2 results
Impact of Diagnosed and Undiagnosed Respiratory Pseudomonas on VAP and VAE During Long-Term Acute Care
- James Harrigan, Ebbing Lautenbach, Emily Reesey, Magda Wernovsky, Pam Tolomeo, Zygmunt Morawski, Jerry Jacob, Michael Grippi, Brendan Kelly
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s258-s259
- Print publication:
- October 2020
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- Article
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Background: Clinically diagnosed ventilator-associated pneumonia (VAP) is common in the long-term acute-care hospital (LTACH) setting and may contribute to adverse ventilator-associated events (VAEs). Pseudomonas aeruginosa is a common causative organism of VAP. We evaluated the impact of respiratory P. aeruginosa colonization and bacterial community dominance, both diagnosed and undiagnosed, on subsequent P. aeruginosa VAP and VAE events during long-term acute care. Methods: We enrolled 83 patients on LTACH admission for ventilator weaning, performed longitudinal sampling of endotracheal aspirates followed by 16S rRNA gene sequencing (Illumina HiSeq), and bacterial community profiling (QIIME2). Statistical analysis was performed with R and Stan; mixed-effects models were fit to relate the abundance of respiratory Psa on admission to clinically diagnosed VAP and VAE events. Results: Of the 83 patients included, 12 were diagnosed with P. aeruginosa pneumonia during the 14 days prior to LTACH admission (known P. aeruginosa), and 22 additional patients received anti–P. aeruginosa antibiotics within 48 hours of admission (suspected P. aeruginosa); 49 patients had no known or suspected P. aeruginosa (unknown P. aeruginosa). Among the known P. aeruginosa group, all 12 patients had P. aeruginosa detectable by 16S sequencing, with elevated admission P. aeruginosa proportional abundance (median, 0.97; IQR, 0.33–1). Among the suspected P. aeruginosa group, all 22 patients had P. aeruginosa detectable by 16S sequencing, with a wide range of admission P. aeruginosa proportional abundance (median, 0.0088; IQR, 0.00012–0.31). Of the 49 patients in the unknown group, 47 also had detectable respiratory Psa, and many had high P. aeruginosa proportional abundance at admission (median, 0.014; IQR, 0.00025–0.52). Incident P. aeruginosa VAP was observed within 30 days in 4 of the known P. aeruginosa patients (33.3%), 5 of the suspected P. aeruginosa patients (22.7%), and 8 of the unknown P. aeruginosa patients (16.3%). VAE was observed within 30 days in 1 of the known P. aeruginosa patients (8.3%), 2 of the suspected P. aeruginosa patients (9.1%), and 1 of the unknown P. aeruginosa patients (2%). Admission P. aeruginosa abundance was positively associated with VAP and VAE risk in all groups, but the association only achieved statistical significance in the unknown group (type S error <0.002 for 30-day VAP and <0.011 for 30-day VAE). Conclusions: We identified a high prevalence of unrecognized respiratory P. aeruginosa colonization among patients admitted to LTACH for weaning from mechanical ventilation. The admission P. aeruginosa proportional abundance was strongly associated with increased risk of incident P. aeruginosa VAP among these patients.
Funding: None
Disclosures: None
Comparison of Respiratory Microbiome Disruption Indices to Predict VAP and VAE risk at LTACH Admission
- Erik Clarke, Kathleen None Chiotos, James Harrigan, Ebbing Lautenbach, Emily Reesey, Magda Wernovsky, Pam Tolomeo, Zygmunt Morawski, Jerry Jacob, Michael Grippi, Brendan Kelly
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- Journal:
- Infection Control & Hospital Epidemiology / Volume 41 / Issue S1 / October 2020
- Published online by Cambridge University Press:
- 02 November 2020, pp. s179-s180
- Print publication:
- October 2020
-
- Article
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- You have access Access
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Background: Healthcare exposure results in significant microbiome disruption, particularly in the setting of critical illness, which may contribute to risk for healthcare-associated infections (HAIs). Patients admitted to long-term acute-care hospitals (LTACHs) have extensive prior healthcare exposure and critical illness; significant microbiome disruption has been previously documented among LTACH patients. We compared the predictive value of 3 respiratory tract microbiome disruption indices—bacterial community diversity, dominance, and absolute abundance—as they relate to risk for ventilator-associated pneumonia (VAP) and adverse ventilator-associated events (VAE), which commonly complicate LTACH care. Methods: We enrolled 83 subjects on admission to an academic LTACH for ventilator weaning and performed longitudinal sampling of endotracheal aspirates, followed by 16S rRNA gene sequencing (Illumina HiSeq), bacterial community profiling (QIIME2) for diversity, and 16S rRNA quantitative PCR (qPCR) for total bacterial abundance. Statistical analyses were performed with R and Stan software. Mixed-effects models were fit to relate the admission MDIs to subsequent clinically diagnosed VAP and VAE. Results: Of the 83 patients, 19 had been diagnosed with pneumonia during the 14 days prior to LTACH admission (ie, “recent past VAP”); 23 additional patients were receiving antibiotics consistent with empiric VAP therapy within 48 hours of admission (ie, “empiric VAP therapy”); and 41 patients had no evidence of VAP at admission (ie, “no suspected VAP”). We detected no statistically significant differences in admission Shannon diversity, maximum amplicon sequence variant (ASV)–level proportional abundance, or 16S qPCR across the variables of interest. In isolation, all 3 admission microbiome disruption indices showed poor predictive performance, though Shannon diversity performed better than maximum ASV abundance. Predictive models that combined (1) bacterial diversity or abundance with (2) recent prior VAP diagnosis and (3) concurrent antibiotic exposure best predicted 14-day VAP (type S error < 0.05) and 30-day VAP (type S error < 0.003). In this cohort, VAE risk was paradoxically associated with higher admission Shannon diversity and lower admission maximum ASV abundance. Conclusions: In isolation, respiratory tract microbiome disruption indices obtained at LTACH admission showed poor predictive performance for subsequent VAP and VAE. But diversity and abundance models incorporating recent VAP history and admission antibiotic exposure performed well predicting 14-day and 30-day VAP.
Disclosures: None
Funding: None