Mitochondrial N-formyl methionine peptides contribute to exaggerated neutrophil activation in patients with COVID-19.

Neutrophil dysregulation is well established in COVID-19. However, factors contributing to neutrophil activation in COVID-19 are not clear. We assessed if N-formyl methionine (fMet) contributes to neutrophil activation in COVID-19. Elevated levels of calprotectin, neutrophil extracellular traps (NETs) and fMet were observed in COVID-19 patients (n = 68), particularly in critically ill patients, as compared to HC (n = 19, p < 0.0001). Of note, the levels of NETs were higher in ICU patients with COVID-19 than in ICU patients without COVID-19 (p < 0.05), suggesting a prominent contribution of NETs in COVID-19. Additionally, plasma from COVID-19 patients with mild and moderate/severe symptoms induced in vitro neutrophil activation through fMet/FPR1 (formyl peptide receptor-1) dependent mechanisms (p < 0.0001). fMet levels correlated with calprotectin levels validating fMet-mediated neutrophil activation in COVID-19 patients (r = 0.60, p = 0.0007). Our data indicate that fMet is an important factor contributing to neutrophil activation in COVID-19 disease and may represent a potential target for therapeutic intervention.

Lung pericytes as mediators of inflammation.

Pericytes are microvascular mural cells that directly contact endothelial cells. They have long been recognized for their roles in vascular development and homeostasis, but more recently have been identified as key mediators of the host response to injury. In this context, pericytes possess a surprising degree of cellular plasticity, behaving dynamically when activated and potentially participating in a range of divergent host responses to injury. Although there has been much interest in the role of pericytes in fibrosis and tissue repair, their involvement in the initial inflammatory process has been understudied and is increasingly appreciated. Pericytes mediate inflammation through leukocyte trafficking and cytokine signaling, respond to pathogen-associated molecular patterns and tissue damage-associated molecular patterns, and may drive vascular inflammation during human SARS-CoV-2 infection. In this review, we highlight the inflammatory phenotype of activated pericytes during organ injury, with an emphasis on novel findings relevant to pulmonary pathophysiology.

Plasma Interleukin-6 Predicts Clinical Decline After Completion of Dexamethasone Therapy in Severe COVID-19.

To identify and characterize clinical decline after completion of dexamethasone in severe COVID-19 and determine whether interleukin (IL)-6 and other inflammatory biomarkers predict the occurrence of clinical decline. DESIGN: Prospective observational cohort. SETTING: ICUs in three University of Washington affiliated hospitals between July 2020 and April 2021. PATIENTS: Patients admitted to an ICU with COVID-19 who completed a course of dexamethasone. MEASUREMENTS AND MAIN RESULTS: We identified 65 adult patients with severe COVID-19 who completed a 10-day course of dexamethasone, of whom 60 had plasma samples collected within 3 days of dexamethasone completion. We measured IL-6 with a clinical-grade electrochemiluminescent assay and a larger panel of inflammatory biomarkers (IL-8, Monocyte Chemoattractant Protein-1, Monocyte Inflammatory Protein-1 alpha, interferon gamma, C-X-C Motif Chemokine Ligand 10, WBC, bicarbonate) with a research immunoassay. We defined clinical decline by the occurrence of incident severe kidney injury, incident or escalating shock or fever, worsening hypoxemia, or death within 5 days of completion of dexamethasone. We estimated risk for clinical decline by standardized log2 transformed biomarker concentration using multivariable logistic regression. Clinical decline post-dexamethasone was common, occurring in 49% of patients (n = 32). Among all biomarkers, IL-6 levels were most strongly associated with clinical decline. After adjustment for age, sex, and study site, the odds of post-dexamethasone clinical decline were 7.33 times higher per one sd increase in log2 transformed IL-6 concentrations (adjusted odds ratio, 7.33; CI, 2.62-20.47; p < 0.001). The discriminatory power of IL-6 for clinical decline was high (cross-validated mean area under the receiver operating characteristic curve, 0.90; 95% CI, 0.79-0.95). CONCLUSIONS: Clinical decline after completion of dexamethasone for severe COVID-19 is common. IL-6 concentrations obtained prior to completion of dexamethasone may have utility in identifying those at highest risk for subsequent worsening. If validated, future work might test whether plasma IL-6 could be used as a tool for a personalized approach to duration of dexamethasone treatment in severe COVID-19.

Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement.

In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing datasets of CXRs from COVID-19+ patients are relatively small, and researchers often pool CXR data from multiple sources, for example, using different x-ray machines in various patient populations under different clinical scenarios. Deep learning models trained on such datasets have been shown to overfit to erroneous features instead of learning pulmonary characteristics in a phenomenon known as shortcut learning. We propose adding feature disentanglement to the training process. This technique forces the models to identify pulmonary features from the images and penalizes them for learning features that can discriminate between the original datasets that the images come from. We find that models trained in this way indeed have better generalization performance on unseen data; in the best case we found that it improved AUC by 0.13 on held out data. We further find that this outperforms masking out non-lung parts of the CXRs and performing histogram equalization, both of which are recently proposed methods for removing biases in CXR datasets.

Presence of Antibodies to Severe Acute Respiratory Syndrome Coronavirus-2 on Admission Is Associated With Decreased Mortality in COVID-19 Critical Illness.

To determine whether the early serologic response in COVID-19 critical illness is associated with hospital mortality. To evaluate if time-to-seroconversion differs by receipt of dexamethasone therapy. DESIGN: Patients were prospectively enrolled within 24 hours of ICU admission from two University of Washington Hospitals. Plasma was collected on enrollment and on days 3, 7, 10, and 14. SETTING: ICUs between March 2020 and April 2021. PATIENTS: Consecutive adults with COVID-19 admitted to an ICU. MEASUREMENTS AND MAIN RESULTS: We measured longitudinal total antispike protein antibody levels (anti-S abs) and total antinucleocapsid antibody levels (anti-N ab) using a U.S. Food and Drug Administration-authorized Roche instrument. We evaluated whether detectable anti-S abs on ICU admission were associated with host factors, initial disease severity, and hospital mortality. We evaluated whether dexamethasone therapy was associated with time-to-seroconversion. Among 93 unvaccinated participants, 47 (51%) had detectable anti-S abs on ICU admission. There was no difference in Acute Physiology and Chronic Health Evaluation II score or time between first positive severe acute respiratory syndrome coronavirus-2 PCR and ICU admission in those with detectable versus undetectable anti-S abs. Adjusting for age, body mass index, and sex, patients with detectable anti-S abs had a lower risk of inhospital death (hazard ratio, 0.40; 95% CI, 0.17-0.94; p = 0.04). Among 21 patients with undetectable anti-S abs on ICU admission and serial measurements available, time-to-seroconversion was not significantly affected by receipt of dexamethasone therapy. CONCLUSIONS: In COVID-19 critical illness, a significant proportion of patients do not have detectable antibodies at ICU admission, and this is independent of severity of illness. Detectable anti-S abs were associated with lower risk of inhospital death. Despite concern that corticosteroids may impair an appropriate antiviral serologic response, early antibody kinetics were not significantly affected by administration of dexamethasone; however, CIs were wide and require further study.

Effective deep learning approaches for predicting COVID-19 outcomes from chest computed tomography volumes.

The rapid evolution of the novel coronavirus disease (COVID-19) pandemic has resulted in an urgent need for effective clinical tools to reduce transmission and manage severe illness. Numerous teams are quickly developing artificial intelligence approaches to these problems, including using deep learning to predict COVID-19 diagnosis and prognosis from chest computed tomography (CT) imaging data. In this work, we assess the value of aggregated chest CT data for COVID-19 prognosis compared to clinical metadata alone. We develop a novel patient-level algorithm to aggregate the chest CT volume into a 2D representation that can be easily integrated with clinical metadata to distinguish COVID-19 pneumonia from chest CT volumes from healthy participants and participants with other viral pneumonia. Furthermore, we present a multitask model for joint segmentation of different classes of pulmonary lesions present in COVID-19 infected lungs that can outperform individual segmentation models for each task. We directly compare this multitask segmentation approach to combining feature-agnostic volumetric CT classification feature maps with clinical metadata for predicting mortality. We show that the combination of features derived from the chest CT volumes improve the AUC performance to 0.80 from the 0.52 obtained by using patients' clinical data alone. These approaches enable the automated extraction of clinically relevant features from chest CT volumes for risk stratification of COVID-19 patients.

Clinical presentation, complications, and outcomes of hospitalized COVID-19 patients in an academic center with a centralized palliative care consult service.

BACKGROUND AND AIMS: Palliative care is a critical component of the response of a healthcare system to a pandemic. We present risk factors associated with mortality and highlight an operational palliative care consult service in facilitating early identification of risk factors to guide goal-concordant care and rational utilization of finite healthcare resources during a pandemic. METHODS: In this case series of 100 consecutive patients hospitalized with COVID-19, we analyzed clinical data, treatment including palliative care, and outcomes in patients with SARS-CoV-2 infection admitted to three hospitals in Seattle, Washington. We compared data between patients who were discharged and non-survivors. RESULTS: Age (OR 4.67 [1.43, 15.32] ages 65-79; OR 3.96 [1.05, 14.89] ages 80-97), dementia (OR 5.62 [1.60, 19.74]), and transfer from a congregate living facility (OR 5.40 [2.07, 14.07]), as well hypoxemia and tachypnea (OR 7.00 [2.91, 22.41]; OR 2.78 [1.11, 6.97]) were associated with mortality. Forty-one (41%) patients required intensive care and 22 (22%) invasive mechanical ventilation. Forty-six (46%) patients were seen by the palliative care service, resulting in a change of resuscitation status in 54% of admitted patients. Fifty-eight (58%) patients recovered and were discharged, 34 (34%) died, and eight (8%) remained hospitalized, of which seven ultimately survived and one died. CONCLUSIONS: Older age, dementia, and congregate living were associated with mortality. Early discussions of goals of care facilitated by an operational palliative care consult service can effectively guide goal-concordant care in patients at high risk for mortality during a pandemic. Development of a functional palliative care consult service is an important component of pandemic planning.

Comparison of Clinical Features and Outcomes in Critically Ill Patients Hospitalized with COVID-19 versus Influenza.

Rationale: No direct comparisons of clinical features, laboratory values, and outcomes between critically ill patients with coronavirus disease (COVID-19) and patients with influenza in the United States have been reported.Objectives: To evaluate the risk of mortality comparing critically ill patients with COVID-19 with patients with seasonal influenza.Methods: We retrospectively identified patients admitted to the intensive care units (ICUs) at two academic medical centers with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or influenza A or B infections between January 1, 2019, and April 15, 2020. The clinical data were obtained by medical record review. All patients except one had follow-up to hospital discharge or death. We used relative risk regression adjusting for age, sex, number of comorbidities, and maximum sequential organ failure scores on Day 1 in the ICU to determine the risk of hospital mortality and organ dysfunction in patients with COVID-19 compared with patients with influenza.Results: We identified 65 critically ill patients with COVID-19 and 74 patients with influenza. The mean (±standard deviation) age in each group was 60.4 ± 15.7 and 56.8 ± 17.6 years, respectively. Patients with COVID-19 were more likely to be male, have a higher body mass index, and have higher rates of chronic kidney disease and diabetes. Of the patients with COVID-19, 37% identified as Hispanic, whereas 10% of the patients with influenza identified as Hispanic. A similar proportion of patients had fevers (∼40%) and lymphopenia (∼80%) on hospital presentation. The rates of acute kidney injury and shock requiring vasopressors were similar between the groups. Although the need for invasive mechanical ventilation was also similar in both groups, patients with COVID-19 had slower improvements in oxygenation, longer durations of mechanical ventilation, and lower rates of extubation than patients with influenza. The hospital mortality was 40% in patients with COVID-19 and 19% in patients with influenza (adjusted relative risk, 2.13; 95% confidence interval, 1.24-3.63; P = 0.006).Conclusions: The need for invasive mechanical ventilation was common in patients in the ICU for COVID-19 and influenza. Compared with those with influenza, patients in the ICU with COVID-19 had worse respiratory outcomes, including longer duration of mechanical ventilation. In addition, patients with COVID-19 were at greater risk for in-hospital mortality, independent of age, sex, comorbidities, and ICU severity of illness.

Comparison of host endothelial, epithelial and inflammatory response in ICU patients with and without COVID-19: a prospective observational cohort study.

BACKGROUND: Analyses of blood biomarkers involved in the host response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral infection can reveal distinct biological pathways and inform development and testing of therapeutics for COVID-19. Our objective was to evaluate host endothelial, epithelial and inflammatory biomarkers in COVID-19. METHODS: We prospectively enrolled 171 ICU patients, including 78 (46%) patients positive and 93 (54%) negative for SARS-CoV-2 infection from April to September, 2020. We compared 22 plasma biomarkers in blood collected within 24 h and 3 days after ICU admission. RESULTS: In critically ill COVID-19 and non-COVID-19 patients, the most common ICU admission diagnoses were respiratory failure or pneumonia, followed by sepsis and other diagnoses. Similar proportions of patients in both groups received invasive mechanical ventilation at the time of study enrollment. COVID-19 and non-COVID-19 patients had similar rates of acute respiratory distress syndrome, severe acute kidney injury, and in-hospital mortality. While concentrations of interleukin 6 and 8 were not different between groups, markers of epithelial cell injury (soluble receptor for advanced glycation end products, sRAGE) and acute phase proteins (serum amyloid A, SAA) were significantly higher in COVID-19 compared to non-COVID-19, adjusting for demographics and APACHE III scores. In contrast, angiopoietin 2:1 (Ang-2:1 ratio) and soluble tumor necrosis factor receptor 1 (sTNFR-1), markers of endothelial dysfunction and inflammation, were significantly lower in COVID-19 (p < 0.002). Ang-2:1 ratio and SAA were associated with mortality only in non-COVID-19 patients. CONCLUSIONS: These studies demonstrate that, unlike other well-studied causes of critical illness, endothelial dysfunction may not be characteristic of severe COVID-19 early after ICU admission. Pathways resulting in elaboration of acute phase proteins and inducing epithelial cell injury may be promising targets for therapeutics in COVID-19.