Very Low Driving-Pressure Ventilation in Patients With COVID-19 Acute Respiratory Distress Syndrome on Extracorporeal Membrane Oxygenation: A Physiologic Study.

OBJECTIVES: To determine in patients with acute respiratory distress syndrome (ARDS) on venovenous extracorporeal membrane oxygenation (VV ECMO) whether reducing driving pressure (ΔP) would decrease plasma biomarkers of inflammation and lung injury (interleukin-6 [IL-6], IL-8, and the soluble receptor for advanced glycation end-products sRAGE). DESIGN: A single-center prospective physiologic study. SETTING: At a single university medical center. PARTICIPANTS: Adult patients with severe COVID-19 ARDS on VV ECMO. INTERVENTIONS: Participants on VV ECMO had the following biomarkers measured: (1) pre-ECMO with low-tidal-volume ventilation (LTVV), (2) post-ECMO with LTVV, (3) during low-driving-pressure ventilation (LDPV), (4) after 2 hours of very low driving-pressure ventilation (V-LDPV, main intervention ΔP = 1 cmH2O), and (5) 2 hours after returning to LDPV. MAIN MEASUREMENTS AND RESULTS: Twenty-six participants were enrolled; 21 underwent V-LDPV. There was no significant change in IL-6, IL-8, and sRAGE from LDPV to V-LDPV and from V-LDPV to LDPV. Only participants (9 of 21) with nonspontaneous breaths had significant change (p < 0.001) in their tidal volumes (Vt) (mean ± SD), 1.9 ± 0.5, 0.1 ± 0.2, and 2.0 ± 0.7 mL/kg predicted body weight (PBW). Participants with spontaneous breathing, Vt were unchanged-4.5 ± 3.1, 4.7 ± 3.1, and 5.6 ± 2.9 mL/kg PBW (p = 0.481 and p = 0.065, respectively). There was no relationship found when accounting for Vt changes and biomarkers. CONCLUSIONS: Biomarkers did not significantly change with decreased ΔPs or Vt changes during the first 24 hours post-ECMO. Despite deep sedation, reductions in Vt during V-LDPV were not reliably achieved due to spontaneous breaths. Thus, patients on VV ECMO for ARDS may have higher Vt (ie, transpulmonary pressure) than desired despite low ΔPs or Vt.

AI-guided discovery of the invariant host response to viral pandemics.

BACKGROUND: Coronavirus Disease 2019 (Covid-19) continues to challenge the limits of our knowledge and our healthcare system. Here we sought to define the host immune response, a.k.a, the "cytokine storm" that has been implicated in fatal COVID-19 using an AI-based approach. METHOD: Over 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a 'seed' gene; ACE2 was rationalized because it encodes the receptor that facilitates the entry of SARS-CoV-2 (the virus that causes COVID-19) into host cells. An AI-based approach was used to explore the utility of the signature in navigating the uncharted territory of Covid-19, setting therapeutic goals, and finding therapeutic solutions. FINDINGS: The 166-gene signature was surprisingly conserved across all viral pandemics, including COVID-19, and a subset of 20-genes classified disease severity, inspiring the nomenclatures ViP and severe-ViP signatures, respectively. The ViP signatures pinpointed a paradoxical phenomenon wherein lung epithelial and myeloid cells mount an IL15 cytokine storm, and epithelial and NK cell senescence and apoptosis determine severity/fatality. Precise therapeutic goals could be formulated; these goals were met in high-dose SARS-CoV-2-challenged hamsters using either neutralizing antibodies that abrogate SARS-CoV-2•ACE2 engagement or a directly acting antiviral agent, EIDD-2801. IL15/IL15RA were elevated in the lungs of patients with fatal disease, and plasma levels of the cytokine prognosticated disease severity. INTERPRETATION: The ViP signatures provide a quantitative and qualitative framework for titrating the immune response in viral pandemics and may serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs. FUNDING: This work was supported by the National Institutes for Health (NIH) [grants CA151673 and GM138385 (to DS) and AI141630 (to P.G), DK107585-05S1 (SD) and AI155696 (to P.G, D.S and S.D), U19-AI142742 (to S. C, CCHI: Cooperative Centers for Human Immunology)]; Research Grants Program Office (RGPO) from the University of California Office of the President (UCOP) (R00RG2628 & R00RG2642 to P.G, D.S and S.D); the UC San Diego Sanford Stem Cell Clinical Center (to P.G, D.S and S.D); LJI Institutional Funds (to S.C); the VA San Diego Healthcare System Institutional funds (to L.C.A). GDK was supported through The American Association of Immunologists Intersect Fellowship Program for Computational Scientists and Immunologists. ONE SENTENCE SUMMARY: The host immune response in COVID-19.

AI-guided discovery of the invariant host response to viral pandemics.

We sought to define the host immune response, a.k.a, the "cytokine storm" that has been implicated in fatal COVID-19 using an AI-based approach. Over 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a 'seed' gene; ACE2 was rationalized because it encodes the receptor that facilitates the entry of SARS-CoV-2 (the virus that causes COVID-19) into host cells. Surprisingly, this 166-gene signature was conserved in all vi ral p andemics, including COVID-19, and a subset of 20-genes classified disease severity, inspiring the nomenclatures ViP and severe-ViP signatures, respectively. The ViP signatures pinpointed a paradoxical phenomenon wherein lung epithelial and myeloid cells mount an IL15 cytokine storm, and epithelial and NK cell senescence and apoptosis determines severity/fatality. Precise therapeutic goals were formulated and subsequently validated in high-dose SARS-CoV-2-challenged hamsters using neutralizing antibodies that abrogate SARS-CoV-2•ACE2 engagement or a directly acting antiviral agent, EIDD-2801. IL15/IL15RA were elevated in the lungs of patients with fatal disease, and plasma levels of the cytokine tracked with disease severity. Thus, the ViP signatures provide a quantitative and qualitative framework for titrating the immune response in viral pandemics and may serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs. ONE SENTENCE SUMMARY: The host immune response in COVID-19. PANEL RESEARCH IN CONTEXT: Evidence before this study: The SARS-CoV-2 pandemic has inspired many groups to find innovative methodologies that can help us understand the host immune response to the virus; unchecked proportions of such immune response have been implicated in fatality. We searched GEO and ArrayExpress that provided many publicly available gene expression data that objectively measure the host immune response in diverse conditions. However, challenges remain in identifying a set of host response events that are common to every condition. There are no studies that provide a reproducible assessment of prognosticators of disease severity, the host response, and therapeutic goals. Consequently, therapeutic trials for COVID-19 have seen many more 'misses' than 'hits'. This work used multiple (> 45,000) gene expression datasets from GEO and ArrayExpress and analyzed them using an unbiased computational approach that relies upon fundamentals of gene expression patterns and mathematical precision when assessing them.Added value of this study: This work identifies a signature that is surprisingly conserved in all viral pandemics, including Covid-19, inspiring the nomenclature ViP-signature. A subset of 20-genes classified disease severity in respiratory pandemics. The ViP signatures pinpointed the nature and source of the 'cytokine storm' mounted by the host. They also helped formulate precise therapeutic goals and rationalized the repurposing of FDA-approved drugs.Implications of all the available evidence: The ViP signatures provide a quantitative and qualitative framework for assessing the immune response in viral pandemics when creating pre-clinical models; they serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs.