Glucocorticoid use in acute respiratory failure from pulmonary causes and association with early changes in the systemic host immune response.

BACKGROUND: Glucocorticoids are commonly used in patients with or at-risk for acute respiratory distress syndrome (ARDS), but optimal use remains unclear despite well-conducted clinical trials. We performed a secondary analysis in patients previously enrolled in the Acute Lung Injury and Biospecimen Repository at the University of Pittsburgh. The primary aim of our study was to investigate early changes in host response biomarkers in response to real-world use of glucocorticoids in patients with acute respiratory failure due to ARDS or at-risk due to a pulmonary insult. Participants had baseline plasma samples obtained on study enrollment and on follow-up 3 to 5 days later to measure markers of innate immunity (IL-6, IL-8, IL-10, TNFr1, ST2, fractalkine), epithelial injury (sRAGE), endothelial injury (angiopoietin-2), and host response to bacterial infections (procalcitonin, pentraxin-3). In our primary analyses, we investigated the effect of receiving glucocorticoids between baseline and follow-up samples on host response biomarkers measured at follow-up by doubly robust inverse probability weighting analysis. In exploratory analyses, we examined associations between glucocorticoid use and previously characterized host response subphenotypes (hyperinflammatory and hypoinflammatory). RESULTS: 67 of 148 participants (45%) received glucocorticoids between baseline and follow-up samples. Dose and type of glucocorticoids varied. Regimens that used hydrocortisone alone were most common (37%), and median daily dose was equivalent to 40 mg methylprednisolone (interquartile range: 21, 67). Participants who received glucocorticoids were more likely to be female, to be on immunosuppressive therapy at baseline, and to have higher baseline levels of ST-2, fractalkine, IL-10, pentraxin-3, sRAGE, and TNFr1. Glucocorticoid use was associated with decreases in IL-6 and increases in fractalkine. In exploratory analyses, glucocorticoid use was more frequent in participants in the hyperinflammatory subphenotype (58% vs 40%, p = 0.05), and was not associated with subphenotype classification at the follow-up time point (p = 0.16). CONCLUSIONS: Glucocorticoid use varied in a cohort of patients with or at-risk for ARDS and was associated with early changes in the systemic host immune response.

Subphenotypes of self-reported symptoms and outcomes in long COVID: a prospective cohort study with latent class analysis.

OBJECTIVE: To characterise subphenotypes of self-reported symptoms and outcomes (SRSOs) in postacute sequelae of COVID-19 (PASC). DESIGN: Prospective, observational cohort study of subjects with PASC. SETTING: Academic tertiary centre from five clinical referral sources. PARTICIPANTS: Adults with COVID-19 ≥20 days before enrolment and presence of any new self-reported symptoms following COVID-19. EXPOSURES: We collected data on clinical variables and SRSOs via structured telephone interviews and performed standardised assessments with validated clinical numerical scales to capture psychological symptoms, neurocognitive functioning and cardiopulmonary function. We collected saliva and stool samples for quantification of SARS-CoV-2 RNA via quantitative PCR. OUTCOMES MEASURES: Description of PASC SRSOs burden and duration, derivation of distinct PASC subphenotypes via latent class analysis (LCA) and relationship with viral load. RESULTS: We analysed baseline data for 214 individuals with a study visit at a median of 197.5 days after COVID-19 diagnosis. Participants reported ever having a median of 9/16 symptoms (IQR 6-11) after acute COVID-19, with muscle-aches, dyspnoea and headache being the most common. Fatigue, cognitive impairment and dyspnoea were experienced for a longer time. Participants had a lower burden of active symptoms (median 3 (1-6)) than those ever experienced (p<0.001). Unsupervised LCA of symptoms revealed three clinically active PASC subphenotypes: a high burden constitutional symptoms (21.9%), a persistent loss/change of smell and taste (20.6%) and a minimal residual symptoms subphenotype (57.5%). Subphenotype assignments were strongly associated with self-assessments of global health, recovery and PASC impact on employment (p<0.001) as well as referral source for enrolment. Viral persistence (5.6% saliva and 1% stool samples positive) did not explain SRSOs or subphenotypes. CONCLUSIONS: We identified three distinct PASC subphenotypes. We highlight that although most symptoms progressively resolve, specific PASC subpopulations are impacted by either high burden of constitutional symptoms or persistent olfactory/gustatory dysfunction, requiring prospective identification and targeted preventive or therapeutic interventions.

Lung Epithelium Releases Growth Differentiation Factor 15 in Response to Pathogen-mediated Injury.

GDF15 (growth differentiation factor 15) is a stress cytokine with several proposed roles, including support of stress erythropoiesis. Higher circulating GDF15 levels are prognostic of mortality during acute respiratory distress syndrome, but the cellular sources and downstream effects of GDF15 during pathogen-mediated lung injury are unclear. We quantified GDF15 in lower respiratory tract biospecimens and plasma from patients with acute respiratory failure. Publicly available data from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection were reanalyzed. We used mouse models of hemorrhagic acute lung injury mediated by Pseudomonas aeruginosa exoproducts in wild-type mice and mice genetically deficient for Gdf15 or its putative receptor, Gfral. In critically ill humans, plasma levels of GDF15 correlated with lower respiratory tract levels and were higher in nonsurvivors. SARS-CoV-2 infection induced GDF15 expression in human lung epithelium, and lower respiratory tract GDF15 levels were higher in coronavirus disease (COVID-19) nonsurvivors. In mice, intratracheal P. aeruginosa type II secretion system exoproducts were sufficient to induce airspace and plasma release of GDF15, which was attenuated with epithelial-specific deletion of Gdf15. Mice with global Gdf15 deficiency had decreased airspace hemorrhage, an attenuated cytokine profile, and an altered lung transcriptional profile during injury induced by P. aeruginosa type II secretion system exoproducts, which was not recapitulated in mice deficient for Gfral. Airspace GDF15 reconstitution did not significantly modulate key lung cytokine levels but increased circulating erythrocyte counts. Lung epithelium releases GDF15 during pathogen injury, which is associated with plasma levels in humans and mice and can increase erythrocyte counts in mice, suggesting a novel lung-blood communication pathway.

Robust airway microbiome signatures in acute respiratory failure and hospital-acquired pneumonia.

Respiratory microbial dysbiosis is associated with acute respiratory distress syndrome (ARDS) and hospital-acquired pneumonia (HAP) in critically ill patients. However, we lack reproducible respiratory microbiome signatures that can increase our understanding of these conditions and potential treatments. Here, we analyze 16S rRNA sequencing data from 2,177 respiratory samples collected from 1,029 critically ill patients (21.7% with ARDS and 26.3% with HAP) and 327 healthy controls, sourced from 17 published studies. After data harmonization and pooling of individual patient data, we identified microbiota signatures associated with ARDS, HAP and prolonged mechanical ventilation. Microbiota signatures for HAP and prolonged mechanical ventilation were characterized by depletion of a core group of microbes typical of healthy respiratory samples, and the ARDS microbiota signature was distinguished by enrichment of potentially pathogenic respiratory microbes, including Pseudomonas and Staphylococcus. Using machine learning models, we identified clinically informative, three- and four-factor signatures that predicted ARDS, HAP and prolonged mechanical ventilation with relatively high accuracy (area under the curve of 0.751, 0.72 and 0.727, respectively). We validated the signatures in an independent prospective cohort of 136 patients on mechanical ventillation and found that patients with microbiome signatures associated with ARDS, HAP or prolonged mechanical ventilation had longer times to successful extubation than patients lacking these signatures (hazard ratios of 1.56 (95% confidence interval (CI) 1.07-2.27), 1.51 (95% CI 1.02-2.23) and 1.50 (95% CI 1.03-2.18), respectively). Thus, we defined and validated robust respiratory microbiome signatures associated with ARDS and HAP that may help to identify promising targets for microbiome therapeutic modulation in critically ill patients.

A common single nucleotide polymorphism is associated with inflammation and critical illness outcomes.

Acute inflammation is heterogeneous in critical illness and predictive of outcome. We hypothesized that genetic variability in novel, yet common, gene variants contributes to this heterogeneity and could stratify patient outcomes. We searched algorithmically for significant differences in systemic inflammatory mediators associated with any of 551,839 SNPs in one derivation (n = 380 patients with blunt trauma) and two validation (n = 75 trauma and n = 537 non-trauma patients) cohorts. This analysis identified rs10404939 in the LYPD4 gene. Trauma patients homozygous for the A allele (rs10404939AA; 27%) had different trajectories of systemic inflammation along with persistently elevated multiple organ dysfunction (MOD) indices vs. patients homozygous for the G allele (rs10404939GG; 26%). rs10404939AA homozygotes in the trauma validation cohort had elevated MOD indices, and non-trauma patients displayed more complex inflammatory networks and worse 90-day survival compared to rs10404939GG homozygotes. Thus, rs10404939 emerged as a common, broadly prognostic SNP in critical illness.

Noninvasive diagnosis of secondary infections in COVID-19 by sequencing of plasma microbial cell-free DNA.

Secondary infection (SI) diagnosis in severe COVID-19 remains challenging. We correlated metagenomic sequencing of plasma microbial cell-free DNA (mcfDNA-Seq) with clinical SI assessment, immune response, and outcomes. We classified 42 COVID-19 inpatients as microbiologically confirmed-SI (Micro-SI, n = 8), clinically diagnosed-SI (Clinical-SI, n = 13, i.e., empiric antimicrobials), or no-clinical-suspicion-for-SI (No-Suspected-SI, n = 21). McfDNA-Seq was successful in 73% of samples. McfDNA detection was higher in Micro-SI (94%) compared to Clinical-SI (57%, p = 0.03), and unexpectedly high in No-Suspected-SI (83%), similar to Micro-SI. We detected culture-concordant mcfDNA species in 81% of Micro-SI samples. McfDNA correlated with LRT 16S rRNA bacterial burden (r = 0.74, p = 0.02), and biomarkers (white blood cell count, IL-6, IL-8, SPD, all p < 0.05). McfDNA levels were predictive of worse 90-day survival (hazard ratio 1.30 [1.02-1.64] for each log10 mcfDNA, p = 0.03). High mcfDNA levels in COVID-19 patients without clinical SI suspicion may suggest SI under-diagnosis. McfDNA-Seq offers a non-invasive diagnostic tool for pathogen identification, with prognostic value on clinical outcomes.

Prognostic Insights from Longitudinal Multicompartment Study of Host-Microbiota Interactions in Critically Ill Patients.

Critical illness can disrupt the composition and function of the microbiome, yet comprehensive longitudinal studies are lacking. We conducted a longitudinal analysis of oral, lung, and gut microbiota in a large cohort of 479 mechanically ventilated patients with acute respiratory failure. Progressive dysbiosis emerged in all three body compartments, characterized by reduced alpha diversity, depletion of obligate anaerobe bacteria, and pathogen enrichment. Clinical variables, including chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, shaped dysbiosis. Notably, of the three body compartments, unsupervised clusters of lung microbiota diversity and composition independently predicted survival, transcending clinical predictors, organ dysfunction severity, and host-response sub-phenotypes. These independent associations of lung microbiota may serve as valuable biomarkers for prognostication and treatment decisions in critically ill patients. Insights into the dynamics of the microbiome during critical illness highlight the potential for microbiota-targeted interventions in precision medicine.

Prognostic Insights from Longitudinal Multicompartment Study of Host-Microbiota Interactions in Critically Ill Patients.

Critical illness can disrupt the composition and function of the microbiome, yet comprehensive longitudinal studies are lacking. We conducted a longitudinal analysis of oral, lung, and gut microbiota in a large cohort of 479 mechanically ventilated patients with acute respiratory failure. Progressive dysbiosis emerged in all three body compartments, characterized by reduced alpha diversity, depletion of obligate anaerobe bacteria, and pathogen enrichment. Clinical variables, including chronic obstructive pulmonary disease, immunosuppression, and antibiotic exposure, shaped dysbiosis. Notably, of the three body compartments, unsupervised clusters of lung microbiota diversity and composition independently predicted survival, transcending clinical predictors, organ dysfunction severity, and host-response sub-phenotypes. These independent associations of lung microbiota may serve as valuable biomarkers for prognostication and treatment decisions in critically ill patients. Insights into the dynamics of the microbiome during critical illness highlight the potential for microbiota-targeted interventions in precision medicine.

Respiratory Fungal Communities are Associated with Systemic Inflammation and Predict Survival in Patients with Acute Respiratory Failure.

Rationale: Disruption of respiratory bacterial communities predicts poor clinical outcomes in critical illness; however, the role of respiratory fungal communities (mycobiome) is poorly understood. Objectives: We investigated whether mycobiota variation in the respiratory tract is associated with host-response and clinical outcomes in critically ill patients. Methods: To characterize the upper and lower respiratory tract mycobiota, we performed rRNA gene sequencing (internal transcribed spacer) of oral swabs and endotracheal aspirates (ETA) from 316 mechanically-ventilated patients. We examined associations of mycobiome profiles (diversity and composition) with clinical variables, host-response biomarkers, and outcomes. Measurements and Main Results: ETA samples with >50% relative abundance for C. albicans (51%) were associated with elevated plasma IL-8 and pentraxin-3 (p=0.05), longer time-to-liberation from mechanical ventilation (p=0.04) and worse 30-day survival (adjusted hazards ratio (adjHR): 1.96 [1.04-3.81], p=0.05). Using unsupervised clustering, we derived two clusters in ETA samples, with Cluster 2 (39%) showing lower alpha diversity (p<0.001) and higher abundance of C. albicans (p<0.001). Cluster 2 was significantly associated with the prognostically adverse hyperinflammatory subphenotype (odds ratio 2.07 [1.03-4.18], p=0.04) and predicted worse survival (adjHR: 1.81 [1.03-3.19], p=0.03). C. albicans abundance in oral swabs was also associated with the hyperinflammatory subphenotype and mortality. Conclusions: Variation in respiratory mycobiota was significantly associated with systemic inflammation and clinical outcomes. C. albicans abundance emerged as a negative predictor in both the upper and lower respiratory tract. The lung mycobiome may play an important role in the biological and clinical heterogeneity among critically ill patients and represent a potential therapeutic target for lung injury in critical illness.

Distinct profiles of host responses between plasma and lower respiratory tract during acute respiratory failure.

Current plasma-based subphenotyping approaches in acute respiratory failure represent host responses at a systemic level but do not capture important differences in lower respiratory tract biology https://bit.ly/40kTdDG.

Factor H preserves alternative complement function during ARDS, linked to improved survival.

Background: Effective regulation of complement activation may be crucial to preserving complement function during acute respiratory distress syndrome (ARDS). Factor H is the primary negative regulator of the alternative pathway of complement. We hypothesised that preserved factor H levels are associated with decreased complement activation and reduced mortality during ARDS. Methods: Total alternative pathway function was measured by serum haemolytic assay (AH50) using available samples from the ARDSnet Lisofylline and Respiratory Management of Acute Lung Injury (LARMA) trial (n=218). Factor B and factor H levels were quantified using ELISA using samples from the ARDSnet LARMA and Statins for Acutely Injured Lungs from Sepsis (SAILS) (n=224) trials. Meta-analyses included previously quantified AH50, factor B and factor H values from an observational registry (Acute Lung Injury Registry and Biospecimen Repository (ALIR)). Complement C3, and complement activation products C3a and Ba plasma levels were measured in SAILS. Results: AH50 greater than the median was associated with reduced mortality in meta-analysis of LARMA and ALIR (hazard ratio (HR) 0.66, 95% CI 0.45-0.96). In contrast, patients in the lowest AH50 quartile demonstrated relative deficiency of both factor B and factor H. Relative deficiency of factor B (HR 1.99, 95% CI 1.44-2.75) or factor H (HR 1.52, 95% CI 1.09-2.11) was associated with increased mortality in meta-analysis of LARMA, SAILS and ALIR. Relative factor H deficiency was associated with increased factor consumption, as evidenced by lower factor B and C3 levels and Ba:B and C3a:C3 ratios. Higher factor H levels associated with lower inflammatory markers. Conclusions: Relative factor H deficiency, higher Ba:B and C3a:C3 ratios and lower factor B and C3 levels suggest a subset of ARDS with complement factor exhaustion, impaired alternative pathway function, and increased mortality, that may be amenable to therapeutic targeting.

The upper and lower respiratory tract microbiome in severe aspiration pneumonia.

Uncertainty persists whether anaerobic bacteria represent important pathogens in aspiration pneumonia. In a nested case-control study of mechanically ventilated patients classified as macro-aspiration pneumonia (MAsP, n = 56), non-macro-aspiration pneumonia (NonMAsP, n = 91), and uninfected controls (n = 11), we profiled upper (URT) and lower respiratory tract (LRT) microbiota with bacterial 16S rRNA gene sequencing, measured plasma host-response biomarkers, analyzed bacterial communities by diversity and oxygen requirements, and performed unsupervised clustering with Dirichlet Multinomial Models (DMM). MAsP and NonMAsP patients had indistinguishable microbiota profiles by alpha diversity and oxygen requirements with similar host-response profiles and 60-day survival. Unsupervised DMM clusters revealed distinct bacterial clusters in the URT and LRT, with low-diversity clusters enriched for facultative anaerobes and typical pathogens, associated with higher plasma levels of SPD and sCD14 and worse 60-day survival. The predictive inter-patient variability in these bacterial profiles highlights the importance of microbiome study in patient sub-phenotyping and precision medicine approaches for severe pneumonia.

Serum metabolomic signatures of fatty acid oxidation defects differentiate host-response subphenotypes of acute respiratory distress syndrome.

BACKGROUND: Fatty acid oxidation (FAO) defects have been implicated in experimental models of acute lung injury and associated with poor outcomes in critical illness. In this study, we examined acylcarnitine profiles and 3-methylhistidine as markers of FAO defects and skeletal muscle catabolism, respectively, in patients with acute respiratory failure. We determined whether these metabolites were associated with host-response ARDS subphenotypes, inflammatory biomarkers, and clinical outcomes in acute respiratory failure. METHODS: In a nested case-control cohort study, we performed targeted analysis of serum metabolites of patients intubated for airway protection (airway controls), Class 1 (hypoinflammatory), and Class 2 (hyperinflammatory) ARDS patients (N = 50 per group) during early initiation of mechanical ventilation. Relative amounts were quantified by liquid chromatography high resolution mass spectrometry using isotope-labeled standards and analyzed with plasma biomarkers and clinical data. RESULTS: Of the acylcarnitines analyzed, octanoylcarnitine levels were twofold increased in Class 2 ARDS relative to Class 1 ARDS or airway controls (P = 0.0004 and < 0.0001, respectively) and was positively associated with Class 2 by quantile g-computation analysis (P = 0.004). In addition, acetylcarnitine and 3-methylhistidine were increased in Class 2 relative to Class 1 and positively correlated with inflammatory biomarkers. In all patients within the study with acute respiratory failure, increased 3-methylhistidine was observed in non-survivors at 30 days (P = 0.0018), while octanoylcarnitine was increased in patients requiring vasopressor support but not in non-survivors (P = 0.0001 and P = 0.28, respectively). CONCLUSIONS: This study demonstrates that increased levels of acetylcarnitine, octanoylcarnitine, and 3-methylhistidine distinguish Class 2 from Class 1 ARDS patients and airway controls. Octanoylcarnitine and 3-methylhistidine were associated with poor outcomes in patients with acute respiratory failure across the cohort independent of etiology or host-response subphenotype. These findings suggest a role for serum metabolites as biomarkers in ARDS and poor outcomes in critically ill patients early in the clinical course.

Gut-lung crosstalk during critical illness.

PURPOSE OF REVIEW: Study of organ crosstalk in critical illness has uncovered complex biological communication between different organ systems, but the role of microbiota in organ crosstalk has received limited attention. We highlight the emerging understanding of the gut-lung axis, and how the largest biomass of the human body in the gut may affect lung physiology in critical illness. RECENT FINDINGS: Disruption of healthy gut microbial communities and replacement by disease-promoting pathogens (pathobiome) generates a maladaptive transmitter of messages from the gut to the lungs, connected via the portal venous and the mesenteric lymphatic systems. Gut barrier impairment allows for microbial translocation (living organisms or cellular fragments) to the lungs. Host-microbiota interactions in the gut mucosa can also impact lung physiology through microbial metabolite secretion or host-derived messengers (hormones, cytokines or immune cells). Clinical examples like the prevention of ventilator-associated pneumonia by selective decontamination of the digestive tract show that the gut-lung axis can be manipulated therapeutically. SUMMARY: A growing body of evidence supports the pathophysiological relevance of the gut-lung axis, yet we are only at the brink of understanding the therapeutic and prognostic relevance of the gut microbiome, metabolites and host-microbe interactions in critical illness.

Inter-rater reliability and prognostic value of baseline Radiographic Assessment of Lung Edema (RALE) scores in observational cohort studies of inpatients with COVID-19.

OBJECTIVES: To reliably quantify the radiographic severity of COVID-19 pneumonia with the Radiographic Assessment of Lung Edema (RALE) score on clinical chest X-rays among inpatients and examine the prognostic value of baseline RALE scores on COVID-19 clinical outcomes. SETTING: Hospitalised patients with COVID-19 in dedicated wards and intensive care units from two different hospital systems. PARTICIPANTS: 425 patients with COVID-19 in a discovery data set and 415 patients in a validation data set. PRIMARY AND SECONDARY OUTCOMES: We measured inter-rater reliability for RALE score annotations by different reviewers and examined for associations of consensus RALE scores with the level of respiratory support, demographics, physiologic variables, applied therapies, plasma host-response biomarkers, SARS-CoV-2 RNA load and clinical outcomes. RESULTS: Inter-rater agreement for RALE scores improved from fair to excellent following reviewer training and feedback (intraclass correlation coefficient of 0.85 vs 0.93, respectively). In the discovery cohort, the required level of respiratory support at the time of CXR acquisition (supplemental oxygen or non-invasive ventilation (n=178); invasive-mechanical ventilation (n=234), extracorporeal membrane oxygenation (n=13)) was significantly associated with RALE scores (median (IQR): 20.0 (14.1-26.7), 26.0 (20.5-34.0) and 44.5 (34.5-48.0), respectively, p<0.0001). Among invasively ventilated patients, RALE scores were significantly associated with worse respiratory mechanics (plateau and driving pressure) and gas exchange metrics (PaO2/FiO2 and ventilatory ratio), as well as higher plasma levels of IL-6, soluble receptor of advanced glycation end-products and soluble tumour necrosis factor receptor 1 (p<0.05). RALE scores were independently associated with 90-day survival in a multivariate Cox proportional hazards model (adjusted HR 1.04 (1.02-1.07), p=0.002). We replicated the significant associations of RALE scores with baseline disease severity and mortality in the independent validation data set. CONCLUSIONS: With a reproducible method to measure radiographic severity in COVID-19, we found significant associations with clinical and physiologic severity, host inflammation and clinical outcomes. The incorporation of radiographic severity assessments in clinical decision-making may provide important guidance for prognostication and treatment allocation in COVID-19.

Trajectories of Host-Response Subphenotypes in Patients With COVID-19 Across the Spectrum of Respiratory Support.

BACKGROUND: Hospitalized patients with severe COVID-19 follow heterogeneous clinical trajectories, requiring different levels of respiratory support and experiencing diverse clinical outcomes. Differences in host immune responses to SARS-CoV-2 infection may account for the heterogeneous clinical course, but we have limited data on the dynamic evolution of systemic biomarkers and related subphenotypes. Improved understanding of the dynamic transitions of host subphenotypes in COVID-19 may allow for improved patient selection for targeted therapies. RESEARCH QUESTION: We examined the trajectories of host-response profiles in severe COVID-19 and evaluated their prognostic impact on clinical outcomes. STUDY DESIGN AND METHODS: In this prospective observational study, we enrolled 323 inpatients with COVID-19 receiving different levels of baseline respiratory support: (1) low-flow oxygen (37%), (2) noninvasive ventilation (NIV) or high-flow oxygen (HFO; 29%), (3) invasive mechanical ventilation (27%), and (4) extracorporeal membrane oxygenation (7%). We collected plasma samples on enrollment and at days 5 and 10 to measure host-response biomarkers. We classified patients by inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker, and subphenotype trajectories and outcomes during hospitalization. RESULTS: IL-6, procalcitonin, and angiopoietin 2 persistently were elevated in patients receiving higher levels of respiratory support, whereas soluble receptor of advanced glycation end products (sRAGE) levels displayed the inverse pattern. Patients receiving NIV or HFO at baseline showed the most dynamic clinical trajectory, with 24% eventually requiring intubation and exhibiting worse 60-day mortality than patients receiving invasive mechanical ventilation at baseline (67% vs 35%; P < .0001). sRAGE levels predicted NIV failure and worse 60-day mortality for patients receiving NIV or HFO, whereas IL-6 levels were predictive in all patients regardless of level of support (P < .01). Patients classified to a hyperinflammatory subphenotype at baseline (< 10%) showed worse 60-day survival (P < .0001) and 50% of them remained classified as hyperinflammatory at 5 days after enrollment. INTERPRETATION: Longitudinal study of the systemic host response in COVID-19 revealed substantial and predictive interindividual variability influenced by baseline levels of respiratory support.

Trajectories of host-response biomarkers and inflammatory subphenotypes in COVID-19 patients across the spectrum of respiratory support.

Purpose: Enhanced understanding of the dynamic changes in the dysregulated inflammatory response in COVID-19 may help improve patient selection and timing for immunomodulatory therapies. Methods: We enrolled 323 COVID-19 inpatients on different levels of baseline respiratory support: i) Low Flow Oxygen (37%), ii) Non-Invasive Ventilation or High Flow Oxygen (NIV_HFO, 29%), iii) Invasive Mechanical Ventilation (IMV, 27%), and iv) Extracorporeal Membrane Oxygenation (ECMO, 7%). We collected plasma samples upon enrollment and days 5 and 10 to measure host-response biomarkers. We classified subjects into inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker and subphenotype trajectories and outcomes during hospitalization. Results: IL-6, procalcitonin, and Angiopoietin-2 were persistently elevated in patients at higher levels of respiratory support, whereas sRAGE displayed the inverse pattern. Patients on NIV_HFO at baseline had the most dynamic clinical trajectory, with 26% eventually requiring intubation and exhibiting worse 60-day mortality than IMV patients at baseline (67% vs. 35%, p<0.0001). sRAGE levels predicted NIV failure and worse 60-day mortality for NIV_HFO patients, whereas IL-6 levels were predictive in IMV or ECMO patients. Hyper-inflammatory subjects at baseline (<10% by both models) had worse 60-day survival (p<0.0001) and 50% of them remained classified as hyper-inflammatory on follow-up sampling at 5 days post-enrollment. Receipt of combined immunomodulatory therapies (steroids and anti-IL6 agents) was associated with markedly increased IL-6 and lower Angiopoietin-2 levels (p<0.05). Conclusions: Longitudinal study of systemic host responses in COVID-19 revealed substantial and predictive inter-individual variability, influenced by baseline levels of respiratory support and concurrent immunomodulatory therapies.