Large scale cytokine profiling uncovers elevated IL12-p70 and IL-17A in severe pediatric acute respiratory distress syndrome

Respiratory Support After Extubation in Children With Pediatric ARDS

BACKGROUND

Postextubation respiratory support in pediatric ARDS may be used to support the recovering respiratory system and promote timely, successful liberation from mechanical ventilation. This study's aims were to (1) describe the use of postextubation respiratory support in pediatric ARDS from the time of extubation to hospital discharge, (2) identify potential risk factors for postextubation respiratory support, and (3) provide preliminary data for future larger studies.

METHODS

This pilot single-center prospective cohort study recruited subjects with pediatric ARDS. Subjects' respiratory status up to hospital discharge, the use of postextubation respiratory support, and how it changed over time were recorded. Analysis was performed comparing subjects who received postextubation respiratory support versus those who did not and compared its use among pediatric ARDS severity categories. Multivariable logistic regression was used to determine variables associated with the use of postextubation respiratory support and included oxygenation index (OI), ventilator duration, and weight.

RESULTS

Seventy-three subjects with pediatric ARDS, with median age and OI of 4 (0.6-10.5) y and 7.3 (4.9-12.7), respectively, were analyzed. Postextubation respiratory support was provided to 54/73 (74%) subjects: 28/45 (62.2%), 19/21 (90.5%), and 7/7 (100%) for mild, moderate, and severe pediatric ARDS, respectively, (P = .01). OI and mechanical ventilation duration were higher in subjects who received postextubation respiratory support (8.7 [5.4-14] vs 4.6 [3.7-7], P < .001 and 10 [7-17] d vs 4 [2-7] d, P < .001) compared to those who did not. At hospital discharge, 12/67 (18.2%) survivors received home respiratory support (6 subjects died prior to hospital discharge). In the multivariable model, ventilator duration (adjusted odds ratio 1.3 [95% CI 1.0-1.7], P = .050) and weight (adjusted odds ratio 0.95 [95% CI 0.91-0.99], P = .02) were associated with the use of postextubation respiratory support.

CONCLUSIONS

The majority of intubated subjects with pediatric ARDS received respiratory support postextubation, and a substantial proportion continued to require it up to hospital discharge.

Pathobiology, Severity, and Risk Stratification of Pediatric Acute Respiratory Distress Syndrome: From the Second Pediatric Acute Lung Injury Consensus Conference

OBJECTIVES

To review the literature for studies published in children on the pathobiology, severity, and risk stratification of pediatric acute respiratory distress syndrome (PARDS) with the intent of guiding current medical practice and identifying important areas for future research related to severity and risk stratification.

DATA SOURCES

Electronic searches of PubMed and Embase were conducted from 2013 to March 2022 by using a combination of medical subject heading terms and text words to capture the pathobiology, severity, and comorbidities of PARDS.

STUDY SELECTION

We included studies of critically ill patients with PARDS that related to the severity and risk stratification of PARDS using characteristics other than the oxygenation defect. Studies using animal models, adult only, and studies with 10 or fewer children were excluded from our review.

DATA EXTRACTION

Title/abstract review, full-text review, and data extraction using a standardized data collection form.

DATA SYNTHESIS

The Grading of Recommendations Assessment, Development, and Evaluation approach was used to identify and summarize relevant evidence and develop recommendations for clinical practice. There were 192 studies identified for full-text extraction to address the relevant Patient/Intervention/Comparator/Outcome questions. One clinical recommendation was generated related to the use of dead space fraction for risk stratification. In addition, six research statements were generated about the impact of age on acute respiratory distress syndrome pathobiology and outcomes, addressing PARDS heterogeneity using biomarkers to identify subphenotypes and endotypes, and use of standardized ventilator, physiologic, and nonpulmonary organ failure measurements for future research.

CONCLUSIONS

Based on an extensive literature review, we propose clinical management and research recommendations related to characterization and risk stratification of PARDS severity.

Validating a Proteomic Signature of Severe COVID-19

COVID-19 is a heterogenous disease. Biomarker-based approaches may identify patients at risk for severe disease, who may be more likely to benefit from specific therapies. Our objective was to identify and validate a plasma protein signature for severe COVID-19.

DESIGN

Prospective observational cohort study.

SETTING

Two hospitals in the United States.

PATIENTS

One hundred sixty-seven hospitalized adults with COVID-19.

INTERVENTION

None.

MEASUREMENTS AND MAIN RESULTS

We measured 713 plasma proteins in 167 hospitalized patients with COVID-19 using a high-throughput platform. We classified patients as nonsevere versus severe COVID-19, defined as the need for high-flow nasal cannula, mechanical ventilation, extracorporeal membrane oxygenation, or death, at study entry and in 7-day intervals thereafter. We compared proteins measured at baseline between these two groups by logistic regression adjusting for age, sex, symptom duration, and comorbidities. We used lead proteins from dysregulated pathways as inputs for elastic net logistic regression to identify a parsimonious signature of severe disease and validated this signature in an external COVID-19 dataset. We tested whether the association between corticosteroid use and mortality varied by protein signature. One hundred ninety-four proteins were associated with severe COVID-19 at the time of hospital admission. Pathway analysis identified multiple pathways associated with inflammatory response and tissue repair programs. Elastic net logistic regression yielded a 14-protein signature that discriminated 90-day mortality in an external cohort with an area under the receiver-operator characteristic curve of 0.92 (95% CI, 0.88-0.95). Classifying patients based on the predicted risk from the signature identified a heterogeneous response to treatment with corticosteroids (p = 0.006).

CONCLUSIONS

Inpatients with COVID-19 express heterogeneous patterns of plasma proteins. We propose a 14-protein signature of disease severity that may have value in developing precision medicine approaches for COVID-19 pneumonia.

Autoinducer-2 promotes Pseudomonas aeruginosa PAO1 acute lung infection via the IL-17A pathway

Pseudomonas aeruginosa is an opportunistic pathogenic bacterium that causes various acute and chronic lung infections in immunocompromised patients. We previously found that a quorum sensing (QS) signal, namely, autoinducer-2 (AI-2), facilitates the pathogenicity of the wild-type (WT) P. aeruginosa PAO1 strain in vitro and in vivo. However, the immunological mechanism that leads to pulmonary injury remains to be elucidated. In this study, we aimed to investigate the effects of AI-2 on interleukin-17A (IL-17A) production during acute P. aeruginosa PAO1 lung infection using a mouse model, with an emphasis on the underlying immunological mechanism. Compared to infection with P. aeruginosa PAO1 alone, infection with P. aeruginosa PAO1 combined with AI-2 treatment resulted in significantly increased levels of IL-17A, numbers of Th17 cells and levels of STAT3 in the lung tissues of WT mice (P < 0.05), as well as more serious lung damage. In contrast, the concentrations of the proinflammatory cytokines IL-1α, IL-1β, and IL-6 and the chemokine keratinocyte-derived chemokine (KC) were significantly reduced during P. aeruginosa lung infection in IL-17A^−/− mice compared with WT mice (P < 0.05), and no effects were observed after AI-2 treatment (P > 0.05). Furthermore, the level of IL-17A in the lungs of WT mice was significantly reduced following infection with a P. aeruginosa strain harboring mutations in the QS genes lasR and rhlR compared with the level of IL-17A following infection with P. aeruginosa PAO1. Our data suggest that AI-2 promotes P. aeruginosa PAO1 acute lung infection via the IL-17A pathway by interfering with the QS systems of P. aeruginosa. IL-17A may be a therapeutic target for the treatment of acute P. aeruginosa lung infections in the clinic.