Division of Infectious Diseases, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Clin Infect Dis. 2022 May 3;74(9):1564-1571. doi: 10.1093/cid/ciab678.
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.
背景:呼吸机相关性下呼吸道感染(VA-LRTI)在重症患者中很常见,与发病率和死亡率增加有关。在急性危重病中,已显示呼吸微生物组破坏指数(MDI)可预测 VA-LRTI 的风险,但它们在危重病初期之后的效用尚不清楚。我们试图描述先前在机械通气开始时预测 VA-LRTI 的 MDI 如何随机械通气时间的延长而变化,以及它们是否仍然与 VA-LRTI 的风险相关。
方法:我们建立了一个由 83 名因长期依赖机械通气而入住长期急性护理医院的患者组成的队列;对下呼吸道进行了密集的、纵向采样,共采集了 1066 个标本;并通过 16S rRNA 测序和 16S rRNA 定量聚合酶链反应来描述下呼吸道微生物组以及总细菌丰度。
结果:横断面 MDI,包括低 Shannon 多样性和高总细菌丰度,与 VA-LRTI 的风险相关,但关联的后验可信区间较宽。下呼吸道微生物组持续破坏与 VA-LRTI 风险的关联更为显著,每天(底数为 e)Shannon 多样性<2.0 与 VA-LRTI 的比值比为 1.36(95%可信区间,1.10-1.72)。观察到的关联在多种 VA-LRTI 的临床定义中是一致的。
结论:横断面 MDI 对机械通气延长期间 VA-LRTI 风险的区分能力有限,但下呼吸道微生物组的持续破坏,最好用连续多天 Shannon 多样性低来描述,可能会识别出一个感染风险高的人群,并可能有助于针对感染预防干预措施。
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