Association between emergency department disposition and mortality in patients with COVID-19 acute respiratory distress syndrome.

Objectives: Patients hospitalized for COVID-19 frequently develop hypoxemia and acute respiratory distress syndrome (ARDS) after admission. In non-COVID-19 ARDS studies, admission to hospital wards with subsequent transfer to intensive care unit (ICU) is associated with worse outcomes. We hypothesized that initial admission to the ward may affect outcomes in patient with COVID-19 ARDS. Methods: This was a retrospective study of consecutive adults admitted for COVID-19 ARDS between March 2020 and March 2021 at Stanford Health Care. Mortality scores at hospital admission (Coronavirus Clinical Characterization Consortium Mortality Score [4C score]) and ICU admission (Simplified Acute Physiology Score III [SAPS-III]) were calculated, as well as ROX index for patients on high flow nasal oxygen. Patients were classified by emergency department (ED) disposition (ward-first vs. ICU-direct), and 28- and 60-day mortality and highest level of respiratory support within 1 day of ICU admission were compared. A second cohort (April 2021‒July 2022, n = 129) was phenotyped to validate mortality outcome. Results: A total of 157 patients were included, 48% of whom were first admitted to the ward (n = 75). Ward-first patients had more comorbidities, including lung disease. Ward-first patients had lower 4C and similar SAPS-III score, yet increased mortality at 28 days (32% vs. 17%, hazard ratio [HR] 2.0, 95% confidence interval [95% CI] 1.0‒3.7, p = 0.039) and 60 days (39% vs. 23%, HR 1.83, 95% CI 1.04‒3.22, p = 0.037) compared to ICU-direct patients. More ward-first patients escalated to mechanical ventilation on day 1 of ICU admission (36% vs. 14%, p = 0.002) despite similar ROX index. Ward-first patients who upgraded to ICU within 48 h of ED presentation had the highest mortality. Mortality findings were replicated in a sensitivity analysis. Conclusion: Despite similar baseline risk scores, ward-first patients with COVID-19 ARDS had increased mortality and escalation to mechanical ventilation compared to ICU-direct patients. Ward-first patients requiring ICU upgrade within 48 h were at highest risk, highlighting a need for improved identification of this group at ED admission.

Right Ventricular Dysfunction Patterns among Patients with COVID-19 in the Intensive Care Unit: A Retrospective Cohort Analysis.

Rationale: Right ventricular (RV) dysfunction is common among patients hospitalized with coronavirus disease (COVID-19); however, its epidemiology may depend on the echocardiographic parameters used to define it. Objectives: To evaluate the prevalence of abnormalities in three common echocardiographic parameters of RV function among patients with COVID-19 admitted to the intensive care unit (ICU), as well as the effect of RV dilatation on differential parameter abnormality and the association of RV dysfunction with 60-day mortality. Methods: We conducted a retrospective cohort study of ICU patients with COVID-19 between March 4, 2020, and March 4, 2021, who received a transthoracic echocardiogram within 48 hours before to at most 7 days after ICU admission. RV dysfunction and dilatation, respectively, were defined by guideline thresholds for tricuspid annular plane systolic excursion (TAPSE), RV fractional area change, RV free wall longitudinal strain (RVFWS), and RV basal dimension or RV end-diastolic area. Association of RV dysfunction with 60-day mortality was assessed through logistic regression adjusting for age, prior history of congestive heart failure, invasive ventilation at the time of transthoracic echocardiogram, and Acute Physiology and Chronic Health Evaluation II score. Results: A total of 116 patients were included, of whom 69% had RV dysfunction by one or more parameters, and 36.3% of these had RV dilatation. The three most common patterns of RV dysfunction were the presence of three abnormalities, the combination of abnormal RVFWS and TAPSE, and isolated TAPSE abnormality. Patients with RV dilatation had worse RV fractional area change (24% vs. 36%; P = 0.001), worse RVFWS (16.3% vs. 19.1%; P = 0.005), higher RV systolic pressure (45 mm Hg vs. 31 mm Hg; P = 0.001) but similar TAPSE (13 mm vs. 13 mm; P = 0.30) compared with those with normal RV size. After multivariable adjustment, 60-day mortality was significantly associated with RV dysfunction (odds ratio, 2.91; 95% confidence interval, 1.01-9.44), as was the presence of at least two parameter abnormalities. Conclusions: ICU patients with COVID-19 had significant heterogeneity in RV function abnormalities present with different patterns associated with RV dilatation. RV dysfunction by any parameter was associated with increased mortality. Therefore, a multiparameter evaluation may be critical in recognizing RV dysfunction in COVID-19.

Autoantibodies are highly prevalent in non-SARS-CoV-2 respiratory infections and critical illness.

The widespread presence of autoantibodies in acute infection with SARS-CoV-2 is increasingly recognized, but the prevalence of autoantibodies in non-SARS-CoV-2 infections and critical illness has not yet been reported. We profiled IgG autoantibodies in 267 patients from 5 independent cohorts with non-SARS-CoV-2 viral, bacterial, and noninfectious critical illness. Serum samples were screened using Luminex arrays that included 58 cytokines and 55 autoantigens, many of which are associated with connective tissue diseases (CTDs). Samples positive for anti-cytokine antibodies were tested for receptor blocking activity using cell-based functional assays. Anti-cytokine antibodies were identified in > 50% of patients across all 5 acutely ill cohorts. In critically ill patients, anti-cytokine antibodies were far more common in infected versus uninfected patients. In cell-based functional assays, 11 of 39 samples positive for select anti-cytokine antibodies displayed receptor blocking activity against surface receptors for Type I IFN, GM-CSF, and IL-6. Autoantibodies against CTD-associated autoantigens were also commonly observed, including newly detected antibodies that emerged in longitudinal samples. These findings demonstrate that anti-cytokine and autoantibodies are common across different viral and nonviral infections and range in severity of illness.

Autoantibodies targeting cytokines and connective tissue disease autoantigens are common in acute non-SARS-CoV-2 infections.

The widespread presence of autoantibodies in acute infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is increasingly recognized, but the prevalence of autoantibodies in infections with organisms other than SARS-CoV-2 has not yet been reported. We used protein arrays to profile IgG autoantibodies from 317 samples from 268 patients across a spectrum of non-SARS-CoV-2 infections, many of whom were critically ill with pneumonia. Anti-cytokine antibodies (ACA) were identified in > 50% of patients infected with non-SARS-CoV-2 viruses and other pathogens, including patients with pneumonia attributed to bacterial causes. In cell-based functional assays, some ACA blocked binding to surface receptors for type I interferons (Type I IFN), granulocyte-macrophage colony-stimulating factor (GM-CSF), and interleukin-6 (IL-6). Autoantibodies against traditional autoantigens associated with connective tissue diseases (CTDs) were also commonly observed in these cohorts, including newly-detected antibodies that emerged in longitudinal samples from patients infected with influenza. We conclude that autoantibodies, some of which are functionally active, may be much more prevalent than previously appreciated in patients who are symptomatically infected with diverse pathogens.

Deconvoluting complex correlates of COVID-19 severity with a multi-omic pandemic tracking strategy.

The SARS-CoV-2 pandemic has differentially impacted populations across race and ethnicity. A multi-omic approach represents a powerful tool to examine risk across multi-ancestry genomes. We leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from nasopharyngeal swabs of 1049 individuals (736 SARS-CoV-2 positive and 313 SARS-CoV-2 negative) and integrate them with digital phenotypes from electronic health records from a diverse catchment area in Northern California. Genome-wide association disaggregated by admixture mapping reveals novel COVID-19-severity-associated regions containing previously reported markers of neurologic, pulmonary and viral disease susceptibility. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. Summary data from multiomic investigation reveals metagenomic and HLA associations with severe COVID-19. The wealth of data available from residual nasopharyngeal swabs in combination with clinical data abstracted automatically at scale highlights a powerful strategy for pandemic tracking, and reveals distinct epidemiologic, genetic, and biological associations for those at the highest risk.

Prospective validation of an 11-gene mRNA host response score for mortality risk stratification in the intensive care unit.

Several clinical calculators predict intensive care unit (ICU) mortality, however these are cumbersome and often require 24 h of data to calculate. Retrospective studies have demonstrated the utility of whole blood transcriptomic analysis in predicting mortality. In this study, we tested prospective validation of an 11-gene messenger RNA (mRNA) score in an ICU population. Whole blood mRNA from 70 subjects in the Stanford ICU Biobank with samples collected within 24 h of Emergency Department presentation were used to calculate an 11-gene mRNA score. We found that the 11-gene score was highly associated with 60-day mortality, with an area under the receiver operating characteristic curve of 0.68 in all patients, 0.77 in shock patients, and 0.98 in patients whose primary determinant of prognosis was acute illness. Subjects with the highest quartile of mRNA scores were more likely to die in hospital (40% vs 7%, p < 0.01) and within 60 days (40% vs 15%, p = 0.06). The 11-gene score improved prognostication with a categorical Net Reclassification Improvement index of 0.37 (p = 0.03) and an Integrated Discrimination Improvement index of 0.07 (p = 0.02) when combined with Simplified Acute Physiology Score 3 or Acute Physiology and Chronic Health Evaluation II score. The test performed poorly in the 95 independent samples collected > 24 h after emergency department presentation. Tests will target a 30-min turnaround time, allowing for rapid results early in admission. Moving forward, this test may provide valuable real-time prognostic information to improve triage decisions and allow for enrichment of clinical trials.

Cytokine profile in plasma of severe COVID-19 does not differ from ARDS and sepsis.

BACKGROUNDElevated levels of inflammatory cytokines have been associated with poor outcomes among COVID-19 patients. It is unknown, however, how these levels compare with those observed in critically ill patients with acute respiratory distress syndrome (ARDS) or sepsis due to other causes.METHODSWe used a Luminex assay to determine expression of 76 cytokines from plasma of hospitalized COVID-19 patients and banked plasma samples from ARDS and sepsis patients. Our analysis focused on detecting statistical differences in levels of 6 cytokines associated with cytokine storm (IL-1ß, IL-1RA, IL-6, IL-8, IL-18, and TNF-α) between patients with moderate COVID-19, severe COVID-19, and ARDS or sepsis.RESULTSFifteen hospitalized COVID-19 patients, 9 of whom were critically ill, were compared with critically ill patients with ARDS (n = 12) or sepsis (n = 16). There were no statistically significant differences in baseline levels of IL-1ß, IL-1RA, IL-6, IL-8, IL-18, and TNF-α between patients with COVID-19 and critically ill controls with ARDS or sepsis.CONCLUSIONLevels of inflammatory cytokines were not higher in severe COVID-19 patients than in moderate COVID-19 or critically ill patients with ARDS or sepsis in this small cohort. Broad use of immunosuppressive therapies in ARDS has failed in numerous Phase 3 studies; use of these therapies in unselected patients with COVID-19 may be unwarranted.FUNDINGFunding was received from NHLBI K23 HL125663 (AJR); The Bill and Melinda Gates Foundation OPP1113682 (AJR and CAB); Burroughs Wellcome Fund Investigators in the Pathogenesis of Infectious Diseases #1016687 NIH/NIAID U19AI057229-16; Stanford Maternal Child Health Research Institute; and Chan Zuckerberg Biohub (CAB).

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.

Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce antibiotic overuse, and lower healthcare costs. Here, we develop a generalizable host-gene-expression-based classifier for acute bacterial and viral infections. We use training data (N = 1069) from 18 retrospective transcriptomic studies. Using only 29 preselected host mRNAs, we train a neural-network classifier with a bacterial-vs-other area under the receiver-operating characteristic curve (AUROC) 0.92 (95% CI 0.90-0.93) and a viral-vs-other AUROC 0.92 (95% CI 0.90-0.93). We then apply this classifier, inflammatix-bacterial-viral-noninfected-version 1 (IMX-BVN-1), without retraining, to an independent cohort (N = 163). In this cohort, IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.86 (95% CI 0.77-0.93), and viral-vs.-other 0.85 (95% CI 0.76-0.93). In patients enrolled within 36 h of hospital admission (N = 70), IMX-BVN-1 AUROCs are: bacterial-vs.-other 0.92 (95% CI 0.83-0.99), and viral-vs.-other 0.91 (95% CI 0.82-0.98). With further study, IMX-BVN-1 could provide a tool for assessing patients with suspected infection and sepsis at hospital admission.

A single-cell atlas of the peripheral immune response in patients with severe COVID-19.

There is an urgent need to better understand the pathophysiology of Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2, which has infected more than three million people worldwide1. Approximately 20% of patients with COVID-19 develop severe disease and 5% of patients require intensive care2. Severe disease has been associated with changes in peripheral immune activity, including increased levels of pro-inflammatory cytokines3,4 that may be produced by a subset of inflammatory monocytes5,6, lymphopenia7,8 and T cell exhaustion9,10. To elucidate pathways in peripheral immune cells that might lead to immunopathology or protective immunity in severe COVID-19, we applied single-cell RNA sequencing (scRNA-seq) to profile peripheral blood mononuclear cells (PBMCs) from seven patients hospitalized for COVID-19, four of whom had acute respiratory distress syndrome, and six healthy controls. We identify reconfiguration of peripheral immune cell phenotype in COVID-19, including a heterogeneous interferon-stimulated gene signature, HLA class II downregulation and a developing neutrophil population that appears closely related to plasmablasts appearing in patients with acute respiratory failure requiring mechanical ventilation. Importantly, we found that peripheral monocytes and lymphocytes do not express substantial amounts of pro-inflammatory cytokines. Collectively, we provide a cell atlas of the peripheral immune response to severe COVID-19.

A single-cell atlas of the peripheral immune response to severe COVID-19.

There is an urgent need to better understand the pathophysiology of Coronavirus disease 2019 (COVID-19), the global pandemic caused by SARS-CoV-2. Here, we apply single-cell RNA sequencing (scRNA-seq) to peripheral blood mononuclear cells (PBMCs) of 7 patients hospitalized with confirmed COVID-19 and 6 healthy controls. We identify substantial reconfiguration of peripheral immune cell phenotype in COVID-19, including a heterogeneous interferon-stimulated gene (ISG) signature, HLA class II downregulation, and a novel B cell-derived granulocyte population appearing in patients with acute respiratory failure requiring mechanical ventilation. Importantly, peripheral monocytes and lymphocytes do not express substantial amounts of pro-inflammatory cytokines, suggesting that circulating leukocytes do not significantly contribute to the potential COVID-19 cytokine storm. Collectively, we provide the most thorough cell atlas to date of the peripheral immune response to severe COVID-19.