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Abstract BackgroundBacterial infections may complicate viral pneumonias. Recent reports suggest that bacterial co-infection at time of presentation is uncommon in coronavirus disease 2019 (COVID-19); however, estimates were based on microbiology tests alone. We sought to develop and apply consensus definitions, incorporating clinical criteria to better understand the rate of co-infections and antibiotic use in COVID-19. MethodsA total of 1016 adult patients admitted to 5 hospitals in the Johns Hopkins Health System between March 1, 2020, and May 31, 2020, with COVID-19 were evaluated. Adjudication of co-infection using definitions developed by a multidisciplinary team for this study was performed. Both respiratory and common nonrespiratory co-infections were assessed. The definition of bacterial community-acquired pneumonia (bCAP) included proven (clinical, laboratory, and radiographic criteria plus microbiologic diagnosis), probable (clinical, laboratory, and radiographic criteria without microbiologic diagnosis), and possible (not all clinical, laboratory, and radiographic criteria met) categories. Clinical characteristics and antimicrobial use were assessed in the context of the consensus definitions. ResultsBacterial respiratory co-infections were infrequent (1.2%); 1 patient had proven bCAP, and 11 (1.1%) had probable bCAP. Two patients (0.2%) had viral respiratory co-infections. Although 69% of patients received antibiotics for pneumonia, the majority were stopped within 48 hours in patients with possible or no evidence of bCAP. The most common nonrespiratory infection was urinary tract infection (present in 3% of the cohort). ConclusionsUsing multidisciplinary consensus definitions, proven or probable bCAP was uncommon in adults hospitalized due to COVID-19, as were other nonrespiratory bacterial infections. Empiric antibiotic use was high, highlighting the need to enhance antibiotic stewardship in the treatment of viral pneumonias. Using standardized consensus definitions we evaluated 1,016 hospitalized adults for co-infections with COVID-19. Proven and probable bacterial respiratory co-infection was low (1.2%), yet most patients (69%) received antibiotics highlighting ongoing needs for antibiotic stewardship in respiratory viral infections.

As clinicians are faced with a deluge of clinical data, data science can play an important role in highlighting key features driving patient outcomes, aiding in the development of new clinical hypotheses. Insight derived from machine learning can serve as a clinical support tool by connecting care providers with reliable results from big data analysis that identify previously undetected clinical patterns. In this work, we show an example of collaboration between clinicians and data scientists during the COVID-19 pandemic, identifying sub-groups of COVID-19 patients with unanticipated outcomes or who are high-risk for severe disease or death. We apply a random forest classifier model to predict adverse patient outcomes early in the disease course, and we connect our classification results to unsupervised clustering of patient features that may underpin patient risk. The paradigm for using data science for hypothesis generation and clinical decision support, as well as our triaged classification approach and unsupervised clustering methods to determine patient cohorts, are applicable to driving rapid hypothesis generation and iteration in a variety of clinical challenges, including future public health crises.

In response to the Ebola outbreak of 2014–2016, the US Office of the Assistant Secretary for Preparedness and Response (ASPR) established 10 regional treatment centers, called biocontainment units (BCUs), to prepare and provide care for patients infected with high-consequence pathogens. Many of these BCUs were among the first units to activate for coronavirus disease 2019 (COVID-19) patient care. The activities of the Johns Hopkins BCU helped prepare the Johns Hopkins Health System for COVID-19 in the 3 domains of containment care: (1) preparedness planning, education and training, (2) patient care and unit operations, and (3) research and innovation. Here, we describe the role of the JH BCU in the Hopkins COVID-19 response to illustrate the value of BCUs in the current pandemic and their potential role in preparing healthcare facilities and health systems for future infectious disease threats.

B-cell depletion therapy is employed in a variety of clinical contexts from auto-immune diseases to malignancy. Prior research on patients with prior B-cell depletion treatment has suggested a mortality risk in patients hospitalized with COVID-19 however previous case–control studies have differed in their methods of patient comparison. Patients previously treated with B-cell-depletion hospitalized with COVID-19 were compared to matched controls in the Johns Hopkins Health System between March 1, 2020 and November 30, 2021. The primary outcome was 30-day all-cause mortality. Secondary outcomes included time to severe illness or death and time to clinical improvement. To eliminate bias due to imbalanced covariates, each patient who had previously received B-cell depletion therapy was matched with patients who had not received therapy based on age, sex, race, WHO severity score, admission date, COVID-19 specific treatment, and vaccination status. Propensity scores were calculated from a multivariable logistic regression model and performed on the matched sets, using B-cell depletion as the outcome, where the propensity score was the probability of receiving B-cell depletion therapy. The propensity score included matched covariates as well as smoking status, medical comorbidities, and vaccination status. Cox proportional-hazards regression models were applied on the matched sets to perform time to death, time to severe illness or death, and time to clinical improvement analyses. 50 patients were identified who had received B-cell depletion therapy and were compared to 186 matched controls. Patients treated with B-cell depletion experienced 30-day mortality of 6.0% compared to 3.8% in controls, adjusted hazard ratio (aHR) 1.45 (95% CI 0.30 to 6.95). B-cell-depleted patients experienced a longer time to clinical improvement, aHR 0.65 (95% CI 0.45–0.94). In this cohort, patients treated with B-cell depletion experienced a higher mortality rate compared to matched controls however this was not statistically significant. This group also experienced a prolonged time to clinical improvement based on WHO severity score.

Genomic studies of patients with COVID-19, or exposed to it, are underway to delineate host factors associated with variability in susceptibility, infectivity, and disease severity. Here, we highlight the ethical implications—both potential benefits and harms—of genomics for clinical practice and public health in the era of COVID-19.

Acute lung injury (ALI) is a debilitating condition associated with severe skeletal muscle weakness that persists in humans long after lung injury has resolved. The molecular mechanisms underlying this condition are unknown. To identify the muscle-specific molecular mechanisms responsible for muscle wasting in a mouse model of ALI. Changes in skeletal muscle weight, fiber size, in vivo contractile performance, and expression of mRNAs and proteins encoding muscle atrophy-associated genes for muscle ring finger-1 (MuRF1) and atrogin1 were measured. Genetic inactivation of MuRF1 or electroporation-mediated transduction of miRNA-based short hairpin RNAs targeting either MuRF1 or atrogin1 were used to identify their role in ALI-associated skeletal muscle wasting. Mice with ALI developed profound muscle atrophy and preferential loss of muscle contractile proteins associated with reduced muscle function in vivo. Although mRNA expression of the muscle-specific ubiquitin ligases, MuRF1 and atrogin1, was increased in ALI mice, only MuRF1 protein levels were up-regulated. Consistent with these changes, suppression of MuRF1 by genetic or biochemical approaches prevented muscle fiber atrophy, whereas suppression of atrogin1 expression was without effect. Despite resolution of lung injury and down-regulation of MuRF1 and atrogin1, force generation in ALI mice remained suppressed. These data show that MuRF1 is responsible for mediating muscle atrophy that occurs during the period of active lung injury in ALI mice and that, as in humans, skeletal muscle dysfunction persists despite resolution of lung injury.

Bedside clinical skills have been diminished by an overreliance on technology. This article presents educational strategies for reinvigorating the bedside encounter and shows how much can be learned from it.

The development of a coronavirus disease 2019 (COVID-19) vaccine has progressed at unprecedented speed. Widespread public uptake of the vaccine is crucial to stem the pandemic. To examine the factors associated with survey participants' self-reported likelihood of selecting and receiving a hypothetical COVID-19 vaccine. A survey study of a nonprobability convenience sample of 2000 recruited participants including a choice-based conjoint analysis was conducted to estimate respondents' probability of choosing a vaccine and willingness to receive vaccination. Participants were asked to evaluate their willingness to receive each hypothetical vaccine individually. The survey presented respondents with 5 choice tasks. In each, participants evaluated 2 hypothetical COVID-19 vaccines and were asked whether they would choose vaccine A, vaccine B, or neither vaccine. Vaccine attributes included efficacy, protection duration, major adverse effects, minor adverse effects, US Food and Drug Administration (FDA) approval process, national origin of vaccine, and endorsement. Levels of each attribute for each vaccine were randomly assigned, and attribute order was randomized across participants. Survey data were collected on July 9, 2020. Average marginal component effect sizes and marginal means were calculated to estimate the relationship between each vaccine attribute level and the probability of the respondent choosing a vaccine and self-reported willingness to receive vaccination. A total of 1971 US adults responded to the survey (median age, 43 [interquartile range, 30-58] years); 999 (51%) were women, 1432 (73%) White, 277 (14%) were Black, and 190 (10%) were Latinx. An increase in efficacy from 50% to 70% was associated with a higher probability of choosing a vaccine (coefficient, 0.07; 95% CI, 0.06-0.09), and an increase from 50% to 90% was associated with a higher probability of choosing a vaccine (coefficient, 0.16; 95% CI, 0.15-0.18). An increase in protection duration from 1 to 5 years was associated with a higher probability of choosing a vaccine (coefficient, 0.05 95% CI, 0.04-0.07). A decrease in the incidence of major adverse effects from 1 in 10 000 to 1 in 1 000 000 was associated with a higher probability of choosing a vaccine (coefficient, 0.07; 95% CI, 0.05-0.08). An FDA emergency use authorization was associated with a lower probability of choosing a vaccine (coefficient, -0.03; 95% CI, -0.04 to -0.01) compared with full FDA approval. A vaccine that originated from a non-US country was associated with a lower probability of choosing a vaccine (China: -0.13 [95% CI, -0.15 to -0.11]; UK: -0.04 [95% CI, -0.06 to -0.02]). Endorsements from the US Centers for Disease Control and Prevention (coefficient, 0.09; 95% CI, 0.07-0.11) and the World Health Organization (coefficient, 0.06; 95% CI, 0.04-0.08), compared with an endorsement from President Trump were associated with higher probabilities of choosing a vaccine. Analyses of participants' willingness to receive each vaccine when assessed individually yielded similar results. An increase in efficacy from 50% to 90% was associated with a 10% higher marginal mean willingness to receive a vaccine (from 0.51 to 0.61). A reduction in the incidence of major side effects was associated with a 4% higher marginal mean willingness to receive a vaccine (from 0.54 to 0.58). A vaccine originating in China was associated with a 10% lower willingness to receive a vaccine vs one developed in the US (from 0.60 to 0.50) Endorsements from the Centers for Disease Control and Prevention and World Health Organization were associated with increases in willingness to receive a vaccine (7% and 6%, respectively) from a baseline endorsement by President Trump (from 0.52 to 0.59 and from 0.52 to 0.58, respectively). In this survey study of US adults, vaccine-related attributes and political characteristics were associated with self-reported preferences for choosing a hypothetical COVID-19 vaccine and self-reported willingness to receive vaccination. These results may help inform public health campaigns to address vaccine hesitancy when a COVID-19 vaccine becomes available.

Current clinical guidelines recommend thromboprophylaxis for adults hospitalized with coronavirus disease 2019 (COVID‐19), yet it is unknown whether higher doses of thromboprophylaxis offer benefits beyond standard doses. We studied electronic health records from 50 091 adults hospitalized with COVID‐19 in the United States between February 2020 and February 2021. We compared standard (enoxaparin 30 or 40 mg/day, fondaparinux 2.5 mg, or heparin 5000 units twice or thrice per day) versus intermediate (enoxaparin 30 or 40 mg twice daily, or up to 1.2 mg/kg of body weight daily, heparin 7500 units thrice per day or heparin 10 000 units twice or thrice per day) thromboprophylaxis. We separately examined risk of escalation to therapeutic anticoagulation, severe disease (first occurrence of high‐flow nasal cannula, noninvasive positive pressure ventilation or invasive mechanical ventilation), and death. To summarize risk, we present hazard ratios (HRs) with 95% confidence intervals (CIs) using adjusted time‐dependent Cox proportional hazards regression models. People whose first dose was high intensity were younger, more often obese, and had greater oxygen support requirements. Intermediate dose thromboprophylaxis was associated with increased risk of therapeutic anticoagulation (HR, 3.39; 95% CI, 3.22‐3.57), severe disease (HR, 1.22; 95% CI, 1.17‐1.28), and death (HR, 1.37; 95% CI, 1.21‐1.55). Increased risks associated with intermediate‐dose thromboprophylaxis persisted in subgroup and sensitivity analyses varying populations and definitions of exposures, outcomes, and covariates. Our findings do not support routine use of intermediate‐dose thromboprophylaxis to prevent clinical worsening, severe disease, or death among adults hospitalized with COVID‐19.