Point-of-care lung ultrasound predicts severe disease and death due to COVID-19: a prospective cohort study.

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.

A Targeted Geospatial Approach to COVID-19 Vaccine Delivery: Findings from the Johns Hopkins Hospital Emergency Department

While COVID-19 vaccines have been shown to significantly decrease morbidity and mortality, there is still much debate about optimal strategies of vaccine rollout. We tested identity-unlinked stored remnant blood specimens of patients at least 18 years presenting to the Johns Hopkins Hospital emergency department (ED) between May to November 2020 for IgG to SARS-CoV-2. Data on SARS-CoV-2 RT PCR were available for patients who were tested due to suspected infection. SARS-CoV-2 infections was defined as either a positive IgG and/or RT-PCR. SARS-CoV-2 infection clustering by zipcode was analyzed by spatial analysis using the Bernoulli model (SaTScan software, Version 9.7). Median age of the 7,461 unique patients visiting the ED was 47 years and 50.8% were female; overall, 740 (9.9%) unique patients had evidence of SARS-CoV-2 infection. Prevalence of infection in ED patients by ZIP code ranged from 4.1% to 22.3%. The observed number of cases in ZIP code C was nearly double the expected (observed/expected ratio = 1.99; 95% CI: 1.62, 2.42). These data suggest a targeted geospatial approach to COVID vaccination should be considered to maximize vaccine rollout efficiency and include high-risk populations that may otherwise be subjected to delays, or missed.

Differential Cytokine Signatures of SARS-CoV-2 and Influenza Infection Highlight Key Differences in Pathobiology

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.

Evaluation of Serological SARS-CoV-2 Lateral Flow Assays for Rapid Point of Care Testing

BackgroundRapid point-of-care tests (POCTs) for SARS-CoV-2-specific antibodies vary in performance. A critical need exists to perform head-to-head comparison of these assays. MethodsPerformance of fifteen different lateral flow POCTs for the detection of SARS-CoV-2-specific antibodies was performed on a well characterized set of 100 samples. Of these, 40 samples from known SARS-CoV-2-infected, convalescent individuals (average of 45 days post symptom onset) were used to assess sensitivity. Sixty samples from the pre-pandemic era (negative control), that were known to have been infected with other respiratory viruses (rhinoviruses A, B, C and/or coronavirus 229E, HKU1, NL63 OC43) were used to assess specificity. The timing of seroconversion was assessed on five POCTs on a panel of 272 longitudinal samples from 47 patients of known time since symptom onset. ResultsFor the assays that were evaluated, the sensitivity and specificity for any reactive band ranged from 55%-97% and 78%-100%, respectively. When assessing the performance of the IgM and the IgG bands alone, sensitivity and specificity ranged from 0%-88% and 80%-100% for IgM and 25%-95% and 90%-100% for IgG. Longitudinal testing revealed that median time post symptom onset to a positive result was 7 days (IQR 5.4, 9.8) for IgM and 8.2 days (IQR 6.3 to 11.3). ConclusionThe testing performance varied widely among POCTs with most variation related to the sensitivity of the assays. The IgM band was most likely to misclassify pre-pandemic samples. The appearance of IgM and IgG bands occurred almost simultaneously.