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During the coronavirus 2019 (COVID-19) pandemic, children suffered severe lung injury resulting in acute respiratory distress syndrome requiring support with extracorporeal membrane oxygenation (ECMO). In this case series, we described our center's experience employing a rehabilitation-focused ECMO strategy including extubation during ECMO support in four pediatric patients with acute COVID-19 pneumonia hospitalized from September 2021 to January 2022. All four patients tolerated extubation within 30 days of ECMO initiation and achieved mobility while on ECMO support. Duration of ECMO support was 35-152 days and hospital lengths of stay were 52-167 days. Three of four patients survived. Two of three survivors had normal functional status at discharge except for ongoing respiratory support. The third survivor had significant motor deficits due to critical illness polyneuropathy and was supported with daytime oxygen and nocturnal noninvasive support. Overall, these patients demonstrated good outcomes and tolerance of a rehabilitation-focused ECMO strategy., Competing Interests: Disclosure: The authors have no conflicts of interest to report., (Copyright © ASAIO 2024.)

BACKGROUNDLower respiratory tract infection (LRTI) is a leading cause of death in children worldwide. LRTI diagnosis is challenging because noninfectious respiratory illnesses appear clinically similar and because existing microbiologic tests are often falsely negative or detect incidentally carried microbes, resulting in antimicrobial overuse and adverse outcomes. Lower airway metagenomics has the potential to detect host and microbial signatures of LRTI. Whether it can be applied at scale and in a pediatric population to enable improved diagnosis and treatment remains unclear.METHODSWe used tracheal aspirate RNA-Seq to profile host gene expression and respiratory microbiota in 261 children with acute respiratory failure. We developed a gene expression classifier for LRTI by training on patients with an established diagnosis of LRTI (n = 117) or of noninfectious respiratory failure (n = 50). We then developed a classifier that integrates the host LRTI probability, abundance of respiratory viruses, and dominance in the lung microbiome of bacteria/fungi considered pathogenic by a rules-based algorithm.RESULTSThe host classifier achieved a median AUC of 0.967 by cross-validation, driven by activation markers of T cells, alveolar macrophages, and the interferon response. The integrated classifier achieved a median AUC of 0.986 and increased the confidence of patient classifications. When applied to patients with an uncertain diagnosis (n = 94), the integrated classifier indicated LRTI in 52% of cases and nominated likely causal pathogens in 98% of those.CONCLUSIONLower airway metagenomics enables accurate LRTI diagnosis and pathogen identification in a heterogeneous cohort of critically ill children through integration of host, pathogen, and microbiome features.FUNDINGSupport for this study was provided by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Heart, Lung, and Blood Institute (UG1HD083171, 1R01HL124103, UG1HD049983, UG01HD049934, UG1HD083170, UG1HD050096, UG1HD63108, UG1HD083116, UG1HD083166, UG1HD049981, K23HL138461, and 5R01HL155418) as well as by the Chan Zuckerberg Biohub.