Additive value of lung ultrasound to clinical parameters for prognosticating COVID-19.

The inclusion of LUS with simple, point-of-care clinical parameters have potential to improve COVID-19 prognostication above that from standard clinical care delivery. https://bit.ly/3InePYK.

Do worsening lung ultrasound scans identify severe COVID-19 trajectories?

Background: While point-of-care ultrasound (POCUS) has been used to track worsening COVID-19 disease it is unclear if there are dynamic differences between severity trajectories. Methods: We studied 12-lung zone protocol scans from 244 participants [with repeat scans obtained in 3 days (N = 114), 7 days (N = 53), and weekly (N = 9)] ≥ 18 years of age hospitalized for COVID-19 pneumonia. Differences in mean lung ultrasound (LUS) scores and percent of lung fields with A-lines over time were compared between peak severity levels (as defined by the WHO clinical progression scale) using linear mixed-effects models. Results: Mean LUS scores were elevated by 0.19 (p = 0.035) and A-lines were present in 14.7% fewer lung fields (p = 0.02) among those with ICU-level or fatal peak illness compared to less severe hospitalized illness, regardless of duration of illness. There were no differences between severity groups in the trajectories of mean LUS score 0.19 (p = 0.66) or percent A-lines (p = 0.40). Discussion: Our results do not support the use of serial LUS scans to monitor COVID-19 disease progression among hospitalized adults.

Point-of-Care Lung Ultrasound Predicts Severe Disease and Death Due to COVID-19: A Prospective Cohort Study.

The clinical utility of point-of-care lung ultrasound (LUS) among hospitalized patients with COVID-19 is unclear. DESIGN: Prospective cohort study. SETTING: A large tertiary care center in Maryland, between April 2020 and September 2021. PATIENTS: Hospitalized adults (≥ 18 yr old) with positive severe acute respiratory syndrome coronavirus 2 reverse transcriptase-polymerase chain reaction results. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All 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 LUS Score (mLUSS) (ranging from 0 to 3) across lung zones was determined. The primary outcome was time to ICU-level care, defined as high-flow oxygen, noninvasive, or invasive 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 61 years and 114 participants (43.2%) were female. The median mLUSS was 1.0 (interquartile range, 0.5-1.3). Following enrollment, 27 participants (10.0%) 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 (adjusted hazard ratio [aHR], 3.61; 95% CI, 1.27-10.2) and 28-day mortality (aHR, 3.10; 95% CI, 1.29-7.50). Pleural line abnormalities were independently associated with disease progression to death (aHR, 20.93; CI, 3.33-131.30). CONCLUSIONS: Participants with a mLUSS greater than or equal to 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.

Optimizing Highly Infectious Disease Isolation Unit Management: Experiences From the Infectious Diseases Isolation and Research Unit, Fort Portal, Uganda.

Infectious disease outbreaks on the scale of the current coronavirus disease 2019 (COVID-19) pandemic are a new phenomenon in many parts of the world. Many isolation unit designs with corresponding workflow dynamics and personal protective equipment postures have been proposed for each emerging disease at the health facility level, depending on the mode of transmission. However, personnel and resource management at the isolation units for a resilient response will vary by human resource capacity, reporting requirements, and practice setting. This study describes an approach to isolation unit management at a rural Uganda Hospital and shares lessons from the Uganda experience for isolation unit managers in low- and middle-income settings.

Distinct blood inflammatory biomarker clusters stratify host phenotypes during the middle phase of COVID-19.

The associations between clinical phenotypes of coronavirus disease 2019 (COVID-19) and the host inflammatory response during the transition from peak illness to convalescence are not yet well understood. Blood plasma samples were collected from 129 adult SARS-CoV-2 positive inpatient and outpatient participants between April 2020 and January 2021, in a multi-center prospective cohort study at 8 military hospitals across the United States. Plasma inflammatory protein biomarkers were measured in samples from 15 to 28 days post symptom onset. Topological Data Analysis (TDA) was used to identify patterns of inflammation, and associations with peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated using logistic regression. The study population (n = 129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct inflammatory biomarker clusters were identified and were associated with significant differences in peak disease severity (p < 0.001), age (p < 0.001), BMI (p < 0.001), and CCI (p = 0.001). Host-biomarker profiles stratified a heterogeneous population of COVID-19 patients during the transition from peak illness to convalescence, and these distinct inflammatory patterns were associated with comorbid disease and severe illness due to COVID-19.

Do worsening lung ultrasound scans identify severe COVID-19 trajectories?

Background While point-of-care ultrasound (POCUS) has been used to track worsening COVID-19 disease it is unclear if there are dynamic differences between severity trajectories. Methods We studied 12-lung zone protocol scans from 244 participants [with repeat scans obtained in 3 days (N = 114), 7 days (N = 53), and weekly (N = 9)] ≥ 18 years of age hospitalized for COVID-19 pneumonia. Differences in mean lung ultrasound (LUS) scores and percent of lung fields with A-lines over time were compared between peak severity levels (as defined by the WHO clinical progression scale) using linear mixed-effects models. Results Mean LUS scores were elevated by 0.19 (p = 0.035) and A-lines were present in 14.7% fewer lung fields (p = 0.02) among those with ICU-level or fatal peak illness compared to less severe hospitalized illness, regardless of duration of illness. There were no differences between severity groups in the trajectories of mean LUS score 0.19 (p = 0.66) or percent A-lines (p = 0.40). Discussion Our results do not support the use of serial LUS scans to monitor COVID-19 disease progression among hospitalized adults.

Strengthened belief in vaccine effectiveness predicted increased COVID-19 vaccination intention and behaviour: Results from a nationally representative longitudinal survey of U.S. adults from July 2020 to April/May 2021.

Vaccine hesitancy remains a major barrier to ending the COVID-19 pandemic in the United States (U.S.) and an important target for communication interventions. Using longitudinal survey data, we examined whether baseline levels and changes in beliefs about the COVID-19 vaccines predicted change in vaccination intention/behaviour. Repeated measures were collected from a nationally representative sample of U.S. adults (n = 665) in July 2020 and April/June 2021. Linear regressions associated change in COVID-19 vaccination intention/behaviour with changes in beliefs about the COVID-19 vaccines' safety, effectiveness in protecting others from infection, and effectiveness in protecting oneself from infection. Changes in beliefs from T1 to T2 were significantly associated with change in vaccination outcomes for all belief types (safety B = 0.39, SE = 0.07; effectiveness for self B = 0.38, SE = 0.09; effectiveness for others B = 0.43, SE = 0.07). Cross-lagged models suggested a reciprocal causal relationship between pro-vaccine beliefs and vaccination intention/behaviour: Intention to get vaccinated at T1 predicted strengthened safety and effectiveness beliefs at T2. T1 effectiveness beliefs predicted T2 vaccination intention/behaviour, though T1 safety beliefs did not. Communication interventions highlighting the protective benefits of COVID-19 vaccines may be particularly successful in reducing vaccine hesitancy.

Point-of-Care Lung Ultrasound Predicts Severe Disease and Death Due to COVID-19: A Prospective Cohort Study

OBJECTIVES: The clinical utility of point-of-care lung ultrasound (LUS) among hospitalized patients with COVID-19 is unclear. DESIGN: Prospective cohort study. SETTING: A large tertiary care center in Maryland, between April 2020 and September 2021. PATIENTS: Hospitalized adults (≥ 18 yr old) with positive severe acute respiratory syndrome coronavirus 2 reverse transcriptase-polymerase chain reaction results. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: All 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 LUS Score (mLUSS) (ranging from 0 to 3) across lung zones was determined. The primary outcome was time to ICU-level care, defined as high-flow oxygen, noninvasive, or invasive 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 61 years and 114 participants (43.2%) were female. The median mLUSS was 1.0 (interquartile range, 0.5–1.3). Following enrollment, 27 participants (10.0%) 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 (adjusted hazard ratio [aHR], 3.61;95% CI, 1.27–10.2) and 28-day mortality (aHR, 3.10;95% CI, 1.29–7.50). Pleural line abnormalities were independently associated with disease progression to death (aHR, 20.93;CI, 3.33–131.30). CONCLUSIONS: Participants with a mLUSS greater than or equal to 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.

Assessing the use of a micro-sampling device for measuring blood protein levels in healthy subjects and COVID-19 patients.

BACKGROUND: Venous phlebotomy performed by trained personnel is critical for patient diagnosis and monitoring of chronic disease, but has limitations in resource-constrained settings, and represents an infection control challenge during outbreaks. Self-collection devices have the potential to shift phlebotomy closer to the point of care, supporting telemedicine strategies and virtual clinical trials. Here we assess a capillary blood micro-sampling device, the Tasso Serum Separator Tube (SST), for measuring blood protein levels in healthy subjects and non-hospitalized COVID-19 patients. METHODS: 57 healthy controls and 56 participants with mild/moderate COVID-19 were recruited at two U.S. military healthcare facilities. Healthy controls donated Tasso SST capillary serum, venous plasma and venous serum samples at multiple time points, while COVID-19 patients donated a single Tasso SST serum sample at enrolment. Concentrations of 17 protein inflammatory biomarkers were measured in all biospecimens by Ella multi-analyte immune-assay. RESULTS: Tasso SST serum protein measurements in healthy control subjects were highly reproducible, but their agreements with matched venous samples varied. Most of the selected proteins, including CRP, Ferritin, IL-6 and PCT, were well-correlated between Tasso SST and venous serum with little sample type bias, but concentrations of D-dimer, IL-1B and IL-1Ra were not. Self-collection at home with delayed sample processing was associated with significant concentrations differences for several analytes compared to supervised, in-clinic collection with rapid processing. Finally, Tasso SST serum protein concentrations were significantly elevated in in non-hospitalized COVID-19 patients compared with healthy controls. CONCLUSIONS: Self-collection of capillary blood with micro-sampling devices provides an attractive alternative to routine phlebotomy. However, concentrations of certain analytes may differ significantly from those in venous samples, and factors including user proficiency, temperature control and time lags between specimen collection and processing need to be considered for their effect on sample quality and reproducibility.