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ObjectiveThe clinical utility of point-of-care lung ultrasound (LUS) for disease severity triage of hospitalized patients with COVID-19 is unclear. DesignProspective cohort study SettingA large tertiary care center in Maryland, USA between April 2020 to September 2021. PatientsHospitalized adults ([≥]18 years of age) with positive SARS-CoV-2 RT-PCR results. InterventionsNone. Measurements and Main ResultsAll patients were scanned using a standardized protocol including 12 lung zones and followed to determine clinical outcomes until hospital discharge and vital status at 28-days. Ultrasounds were independently reviewed for lung and pleural line artifacts and abnormalities, and the mean Lung Ultrasound Score (ranging from 0 to 3) across lung zones (mLUSS) was determined. The primary outcome was time to ICU-level care, defined as high flow oxygen, noninvasive, or mechanical ventilation, within 28-days of the initial ultrasound. Cox proportional hazards regression models adjusted for age and sex were fit for mLUSS and each ultrasound covariate. A total of 264 participants were enrolled in the study; the median age was 59 years and 114 (43.2) % of participants were female. The median mLUSS was 1 (interquartile range: 0.5 to 1.3). Following enrollment, 29 (11.0%) participants went on to require ICU-level care and 14 (5.3%) subsequently died by 28 days. Each increase in mLUSS at enrollment was associated with disease progression to ICU-level care (aHR = 3.63; 95% CI: 1.23 to 10.65) and 28-day mortality (aHR = 4.50; 95% CI: 1.52 to 13.31). Pleural line abnormalities were independently associated with disease progression to ICU-level care (aHR = 18.86; CI: 1.57 to 226.09). ConclusionsParticipants with a mLUSS [≥]1 or pleural line changes on LUS had an increased likelihood of subsequent requirement of high flow oxygen or greater. LUS is a promising tool for assessing risk of COVID-19 progression at the bedside.
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BackgroundSeveral inflammatory cytokines are upregulated in severe COVID-19. We compared cytokines in COVID-19 versus influenza in order to define differentiating features of the inflammatory response to these pathogens and their association with severe disease. Because elevated body mass index (BMI) is a known risk factor for severe COVID-19, we examined the relationship of BMI to cytokines associated with severe disease. MethodsThirty-seven cytokines and chemokines were measured in plasma from 145 patients with COVID-19, 57 patients with influenza, and 30 healthy controls. Controlling for BMI, age, and sex, differences in cytokines between groups were determined by linear regression and random forest prediction was utilized to determine the cytokines most important in distinguishing severe COVID-19 and influenza. Mediation analysis was utilized to identify cytokines that mediate the effect of BMI on disease severity. ResultsIL-18, IL-1{beta}, IL-6, and TNF- were significantly increased in COVID-19 versus influenza patients while GM-CSF, IFN-{gamma}, IFN-{lambda}1, IL-10, IL-15, and MCP-2 were significantly elevated in the influenza group. In subgroup analysis based on disease severity, IL-18, IL-6, and TNF- were elevated in severe COVID-19, but not severe influenza. Random forest analysis identified high IL-6 and low IFN-{lambda}1 levels as the most distinct between severe COVID-19 and severe influenza. Finally, IL-1RA was identified as a potential mediator of the effects of BMI on COVID-19 severity. ConclusionsThese findings point to activation of fundamentally different innate immune pathways in SARS-CoV-2 and influenza infection, and emphasize drivers of severe COVID-19 to focus both mechanistic and therapeutic investigations. SummarySevere COVID-19 is marked by dysregulated inflammation and is associated with elevated BMI. By comparing cytokines and chemokines in patients with either COVID-19 or influenza, we identified distinct inflammatory pathways and a cytokine mediator of the effect of BMI.
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SARS-CoV-2 infection induces severe disease in a subpopulation of patients, but the underlying mechanisms remain unclear. We demonstrate robust IgM autoantibodies that recognize angiotensin converting enzyme-2 (ACE2) in 18/66 (27%) patients with severe COVID-19, which are rare (2/52; 3.8%) in hospitalized patients who are not ventilated. The antibodies do not undergo class-switching to IgG, suggesting a T-independent antibody response. Purified IgM from anti-ACE2 patients activates complement. Pathological analysis of lung obtained at autopsy shows endothelial cell staining for IgM in blood vessels in some patients. We propose that vascular endothelial ACE2 expression focuses the pathogenic effects of these autoantibodies on blood vessels, and contributes to the angiocentric pathology observed in some severe COVID-19 patients. These findings may have predictive and therapeutic implications. One-sentence summaryACE2 autoantibodies in severe COVID-19 have features of a T-independent immune response, and may mediate vascular damage.
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It remains unclear why some patients infected with SARS-CoV-2 readily resolve infection while others develop severe disease. To address this question, we employed a novel assay to interrogate immune-metabolic programs of T cells and myeloid cells in severe and recovered COVID-19 patients. Using this approach, we identified a unique population of T cells expressing high H3K27me3 and the mitochondrial membrane protein voltage-dependent anion channel (VDAC), which were expanded in acutely ill COVID-19 patients and distinct from T cells found in patients infected with hepatitis c or influenza and in recovered COVID-19. Increased VDAC was associated with gene programs linked to mitochondrial dysfunction and apoptosis. High-resolution fluorescence and electron microscopy imaging of the cells revealed dysmorphic mitochondria and release of cytochrome c into the cytoplasm, indicative of apoptosis activation. The percentage of these cells was markedly increased in elderly patients and correlated with lymphopenia. Importantly, T cell apoptosis could be inhibited in vitro by targeting the oligomerization of VDAC or blocking caspase activity. In addition to these T cell findings, we also observed a robust population of Hexokinase II+ polymorphonuclear-myeloid derived suppressor cells (PMN-MDSC), exclusively found in the acutely ill COVID-19 patients and not the other viral diseases. Finally, we revealed a unique population of monocytic MDSC (M-MDSC) expressing high levels of carnitine palmitoyltransferase 1a (CPT1a) and VDAC. The metabolic phenotype of these cells was not only highly specific to COVID-19 patients but the presence of these cells was able to distinguish severe from mild disease. Overall, the identification of these novel metabolic phenotypes not only provides insight into the dysfunctional immune response in acutely ill COVID-19 patients but also provide a means to predict and track disease severity as well as an opportunity to design and evaluate novel metabolic therapeutic regimens. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/20186064v2_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@89f509org.highwire.dtl.DTLVardef@1362640org.highwire.dtl.DTLVardef@940aeorg.highwire.dtl.DTLVardef@175792b_HPS_FORMAT_FIGEXP M_FIG C_FIG
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BackgroundOutpatient COVID-19 has been insufficiently characterized. ObjectiveTo determine the progression of disease and subsequent determinants of hospitalization. DesignA prospective outpatient cohort. SettingOutpatients were recruited by phone between April 21 to June 23, 2020 after receiving outpatient or emergency department testing within a large health network in Maryland, USA. ParticipantsOutpatient adults with positive RT-PCR results for SARS-CoV-2. MeasurementsSymptoms, portable pulse oximeter oxygen saturation (SaO2), heart rate, and temperature were collected by participants on days 0, 3, 7, 14, 21, and 28 after enrollment. Baseline demographics, comorbid conditions were evaluated for risk of subsequent hospitalization using negative binomial, logistic, and random effects logistic regression. ResultsAmong 118 SARS-CoV-2 infected outpatients, the median age was 56.0 years (IQR, 50.0 to 63.0) and 50 (42.4%) were male. Among those reporting active symptoms, the most common symptoms during the first week since symptom onset included weakness/fatigue (67.3%), cough (58.0%), headache (43.8%), and sore throat (34.8%). Participants returned to their usual health a median of 20 days (IQR, 13 to 38) from the symptom onset, and only 65.5% of respondents were at their usual health during the fourth week of illness. Over 28 days, 10.9% presented to the emergency department and 7.6% required hospitalization. Individuals at the same duration of illness had a 6.1 times increased adjusted odds of subsequent hospitalization per every percent decrease in home SaO2 (95% confidence interval [CI]: 1.41 to 31.23, p=0.02). LimitationsSeverity and duration of illness may differ in a younger population. ConclusionSymptoms often persisted but uncommonly progressed to hospitalization. Home SaO2 might be an important adjunctive tool to identify progression of COVID-19. RegistrationClinicaltrials.gov NCT number: NCT04496466 Funding SourceThe Sherrilyn and Ken Fisher Center for Environmental Infectious Diseases Discovery Program and the Johns Hopkins University School of Medicine
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BackgroundThe early COVID-19 pandemic has been characterized by rapid global spread. In the United States National Capital Region, over 2,000 cases were reported within three weeks of its first detection in March 2020. We aimed to use genomic sequencing to understand the initial spread of SARS-CoV-2, the virus that causes COVID-19, in the region. By correlating genetic information to disease phenotype, we also aimed to gain insight into any correlation between viral genotype and case severity or transmissibility. MethodsWe performed whole genome sequencing of clinical SARS-CoV-2 samples collected in March 2020 by the Johns Hopkins Health System. We analyzed these regional SARS-CoV-2 genomes alongside detailed clinical metadata and the global phylogeny to understand early establishment of the virus within the region. ResultsWe analyzed 620 samples from the Johns Hopkins Health System collected between March 11-31, 2020, comprising 37.3% of the total cases in Maryland during this period. We selected 143 of these samples for sequencing, generating 114 complete viral genomes. These genomes belong to all five major Nextstrain-defined clades, suggesting multiple introductions into the region and underscoring the diversity of the regional epidemic. We also found that clinically severe cases had genomes belonging to all of these clades. ConclusionsWe established a pipeline for SARS-CoV-2 sequencing within the Johns Hopkins Health system, which enabled us to capture the significant viral diversity present in the region as early as March 2020. Efforts to control local spread of the virus were likely confounded by the number of introductions into the region early in the epidemic and interconnectedness of the region as a whole.