Host Response Changes and Their Association with Mortality in COVID-19 Patients with Lymphopenia.

Rationale: Lymphopenia in coronavirus disease (COVID-19) is associated with increased mortality. Objectives: To explore the association between lymphopenia, host response aberrations, and mortality in patients with lymphopenic COVID-19. Methods: We determined 43 plasma biomarkers reflective of four pathophysiological domains: endothelial cell and coagulation activation, inflammation and organ damage, cytokine release, and chemokine release. We explored if decreased concentrations of lymphocyte-derived proteins in patients with lymphopenia were associated with an increase in mortality. We sought to identify host response phenotypes in patients with lymphopenia by cluster analysis of plasma biomarkers. Measurements and Main Results: A total of 439 general ward patients with COVID-19 were stratified by baseline lymphocyte counts: normal (>1.0 × 109/L; n = 167), mild lymphopenia (>0.5 to ⩽1.0 × 109/L; n = 194), and severe lymphopenia (⩽0.5 × 109/L; n = 78). Lymphopenia was associated with alterations in each host response domain. Lymphopenia was associated with increased mortality. Moreover, in patients with lymphopenia (n = 272), decreased concentrations of several lymphocyte-derived proteins (e.g., CCL5, IL-4, IL-13, IL-17A) were associated with an increase in mortality (at P < 0.01 or stronger significance levels). A cluster analysis revealed three host response phenotypes in patients with lymphopenia: "hyporesponsive" (23.2%), "hypercytokinemic" (36.4%), and "inflammatory-injurious" (40.4%), with substantially differing mortality rates of 9.5%, 5.1%, and 26.4%, respectively. A 10-biomarker model accurately predicted these host response phenotypes in an external cohort with similar mortality distribution. The inflammatory-injurious phenotype showed a remarkable combination of relatively high inflammation and organ damage markers with high antiinflammatory cytokine levels yet low proinflammatory cytokine levels. Conclusions: Lymphopenia in COVID-19 signifies a heterogenous group of patients with distinct host response features. Specific host responses contribute to lymphopenia-associated mortality in COVID-19, including reduced CCL5 levels.

Host and Microbe Blood Metagenomics Reveals Key Pathways Characterizing Critical Illness Phenotypes.

Rationale: Two molecular phenotypes of sepsis and acute respiratory distress syndrome, termed hyperinflammatory and hypoinflammatory, have been consistently identified by latent class analysis in numerous cohorts, with widely divergent clinical outcomes and differential responses to some treatments; however, the key biological differences between these phenotypes remain poorly understood.Objectives: We used host and microbe metagenomic sequencing data from blood to deepen our understanding of biological differences between latent class analysis-derived phenotypes and to assess concordance between the latent class analysis-derived phenotypes and phenotypes reported by other investigative groups (e.g., Sepsis Response Signature [SRS1-2], molecular diagnosis and risk stratification of sepsis [MARS1-4], reactive and uninflamed).Methods: We analyzed data from 113 patients with hypoinflammatory sepsis and 76 patients with hyperinflammatory sepsis enrolled in a two-hospital prospective cohort study. Molecular phenotypes had been previously assigned using latent class analysis.Measurements and Main Results: The hyperinflammatory and hypoinflammatory phenotypes of sepsis had distinct gene expression signatures, with 5,755 genes (31%) differentially expressed. The hyperinflammatory phenotype was associated with elevated expression of innate immune response genes, whereas the hypoinflammatory phenotype was associated with elevated expression of adaptive immune response genes and, notably, T cell response genes. Plasma metagenomic analysis identified differences in prevalence of bacteremia, bacterial DNA abundance, and composition between the phenotypes, with an increased presence and abundance of Enterobacteriaceae in the hyperinflammatory phenotype. Significant overlap was observed between these phenotypes and previously identified transcriptional subtypes of acute respiratory distress syndrome (reactive and uninflamed) and sepsis (SRS1-2). Analysis of data from the VANISH trial indicated that corticosteroids might have a detrimental effect in patients with the hypoinflammatory phenotype.Conclusions: The hyperinflammatory and hypoinflammatory phenotypes have distinct transcriptional and metagenomic features that could be leveraged for precision treatment strategies.

From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations For Developing Precision Medicine in ICU.

Critical care uses syndromic definitions to describe patient groups for clinical practice and research. There is growing recognition that a "precision medicine" approach is required and that integrated biologic and physiologic data identify reproducible subpopulations that may respond differently to treatment. This article reviews the current state of the field and considers how to successfully transition to a precision medicine approach. In order to impact clinical care, identified subpopulations must do more than differentiate prognosis. They must differentiate response to treatment, ideally by defining subgroups with distinct functional or pathobiological mechanisms (endotypes). There are now multiple examples of reproducible subpopulations of sepsis, acute respiratory distress syndrome, and acute kidney or brain injury described using clinical, physiological, and/or biological data. Many of these subpopulations have demonstrated the potential to define differential treatment response, largely in retrospective studies, and that the same treatment-responsive subpopulations may cross multiple clinical syndromes (treatable traits). To bring about a change in clinical practice, a precision medicine approach must be evaluated in prospective clinical studies requiring novel adaptive trial designs. Several such studies are underway but there are multiple challenges to be tackled. Such subpopulations must be readily identifiable and be applicable to all critically ill populations around the world. Subdividing clinical syndromes into subpopulations will require large patient numbers. Global collaboration of investigators, clinicians, industry and patients over many years will therefore be required to transition to a precision medicine approach and ultimately realize treatment advances seen in other medical fields. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Breath Markers of Oxidative Stress in Children with Severe Viral Lower Respiratory Tract Infection.

Severe viral lower respiratory tract infection (LRTI), resulting in both acute and long-term pulmonary disease, constitutes a substantial burden among young children. Viral LRTI triggers local oxidative stress pathways by infection and inflammation, and supportive care in the pediatric intensive care unit may further aggravate oxidative injury. The main goal of this exploratory study was to identify and monitor breath markers linked to oxidative stress in children over the disease course of severe viral LRTI. Exhaled breath was sampled during invasive ventilation, and volatile organic compounds (VOCs) were analyzed using gas chromatography and mass spectrometry. VOCs were selected in an untargeted principal component analysis and assessed for change over time. In addition, identified VOCs were correlated with clinical parameters. Seventy breath samples from 21 patients were analyzed. A total of 15 VOCs were identified that contributed the most to the explained variance of breath markers. Of these 15 VOCs, 10 were previously linked to pathways of oxidative stress. Eight VOCs, including seven alkanes and methyl alkanes, significantly decreased from the initial phase of ventilation to the day of extubation. No correlation was observed with the administered oxygen dose, whereas six VOCs showed a poor to strong positive correlation with driving pressure. In this prospective study of children with severe viral LRTI, the majority of VOCs that were most important for the explained variance mirrored clinical improvement. These breath markers could potentially help monitor the pulmonary oxidative status in these patients, but further research with other objective measures of pulmonary injury is required.

The alveolar fibroproliferative response in moderate to severe COVID-19-related acute respiratory distress syndrome and 1-yr follow-up.

COVID-19-related acute respiratory distress syndrome (ARDS) can lead to long-term pulmonary fibrotic lesions. Alveolar fibroproliferative response (FPR) is a key factor in the development of pulmonary fibrosis. N-terminal peptide of procollagen III (NT-PCP-III) is a validated biomarker for activated FPR in ARDS. This study aimed to assess the association between dynamic changes in alveolar FPR and long-term outcomes, as well as mortality in COVID-19 ARDS patients. We conducted a prospective cohort study of 154 COVID-19 ARDS patients. We collected bronchoalveolar lavage (BAL) and blood samples for measurement of 17 pulmonary fibrosis biomarkers, including NT-PCP-III. We assessed pulmonary function and chest computed tomography (CT) at 3 and 12 mo after hospital discharge. We performed joint modeling to assess the association between longitudinal changes in biomarker levels and mortality at day 90 after starting mechanical ventilation. 154 patients with 284 BAL samples were analyzed. Of all patients, 40% survived to day 90, of whom 54 completed the follow-up procedure. A longitudinal increase in NT-PCP-III was associated with increased mortality (HR 2.89, 95% CI: 2.55-3.28; P < 0.001). Forced vital capacity and diffusion for carbon monoxide were impaired at 3 mo but improved significantly at one year after hospital discharge (P = 0.03 and P = 0.004, respectively). There was no strong evidence linking alveolar FPR during hospitalization and signs of pulmonary fibrosis in pulmonary function or chest CT images during 1-yr follow-up. In COVID-19 ARDS patients, alveolar FPR during hospitalization was associated with higher mortality but not with the presence of long-term fibrotic lung sequelae within survivors.NEW & NOTEWORTHY This is the first prospective study on the longitudinal alveolar fibroproliferative response in COVID-19 ARDS and its relationship with mortality and long-term follow-up. We used the largest cohort of COVID-19 ARDS patients who had consecutive bronchoalveolar lavages and measured 17 pulmonary fibroproliferative biomarkers. We found that a higher fibroproliferative response during admission was associated with increased mortality, but not correlated with long-term fibrotic lung sequelae in survivors.

Breath metabolomics for diagnosis of acute respiratory distress syndrome.

BACKGROUND: Acute respiratory distress syndrome (ARDS) poses challenges in early identification. Exhaled breath contains metabolites reflective of pulmonary inflammation. AIM: To evaluate the diagnostic accuracy of breath metabolites for ARDS in invasively ventilated intensive care unit (ICU) patients. METHODS: This two-center observational study included critically ill patients receiving invasive ventilation. Gas chromatography and mass spectrometry (GC-MS) was used to quantify the exhaled metabolites. The Berlin definition of ARDS was assessed by three experts to categorize all patients into "certain ARDS", "certain no ARDS" and "uncertain ARDS" groups. The patients with "certain" labels from one hospital formed the derivation cohort used to train a classifier built based on the five most significant breath metabolites. The diagnostic accuracy of the classifier was assessed in all patients from the second hospital and combined with the lung injury prediction score (LIPS). RESULTS: A total of 499 patients were included in this study. Three hundred fifty-seven patients were included in the derivation cohort (60 with certain ARDS; 17%), and 142 patients in the validation cohort (47 with certain ARDS; 33%). The metabolites 1-methylpyrrole, 1,3,5-trifluorobenzene, methoxyacetic acid, 2-methylfuran and 2-methyl-1-propanol were included in the classifier. The classifier had an area under the receiver operating characteristics curve (AUROCC) of 0.71 (CI 0.63-0.78) in the derivation cohort and 0.63 (CI 0.52-0.74) in the validation cohort. Combining the breath test with the LIPS does not significantly enhance the diagnostic performance. CONCLUSION: An exhaled breath metabolomics-based classifier has moderate diagnostic accuracy for ARDS but was not sufficiently accurate for clinical use, even after combination with a clinical prediction score.

Inflammatory subphenotypes previously identified in ARDS are associated with mortality at intensive care unit discharge: a secondary analysis of a prospective observational study.

BACKGROUND: Intensive care unit (ICU)-survivors have an increased risk of mortality after discharge compared to the general population. On ICU admission subphenotypes based on the plasma biomarker levels of interleukin-8, protein C and bicarbonate have been identified in patients admitted with acute respiratory distress syndrome (ARDS) that are prognostic of outcome and predictive of treatment response. We hypothesized that if these inflammatory subphenotypes previously identified among ARDS patients are assigned at ICU discharge in a more general critically ill population, they are associated with short- and long-term outcome. METHODS: A secondary analysis of a prospective observational cohort study conducted in two Dutch ICUs between 2011 and 2014 was performed. All patients discharged alive from the ICU were at ICU discharge adjudicated to the previously identified inflammatory subphenotypes applying a validated parsimonious model using variables measured median 10.6 h [IQR, 8.0-31.4] prior to ICU discharge. Subphenotype distribution at ICU discharge, clinical characteristics and outcomes were analyzed. As a sensitivity analysis, a latent class analysis (LCA) was executed for subphenotype identification based on plasma protein biomarkers at ICU discharge reflective of coagulation activation, endothelial cell activation and inflammation. Concordance between the subphenotyping strategies was studied. RESULTS: Of the 8332 patients included in the original cohort, 1483 ICU-survivors had plasma biomarkers available and could be assigned to the inflammatory subphenotypes. At ICU discharge 6% (n = 86) was assigned to the hyperinflammatory and 94% (n = 1397) to the hypoinflammatory subphenotype. Patients assigned to the hyperinflammatory subphenotype were discharged with signs of more severe organ dysfunction (SOFA scores 7 [IQR 5-9] vs. 4 [IQR 2-6], p < 0.001). Mortality was higher in patients assigned to the hyperinflammatory subphenotype (30-day mortality 21% vs. 11%, p = 0.005; one-year mortality 48% vs. 28%, p < 0.001). LCA deemed 2 subphenotypes most suitable. ICU-survivors from class 1 had significantly higher mortality compared to class 2. Patients belonging to the hyperinflammatory subphenotype were mainly in class 1. CONCLUSIONS: Patients assigned to the hyperinflammatory subphenotype at ICU discharge showed significantly stronger anomalies in coagulation activation, endothelial cell activation and inflammation pathways implicated in the pathogenesis of critical disease and increased mortality until one-year follow up.

Heterogeneity of treatment effect of vilobelimab in COVID-19: a secondary analysis of a randomised controlled trial.

In a phase 3 trial (PANAMO, NCT04333420), vilobelimab, a complement 5a (C5a) inhibitor, reduced 28-day mortality in mechanically ventilated COVID-19 patients. This post hoc analysis of 368 patients aimed to explore treatment heterogeneity through unsupervised learning. All available clinical variables at baseline were used as input. Treatment heterogeneity was assessed using latent class analysis (LCA), Ward's hierarchical clustering (HC) and the adjudication to previously described clinical sepsis phenotypes. The primary outcome was 28-day mortality. For LCA, a 2-class latent model was deemed most suitable. In the LCA model, 82 (22%) patients were assigned to class 1 and 286 (78%) to class 2. Class 1 was defined by more severely ill patients with significantly higher mortality. In an adjusted logistic regression, no heterogeneity of treatment effect (HTE) between classes was observed (p = 0.998). For HC, no significant classes were found (p = 0.669). Using the previously described clinical sepsis subtypes, 41 patients (11%) were adjudicated subtype alpha (α), 17 (5%) beta (ß), 112 (30%) delta (δ) and 198 (54%) gamma (γ). HTE was observed between clinical subtypes (p = 0.001) with improved 28-day mortality after treatment with vilobelimab for the δ subtype (OR = 0.17, 95% CI 0.07-0.40, p < 0.001). No signal for harm of treatment with vilobelimab was observed in any class or clinical subtype. Overall, treatment effect with vilobelimab was consistent across different classes and subtypes, except for the δ subtype, suggesting potential additional benefit for the most severely ill patients.

Clustering COVID-19 ARDS patients through the first days of ICU admission. An analysis of the CIBERESUCICOVID Cohort.

BACKGROUND: Acute respiratory distress syndrome (ARDS) can be classified into sub-phenotypes according to different inflammatory/clinical status. Prognostic enrichment was achieved by grouping patients into hypoinflammatory or hyperinflammatory sub-phenotypes, even though the time of analysis may change the classification according to treatment response or disease evolution. We aimed to evaluate when patients can be clustered in more than 1 group, and how they may change the clustering of patients using data of baseline or day 3, and the prognosis of patients according to their evolution by changing or not the cluster. METHODS: Multicenter, observational prospective, and retrospective study of patients admitted due to ARDS related to COVID-19 infection in Spain. Patients were grouped according to a clustering mixed-type data algorithm (k-prototypes) using continuous and categorical readily available variables at baseline and day 3. RESULTS: Of 6205 patients, 3743 (60%) were included in the study. According to silhouette analysis, patients were grouped in two clusters. At baseline, 1402 (37%) patients were included in cluster 1 and 2341(63%) in cluster 2. On day 3, 1557(42%) patients were included in cluster 1 and 2086 (57%) in cluster 2. The patients included in cluster 2 were older and more frequently hypertensive and had a higher prevalence of shock, organ dysfunction, inflammatory biomarkers, and worst respiratory indexes at both time points. The 90-day mortality was higher in cluster 2 at both clustering processes (43.8% [n = 1025] versus 27.3% [n = 383] at baseline, and 49% [n = 1023] versus 20.6% [n = 321] on day 3). Four hundred and fifty-eight (33%) patients clustered in the first group were clustered in the second group on day 3. In contrast, 638 (27%) patients clustered in the second group were clustered in the first group on day 3. CONCLUSIONS: During the first days, patients can be clustered into two groups and the process of clustering patients may change as they continue to evolve. This means that despite a vast majority of patients remaining in the same cluster, a minority reaching 33% of patients analyzed may be re-categorized into different clusters based on their progress. Such changes can significantly impact their prognosis.

Lung Ultrasound Prediction Model for Acute Respiratory Distress Syndrome: A Multicenter Prospective Observational Study.

Rationale: Lung ultrasound (LUS) is a promising tool for diagnosis of acute respiratory distress syndrome (ARDS), but adequately sized studies with external validation are lacking. Objectives: To develop and validate a data-driven LUS score for diagnosis of ARDS and compare its performance with that of chest radiography (CXR). Methods: This multicenter prospective observational study included invasively ventilated ICU patients who were divided into a derivation cohort and a validation cohort. Three raters scored ARDS according to the Berlin criteria, resulting in a classification of "certain no ARDS," or "certain ARDS" when experts agreed or "uncertain ARDS" when evaluations conflicted. Uncertain cases were classified in a consensus meeting. Results of a 12-region LUS exam were used in a logistic regression model to develop the LUS-ARDS score. Measurements and Main Results: Three hundred twenty-four (16% certain ARDS) and 129 (34% certain ARDS) patients were included in the derivation cohort and the validation cohort, respectively. With an ARDS diagnosis by the expert panel as the reference test, the LUS-ARDS score, including the left and right LUS aeration scores and anterolateral pleural line abnormalities, had an area under the receiver operating characteristic (ROC) curve of 0.90 (95% confidence interval [CI], 0.85-0.95) in certain patients of the derivation cohort and 0.80 (95% CI, 0.72-0.87) in all patients of the validation cohort. Within patients who had imaging-gold standard chest computed tomography available, diagnostic accuracy of eight independent CXR readers followed the ROC curve of the LUS-ARDS score. Conclusions: The LUS-ARDS score can be used to accurately diagnose ARDS also after external validation. The LUS-ARDS score may be a useful adjunct to a diagnosis of ARDS after further validation, as it showed performance comparable with that of the current practice with experienced CXR readers but more objectifiable diagnostic accuracy at each cutoff.

Microbial Volatiles as Diagnostic Biomarkers of Bacterial Lung Infection in Mechanically Ventilated Patients.

BACKGROUND: Early and accurate recognition of respiratory pathogens is crucial to prevent increased risk of mortality in critically ill patients. Microbial-derived volatile organic compounds (mVOCs) in exhaled breath could be used as noninvasive biomarkers of infection to support clinical diagnosis. METHODS: In this study, we investigated the diagnostic potential of in vitro-confirmed mVOCs in the exhaled breath of patients under mechanical ventilation from the BreathDx study. Samples were analyzed by thermal desorption-gas chromatography-mass spectrometry. RESULTS: Pathogens from bronchoalveolar lavage (BAL) cultures were identified in 45 of 89 patients and Staphylococcus aureus was the most commonly identified pathogen (n = 15). Of 19 mVOCs detected in the in vitro culture headspace of 4 common respiratory pathogens (S. aureus, Pseudomonas aeruginosa, Klebsiella pneumoniae, and Escherichia coli), 14 were found in exhaled breath samples. Higher concentrations of 2 mVOCs were found in the exhaled breath of patients infected with S. aureus compared to those without (3-methylbutanal: P < .01, area under the receiver operating characteristic curve [AUROC] = 0.81-0.87; and 3-methylbutanoic acid: P = .01, AUROC = 0.79-0.80). In addition, bacteria identified from BAL cultures that are known to metabolize tryptophan (E. coli, Klebsiella oxytoca, and Haemophilus influenzae) were grouped and found to produce higher concentrations of indole compared to breath samples with culture-negative (P = .034) and other pathogen-positive (P = .049) samples. CONCLUSIONS: This study demonstrates the capability of using mVOCs to detect the presence of specific pathogen groups with potential to support clinical diagnosis. Although not all mVOCs were found in patient samples within this small pilot study, further targeted and qualitative investigation is warranted using multicenter clinical studies.

Hyperoxia-induced lung injury in acute respiratory distress syndrome: what is its relative impact?

Over the past decade, the interest in oxygen toxicity has led to various observational studies and randomized clinical trials in critically ill patients, assessing the association with outcomes and the potential benefit of restrictive oxygenation targets. Yet to date, no consensus has been reached regarding the clinical impact of hyperoxia and hyperoxemia. In this perspective article, we explore the experimental and clinical evidence on hyperoxia-induced lung injury (HILI) and assess its relative impact in current critical care practice, specifically in patients who require oxygen therapy due to acute respiratory distress syndrome (ARDS). Here, we suggest that in current clinical practice in the setting of ARDS HILI may actually be of less importance than other ventilator-related factors.

Biomarkers of alveolar epithelial injury and endothelial dysfunction are associated with scores of pulmonary edema in invasively ventilated patients.

Pulmonary edema is a central hallmark of acute respiratory distress syndrome (ARDS). Endothelial dysfunction and epithelial injury contribute to alveolar-capillary permeability but their differential contribution to pulmonary edema development remains understudied. Plasma levels of surfactant protein-D (SP-D), soluble receptor for advanced glycation end products (sRAGE), and angiopoietin-2 (Ang-2) were measured in a prospective, multicenter cohort of invasively ventilated patients. Pulmonary edema was quantified using the radiographic assessment of lung edema (RALE) and global lung ultrasound (LUS) score. Variables were collected within 48 h after intubation. Linear regression was used to examine the association of the biomarkers with pulmonary edema. In 362 patients, higher SP-D, sRAGE, and Ang-2 concentrations were significantly associated with higher RALE and global LUS scores. After stratification by ARDS subgroups (pulmonary, nonpulmonary, COVID, non-COVID), the positive association of SP-D levels with pulmonary edema remained, whereas sRAGE and Ang-2 showed less consistent associations throughout the subgroups. In a multivariable analysis, SP-D levels were most strongly associated with pulmonary edema when combined with sRAGE (RALE score: ßSP-D = 6.79 units/log10 pg/mL, ßsRAGE = 3.84 units/log10 pg/mL, R2 = 0.23; global LUS score: ßSP-D = 3.28 units/log10 pg/mL, ßsRAGE = 2.06 units/log10 pg/mL, R2 = 0.086), whereas Ang-2 did not further improve the model. Biomarkers of epithelial injury and endothelial dysfunction were associated with pulmonary edema in invasively ventilated patients. SP-D and sRAGE showed the strongest association, suggesting that epithelial injury may form a final common pathway in the alveolar-capillary barrier dysfunction underlying pulmonary edema.

Acute respiratory distress syndrome: causes, pathophysiology, and phenotypes.

Acute respiratory distress syndrome (ARDS) is a common clinical syndrome of acute respiratory failure as a result of diffuse lung inflammation and oedema. ARDS can be precipitated by a variety of causes. The pathophysiology of ARDS is complex and involves the activation and dysregulation of multiple overlapping and interacting pathways of injury, inflammation, and coagulation, both in the lung and systemically. Mechanical ventilation can contribute to a cycle of lung injury and inflammation. Resolution of inflammation is a coordinated process that requires downregulation of proinflammatory pathways and upregulation of anti-inflammatory pathways. The heterogeneity of the clinical syndrome, along with its biology, physiology, and radiology, has increasingly been recognised and incorporated into identification of phenotypes. A precision-medicine approach that improves the identification of more homogeneous ARDS phenotypes should lead to an improved understanding of its pathophysiological mechanisms and how they differ from patient to patient.

Autoantibodies Neutralizing Type I IFNs in the Bronchoalveolar Lavage of at Least 10% of Patients During Life-Threatening COVID-19 Pneumonia.

Autoantibodies (auto-Abs) neutralizing type I interferons (IFNs) are found in the blood of at least 15% of unvaccinated patients with life-threatening COVID-19 pneumonia. We report here the presence of auto-Abs neutralizing type I IFNs in the bronchoalveolar lavage (BAL) of 54 of the 415 unvaccinated patients (13%) with life-threatening COVID-19 pneumonia tested. The 54 individuals with neutralizing auto-Abs in the BAL included 45 (11%) with auto-Abs against IFN-α2, 37 (9%) with auto-Abs against IFN-ω, 54 (13%) with auto-Abs against IFN-α2 and/or ω, and five (1%) with auto-Abs against IFN-ß, including three (0.7%) with auto-Abs neutralizing IFN-α2, IFN-ω, and IFN-ß, and two (0.5%) with auto-Abs neutralizing IFN-α2 and IFN-ß. Auto-Abs against IFN-α2 also neutralize the other 12 subtypes of IFN-α. Paired plasma samples were available for 95 patients. All seven patients with paired samples who had detectable auto-Abs in BAL also had detectable auto-Abs in plasma, and one patient had auto-Abs detectable only in blood. Auto-Abs neutralizing type I IFNs are, therefore, present in the alveolar space of at least 10% of patients with life-threatening COVID-19 pneumonia. These findings suggest that these auto-Abs impair type I IFN immunity in the lower respiratory tract, thereby contributing to hypoxemic COVID-19 pneumonia.

Persistent alveolar inflammatory response in critically ill patients with COVID-19 is associated with mortality.

INTRODUCTION: Patients with COVID-19-related acute respiratory distress syndrome (ARDS) show limited systemic hyperinflammation, but immunomodulatory treatments are effective. Little is known about the inflammatory response in the lungs and if this could be targeted using high-dose steroids (HDS). We aimed to characterise the alveolar immune response in patients with COVID-19-related ARDS, to determine its association with mortality, and to explore the association between HDS treatment and the alveolar immune response. METHODS: In this observational cohort study, a comprehensive panel of 63 biomarkers was measured in repeated bronchoalveolar lavage (BAL) fluid and plasma samples of patients with COVID-19 ARDS. Differences in alveolar-plasma concentrations were determined to characterise the alveolar inflammatory response. Joint modelling was performed to assess the longitudinal changes in alveolar biomarker concentrations, and the association between changes in alveolar biomarker concentrations and mortality. Changes in alveolar biomarker concentrations were compared between HDS-treated and matched untreated patients. RESULTS: 284 BAL fluid and paired plasma samples of 154 patients with COVID-19 were analysed. 13 biomarkers indicative of innate immune activation showed alveolar rather than systemic inflammation. A longitudinal increase in the alveolar concentration of several innate immune markers, including CC motif ligand (CCL)20 and CXC motif ligand (CXCL)1, was associated with increased mortality. Treatment with HDS was associated with a subsequent decrease in alveolar CCL20 and CXCL1 levels. CONCLUSIONS: Patients with COVID-19-related ARDS showed an alveolar inflammatory state related to the innate host response, which was associated with a higher mortality. HDS treatment was associated with decreasing alveolar concentrations of CCL20 and CXCL1.

ERS/ESICM/ESCMID/ALAT guidelines for the management of severe community-acquired pneumonia.

BACKGROUND: Severe community-acquired pneumonia (sCAP) is associated with high morbidity and mortality, and while European and non-European guidelines are available for community-acquired pneumonia, there are no specific guidelines for sCAP. MATERIALS AND METHODOLOGY: The European Respiratory Society (ERS), European Society of Intensive Care Medicine (ESICM), European Society of Clinical Microbiology and Infectious Diseases (ESCMID) and Latin American Thoracic Association (ALAT) launched a task force to develop the first international guidelines for sCAP. The panel comprised a total of 18 European and four non-European experts, as well as two methodologists. Eight clinical questions for sCAP diagnosis and treatment were chosen to be addressed. Systematic literature searches were performed in several databases. Meta-analyses were performed for evidence synthesis, whenever possible. The quality of evidence was assessed with GRADE (Grading of Recommendations, Assessment, Development and Evaluation). Evidence to Decision frameworks were used to decide on the direction and strength of recommendations. RESULTS: Recommendations issued were related to diagnosis, antibiotics, organ support, biomarkers and co-adjuvant therapy. After considering the confidence in effect estimates, the importance of outcomes studied, desirable and undesirable consequences of treatment, cost, feasibility, acceptability of the intervention and implications to health equity, recommendations were made for or against specific treatment interventions. CONCLUSIONS: In these international guidelines, ERS, ESICM, ESCMID and ALAT provide evidence-based clinical practice recommendations for diagnosis, empirical treatment and antibiotic therapy for sCAP, following the GRADE approach. Furthermore, current knowledge gaps have been highlighted and recommendations for future research have been made.

Age-related changes in plasma biomarkers and their association with mortality in COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19)-induced mortality occurs predominantly in older patients. Several immunomodulating therapies seem less beneficial in these patients. The biological substrate behind these observations is unknown. The aim of this study was to obtain insight into the association between ageing, the host response and mortality in patients with COVID-19. METHODS: We determined 43 biomarkers reflective of alterations in four pathophysiological domains: endothelial cell and coagulation activation, inflammation and organ damage, and cytokine and chemokine release. We used mediation analysis to associate ageing-driven alterations in the host response with 30-day mortality. Biomarkers associated with both ageing and mortality were validated in an intensive care unit and external cohort. RESULTS: 464 general ward patients with COVID-19 were stratified according to age decades. Increasing age was an independent risk factor for 30-day mortality. Ageing was associated with alterations in each of the host response domains, characterised by greater activation of the endothelium and coagulation system and stronger elevation of inflammation and organ damage markers, which was independent of an increase in age-related comorbidities. Soluble tumour necrosis factor receptor 1, soluble triggering receptor expressed on myeloid cells 1 and soluble thrombomodulin showed the strongest correlation with ageing and explained part of the ageing-driven increase in 30-day mortality (proportion mediated: 13.0%, 12.9% and 12.6%, respectively). CONCLUSIONS: Ageing is associated with a strong and broad modification of the host response to COVID-19, and specific immune changes likely contribute to increased mortality in older patients. These results may provide insight into potential age-specific immunomodulatory targets in COVID-19.

Exhaled Volatile Organic Compounds for Early Prediction of Bronchopulmonary Dysplasia in Infants Born Preterm.

OBJECTIVE(S): To investigate the predictive performances of exhaled breath volatile organic compounds (VOCs) for development of bronchopulmonary dysplasia (BPD) in infants born preterm. METHODS: Exhaled breath was collected from infants born <30 weeks' gestation at days 3 and 7 of life. Ion fragments detected by gas chromatography-mass spectrometry analysis were used to derive and internally validate a VOC prediction model for moderate or severe BPD at 36 weeks of postmenstrual age. We tested the predictive performance of the National Institute of Child Health and Human Development (NICHD) clinical BPD prediction model with and without VOCs. RESULTS: Breath samples were collected from 117 infants (mean gestation 26.8 ± 1.5 weeks). Thirty-three percent of the infants developed moderate or severe BPD. The VOC model showed a c-statistic of 0.89 (95% CI 0.80-0.97) and 0.92 (95% CI 0.84-0.99) for the prediction of BPD at days 3 and 7, respectively. Adding the VOCs to the clinical prediction model in noninvasively supported infants resulted in significant improvement in discriminative power on both days (day 3: c-statistic 0.83 vs 0.92, P value .04; day 7: c-statistic 0.82 vs 0.94, P value .03). CONCLUSIONS: This study showed that VOC profiles in exhaled breath of preterm infants on noninvasive support in the first week of life differ between those developing and not developing BPD. Adding VOCs to a clinical prediction model significantly improved its discriminative performance.

Integrating biology into clinical trial design.

PURPOSE OF REVIEW: Critical care medicine revolves around syndromes, such as acute respiratory distress syndrome (ARDS), sepsis and acute kidney injury. Few interventions have shown to be effective in large clinical trials, likely because of between-patient heterogeneity. Translational evidence suggests that more homogeneous biological subgroups can be identified and that differential treatment effects exist. Integrating biological considerations into clinical trial design is therefore an important frontier of critical care research. RECENT FINDINGS: The pathophysiology of critical care syndromes involves a multiplicity of processes, which emphasizes the difficulty of integrating biology into clinical trial design. Biological assessment can be integrated into clinical trials using predictive enrichment at trial inclusion, time-dependent variation to better understand treatment effects and biological markers as surrogate outcomes. SUMMARY: Integrating our knowledge on biological heterogeneity into clinical trial design, which has revolutionized other medical fields, could serve as a solution to implement personalized treatment in critical care syndromes. Changing the trial design by using predictive enrichment, incorporation of the evaluation of time-dependent changes and biological markers as surrogate outcomes may improve the likelihood of detecting a beneficial effect from targeted therapeutic interventions and the opportunity to test multiple lines of treatment per patient.