Lung microbiota were quantified and characterized using droplet digital PCR and bacterial 16S ribosomal RNA gene quantification and sequencing. Primary predictors were the bacterial burden, community diversity, and community composition of lung microbiota. The primary outcome was ventilatorfree days, determined at 28 days after admission. Measurements and Main Results: Lungs of 91 critically ill patients were sampled using miniature BAL within 24 hours of ICU admission. Patients with increased lung bacterial burden had fewer ventilator-free days (hazard ratio, 0.43; 95% confidence interval, 0.21-0.88), which remained significant when the analysis was controlled for pneumonia and severity of illness. The community composition of lung bacteria predicted ventilator-free days (P = 0.003), driven by the presence of gutassociated bacteria (e.g., species of the Lachnospiraceae and Enterobacteriaceae families). Detection of gut-associated bacteria was also associated with the presence of acute respiratory distress syndrome. Conclusions: Key features of the lung microbiome (bacterial burden and enrichment with gut-associated bacteria) predict outcomes in critically ill patients. The lung microbiome is an understudied source of clinical variation in critical illness and represents a novel therapeutic target for the prevention and treatment of acute respiratory failure.en_US
dc.identifier.citationAmerican Journal of Respiratory and Critical Care Medicine. Vol.201, No.5 (2020), 555-563en_US
dc.identifier.doi10.1164/rccm.201907-1487OCen_US
dc.identifier.issn15354970en_US
dc.identifier.issn1073449Xen_US
dc.identifier.other2-s2.0-85080041449en_US
dc.identifier.urihttps://repository.li.mahidol.ac.th/handle/20.500.14594/53736
dc.rightsMahidol Universityen_US
dc.rights.holderSCOPUSen_US
dc.source.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85080041449&origin=inwarden_US
dc.subjectMedicineen_US
dc.titleLung microbiota predict clinical outcomes in critically ill patientsen_US
dc.typeArticleen_US
dspace.entity.typePublication
mu.datasource.scopushttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85080041449&origin=inwarden_US

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