Effect of Neutralizing Monoclonal Antibody Treatment on Early Trajectories of Virologic and Immunologic Biomarkers in Patients Hospitalized With COVID-19.

BACKGROUND: Neutralizing monoclonal antibodies (nmAbs) failed to show clear benefit for hospitalized patients with coronavirus disease 2019 (COVID-19). Dynamics of virologic and immunologic biomarkers remain poorly understood. METHODS: Participants enrolled in the Therapeutics for Inpatients with COVID-19 trials were randomized to nmAb versus placebo. Longitudinal differences between treatment and placebo groups in levels of plasma nucleocapsid antigen (N-Ag), anti-nucleocapsid antibody, C-reactive protein, interleukin-6, and D-dimer at enrollment, day 1, 3, and 5 were estimated using linear mixed models. A 7-point pulmonary ordinal scale assessed at day 5 was compared using proportional odds models. RESULTS: Analysis included 2149 participants enrolled between August 2020 and September 2021. Treatment resulted in 20% lower levels of plasma N-Ag compared with placebo (95% confidence interval, 12%-27%; P < .001), and a steeper rate of decline through the first 5 days (P < .001). The treatment difference did not vary between subgroups, and no difference was observed in trajectories of other biomarkers or the day 5 pulmonary ordinal scale. CONCLUSIONS: Our study suggests that nmAb has an antiviral effect assessed by plasma N-Ag among hospitalized patients with COVID-19, with no blunting of the endogenous anti-nucleocapsid antibody response. No effect on systemic inflammation or day 5 clinical status was observed. CLINICAL TRIALS REGISTRATION: NCT04501978.

Baricitinib plus Remdesivir for Hospitalized Adults with Covid-19.

BACKGROUND: Severe coronavirus disease 2019 (Covid-19) is associated with dysregulated inflammation. The effects of combination treatment with baricitinib, a Janus kinase inhibitor, plus remdesivir are not known. METHODS: We conducted a double-blind, randomized, placebo-controlled trial evaluating baricitinib plus remdesivir in hospitalized adults with Covid-19. All the patients received remdesivir (≤10 days) and either baricitinib (≤14 days) or placebo (control). The primary outcome was the time to recovery. The key secondary outcome was clinical status at day 15. RESULTS: A total of 1033 patients underwent randomization (with 515 assigned to combination treatment and 518 to control). Patients receiving baricitinib had a median time to recovery of 7 days (95% confidence interval [CI], 6 to 8), as compared with 8 days (95% CI, 7 to 9) with control (rate ratio for recovery, 1.16; 95% CI, 1.01 to 1.32; P = 0.03), and a 30% higher odds of improvement in clinical status at day 15 (odds ratio, 1.3; 95% CI, 1.0 to 1.6). Patients receiving high-flow oxygen or noninvasive ventilation at enrollment had a time to recovery of 10 days with combination treatment and 18 days with control (rate ratio for recovery, 1.51; 95% CI, 1.10 to 2.08). The 28-day mortality was 5.1% in the combination group and 7.8% in the control group (hazard ratio for death, 0.65; 95% CI, 0.39 to 1.09). Serious adverse events were less frequent in the combination group than in the control group (16.0% vs. 21.0%; difference, -5.0 percentage points; 95% CI, -9.8 to -0.3; P = 0.03), as were new infections (5.9% vs. 11.2%; difference, -5.3 percentage points; 95% CI, -8.7 to -1.9; P = 0.003). CONCLUSIONS: Baricitinib plus remdesivir was superior to remdesivir alone in reducing recovery time and accelerating improvement in clinical status among patients with Covid-19, notably among those receiving high-flow oxygen or noninvasive ventilation. The combination was associated with fewer serious adverse events. (Funded by the National Institute of Allergy and Infectious Diseases; ClinicalTrials.gov number, NCT04401579.).

Abatacept, Cenicriviroc, or Infliximab for Treatment of Adults Hospitalized With COVID-19 Pneumonia: A Randomized Clinical Trial.

Importance: Immune dysregulation contributes to poorer outcomes in COVID-19. Objective: To investigate whether abatacept, cenicriviroc, or infliximab provides benefit when added to standard care for COVID-19 pneumonia. Design, Setting, and Participants: Randomized, double-masked, placebo-controlled clinical trial using a master protocol to investigate immunomodulators added to standard care for treatment of participants hospitalized with COVID-19 pneumonia. The results of 3 substudies are reported from 95 hospitals at 85 clinical research sites in the US and Latin America. Hospitalized patients 18 years or older with confirmed SARS-CoV-2 infection within 14 days and evidence of pulmonary involvement underwent randomization between October 2020 and December 2021. Interventions: Single infusion of abatacept (10 mg/kg; maximum dose, 1000 mg) or infliximab (5 mg/kg) or a 28-day oral course of cenicriviroc (300-mg loading dose followed by 150 mg twice per day). Main Outcomes and Measures: The primary outcome was time to recovery by day 28 evaluated using an 8-point ordinal scale (higher scores indicate better health). Recovery was defined as the first day the participant scored at least 6 on the ordinal scale. Results: Of the 1971 participants randomized across the 3 substudies, the mean (SD) age was 54.8 (14.6) years and 1218 (61.8%) were men. The primary end point of time to recovery from COVID-19 pneumonia was not significantly different for abatacept (recovery rate ratio [RRR], 1.12 [95% CI, 0.98-1.28]; P = .09), cenicriviroc (RRR, 1.01 [95% CI, 0.86-1.18]; P = .94), or infliximab (RRR, 1.12 [95% CI, 0.99-1.28]; P = .08) compared with placebo. All-cause 28-day mortality was 11.0% for abatacept vs 15.1% for placebo (odds ratio [OR], 0.62 [95% CI, 0.41-0.94]), 13.8% for cenicriviroc vs 11.9% for placebo (OR, 1.18 [95% CI 0.72-1.94]), and 10.1% for infliximab vs 14.5% for placebo (OR, 0.59 [95% CI, 0.39-0.90]). Safety outcomes were comparable between active treatment and placebo, including secondary infections, in all 3 substudies. Conclusions and Relevance: Time to recovery from COVID-19 pneumonia among hospitalized participants was not significantly different for abatacept, cenicriviroc, or infliximab vs placebo. Trial Registration: ClinicalTrials.gov Identifier: NCT04593940.

Host Gene Expression to Predict Sepsis Progression.

OBJECTIVES: Sepsis causes significant mortality. However, most patients who die of sepsis do not present with severe infection, hampering efforts to deliver early, aggressive therapy. It is also known that the host gene expression response to infection precedes clinical illness. This study seeks to develop transcriptomic models to predict progression to sepsis or shock within 72 hours of hospitalization and to validate previously identified transcriptomic signatures in the prediction of 28-day mortality. DESIGN: Retrospective differential gene expression analysis and predictive modeling using RNA sequencing data. PATIENTS: Two hundred seventy-seven patients enrolled at four large academic medical centers; all with clinically adjudicated infection were considered for inclusion in this study. MEASUREMENTS AND MAIN RESULTS: Sepsis progression was defined as an increase in Sepsis 3 category within 72 hours. Transcriptomic data were generated using RNAseq of whole blood. Least absolute shrinkage and selection operator modeling was used to identify predictive signatures for various measures of disease progression. Four previously identified gene signatures were tested for their ability to predict 28-day mortality. There were no significant differentially expressed genes in 136 subjects with worsened Sepsis 3 category compared with 141 nonprogressor controls. There were 1,178 differentially expressed genes identified when sepsis progression was defined as ICU admission or 28-day mortality. A model based on these genes predicted progression with an area under the curve of 0.71. Validation of previously identified gene signatures to predict sepsis mortality revealed area under the receiver operating characteristic values of 0.70-0.75 and no significant difference between signatures. CONCLUSIONS: Host gene expression was unable to predict sepsis progression when defined by an increase in Sepsis-3 category, suggesting this definition is not a useful framework for transcriptomic prediction methods. However, there was a differential response when progression was defined as ICU admission or death. Validation of previously described signatures predicted 28-day mortality with insufficient accuracy to offer meaningful clinical utility.

Discriminating Bacterial and Viral Infection Using a Rapid Host Gene Expression Test.

OBJECTIVES: Host gene expression signatures discriminate bacterial and viral infection but have not been translated to a clinical test platform. This study enrolled an independent cohort of patients to describe and validate a first-in-class host response bacterial/viral test. DESIGN: Subjects were recruited from 2006 to 2016. Enrollment blood samples were collected in an RNA preservative and banked for later testing. The reference standard was an expert panel clinical adjudication, which was blinded to gene expression and procalcitonin results. SETTING: Four U.S. emergency departments. PATIENTS: Six-hundred twenty-three subjects with acute respiratory illness or suspected sepsis. INTERVENTIONS: Forty-five-transcript signature measured on the BioFire FilmArray System (BioFire Diagnostics, Salt Lake City, UT) in ~45 minutes. MEASUREMENTS AND MAIN RESULTS: Host response bacterial/viral test performance characteristics were evaluated in 623 participants (mean age 46 yr; 45% male) with bacterial infection, viral infection, coinfection, or noninfectious illness. Performance of the host response bacterial/viral test was compared with procalcitonin. The test provided independent probabilities of bacterial and viral infection in ~45 minutes. In the 213-subject training cohort, the host response bacterial/viral test had an area under the curve for bacterial infection of 0.90 (95% CI, 0.84-0.94) and 0.92 (95% CI, 0.87-0.95) for viral infection. Independent validation in 209 subjects revealed similar performance with an area under the curve of 0.85 (95% CI, 0.78-0.90) for bacterial infection and 0.91 (95% CI, 0.85-0.94) for viral infection. The test had 80.1% (95% CI, 73.7-85.4%) average weighted accuracy for bacterial infection and 86.8% (95% CI, 81.8-90.8%) for viral infection in this validation cohort. This was significantly better than 68.7% (95% CI, 62.4-75.4%) observed for procalcitonin (p < 0.001). An additional cohort of 201 subjects with indeterminate phenotypes (coinfection or microbiology-negative infections) revealed similar performance. CONCLUSIONS: The host response bacterial/viral measured using the BioFire System rapidly and accurately discriminated bacterial and viral infection better than procalcitonin, which can help support more appropriate antibiotic use.

Average Weighted Accuracy: Pragmatic Analysis for a Rapid Diagnostics in Categorizing Acute Lung Infections (RADICAL) Study.

Patient management relies on diagnostic information to identify appropriate treatment. Standard evaluations of diagnostic tests consist of estimating sensitivity, specificity, positive/negative predictive values, likelihood ratios, and accuracy. Although useful, these metrics do not convey the tests' clinical value, which is critical to informing decision-making. Full appreciation of the clinical impact of a diagnostic test requires analyses that integrate sensitivity and specificity, account for the disease prevalence within the population of test application, and account for the relative importance of specificity vs sensitivity by considering the clinical implications of false-positive and false-negative results. We developed average weighted accuracy (AWA), representing a pragmatic metric of diagnostic yield or global utility of a diagnostic test. AWA can be used to compare test alternatives, even across different studies. We apply the AWA methodology to evaluate a new diagnostic test developed in the Rapid Diagnostics in Categorizing Acute Lung Infections (RADICAL) study.

Direct-from-blood RNA sequencing identifies the cause of post-bronchoscopy fever.

BACKGROUND: Antibiotic resistance is rising at disturbing rates and contributes to the deaths of millions of people yearly. Antibiotic resistant infections disproportionately affect those with immunocompromising conditions, chronic colonization, and frequent antibiotic use such as transplant patients or those with cystic fibrosis. However, clinicians lack the diagnostic tools to confidently diagnose and treat infections, leading to widespread use of empiric broad spectrum antimicrobials, often for prolonged duration. CASE PRESENTATION: A 22 year-old Caucasian female with cystic fibrosis received a bilateral orthotopic lung transplantation 5 months prior to the index hospitalization. She underwent routine surveillance bronchoscopy and was admitted for post-procedure fever. A clear cause of infection was not identified by routine methods. Imaging and bronchoscopic lung biopsy did not identify an infectious agent or rejection. She was treated with a prolonged course of antimicrobials targeting known colonizing organisms from prior bronchoalveolar lavage cultures (Pseudomonas, Staphylococcus aureus, and Aspergillus). However, we identified Stenotrophomonas maltophilia in two independent whole blood samples using direct-pathogen sequencing, which was not identified by other methods. CONCLUSIONS: This case represents a common clinical conundrum: identification of infection in a high-risk, complex patient. Here, direct-pathogen sequencing identified a pathogen that would not otherwise have been identified by common techniques. Had results been clinically available, treatment could have been customized, avoiding a prolonged course of broad spectrum antimicrobials that would only exacerbate resistance. Direct-pathogen sequencing is poised to fill a diagnostic gap for pathogen identification, allowing early identification and customization of treatment in a culture-independent, pathogen-agnostic manner.

Early trajectories of virological and immunological biomarkers and clinical outcomes in patients admitted to hospital for COVID-19: an international, prospective cohort study.

BACKGROUND: Serial measurement of virological and immunological biomarkers in patients admitted to hospital with COVID-19 can give valuable insight into the pathogenic roles of viral replication and immune dysregulation. We aimed to characterise biomarker trajectories and their associations with clinical outcomes. METHODS: In this international, prospective cohort study, patients admitted to hospital with COVID-19 and enrolled in the Therapeutics for Inpatients with COVID-19 platform trial within the Accelerating COVID-19 Therapeutic Interventions and Vaccines programme between Aug 5, 2020 and Sept 30, 2021 were included. Participants were included from 108 sites in Denmark, Greece, Poland, Singapore, Spain, Switzerland, Uganda, the UK, and the USA, and randomised to placebo or one of four neutralising monoclonal antibodies: bamlanivimab (Aug 5 to Oct 13, 2020), sotrovimab (Dec 16, 2020, to March 1, 2021), amubarvimab-romlusevimab (Dec 16, 2020, to March 1, 2021), and tixagevimab-cilgavimab (Feb 10 to Sept 30, 2021). This trial included an analysis of 2149 participants with plasma nucleocapsid antigen, anti-nucleocapsid antibody, C-reactive protein (CRP), IL-6, and D-dimer measured at baseline and day 1, day 3, and day 5 of enrolment. Day-90 follow-up status was available for 1790 participants. Biomarker trajectories were evaluated for associations with baseline characteristics, a 7-day pulmonary ordinal outcome, 90-day mortality, and 90-day rate of sustained recovery. FINDINGS: The study included 2149 participants. Participant median age was 57 years (IQR 46-68), 1246 (58·0%) of 2149 participants were male and 903 (42·0%) were female; 1792 (83·4%) had at least one comorbidity, and 1764 (82·1%) were unvaccinated. Mortality to day 90 was 172 (8·0%) of 2149 and 189 (8·8%) participants had sustained recovery. A pattern of less favourable trajectories of low anti-nucleocapsid antibody, high plasma nucleocapsid antigen, and high inflammatory markers over the first 5 days was observed for high-risk baseline clinical characteristics or factors related to SARS-CoV-2 infection. For example, participants with chronic kidney disease demonstrated plasma nucleocapsid antigen 424% higher (95% CI 319-559), CRP 174% higher (150-202), IL-6 173% higher (144-208), D-dimer 149% higher (134-165), and anti-nucleocapsid antibody 39% lower (60-18) to day 5 than those without chronic kidney disease. Participants in the highest quartile for plasma nucleocapsid antigen, CRP, and IL-6 at baseline and day 5 had worse clinical outcomes, including 90-day all-cause mortality (plasma nucleocapsid antigen hazard ratio (HR) 4·50 (95% CI 3·29-6·15), CRP HR 3·37 (2·30-4·94), and IL-6 HR 5·67 (4·12-7·80). This risk persisted for plasma nucleocapsid antigen and CRP after adjustment for baseline biomarker values and other baseline factors. INTERPRETATION: Patients admitted to hospital with less favourable 5-day biomarker trajectories had worse prognosis, suggesting that persistent viral burden might drive inflammation in the pathogenesis of COVID-19, identifying patients that might benefit from escalation of antiviral or anti-inflammatory treatment. FUNDING: US National Institutes of Health.

Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance.

Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.

Systematic comparison of published host gene expression signatures for bacterial/viral discrimination.

BACKGROUND: Measuring host gene expression is a promising diagnostic strategy to discriminate bacterial and viral infections. Multiple signatures of varying size, complexity, and target populations have been described. However, there is little information to indicate how the performance of various published signatures compare to one another. METHODS: This systematic comparison of host gene expression signatures evaluated the performance of 28 signatures, validating them in 4589 subjects from 51 publicly available datasets. Thirteen COVID-specific datasets with 1416 subjects were included in a separate analysis. Individual signature performance was evaluated using the area under the receiving operating characteristic curve (AUC) value. Overall signature performance was evaluated using median AUCs and accuracies. RESULTS: Signature performance varied widely, with median AUCs ranging from 0.55 to 0.96 for bacterial classification and 0.69-0.97 for viral classification. Signature size varied (1-398 genes), with smaller signatures generally performing more poorly (P < 0.04). Viral infection was easier to diagnose than bacterial infection (84% vs. 79% overall accuracy, respectively; P < .001). Host gene expression classifiers performed more poorly in some pediatric populations (3 months-1 year and 2-11 years) compared to the adult population for both bacterial infection (73% and 70% vs. 82%, respectively; P < .001) and viral infection (80% and 79% vs. 88%, respectively; P < .001). We did not observe classification differences based on illness severity as defined by ICU admission for bacterial or viral infections. The median AUC across all signatures for COVID-19 classification was 0.80 compared to 0.83 for viral classification in the same datasets. CONCLUSIONS: In this systematic comparison of 28 host gene expression signatures, we observed differences based on a signature's size and characteristics of the validation population, including age and infection type. However, populations used for signature discovery did not impact performance, underscoring the redundancy among many of these signatures. Furthermore, differential performance in specific populations may only be observable through this type of large-scale validation.

Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion.

SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associate with mild or moderate symptoms are already robust and include severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity is marked by upregulation classical antiviral pathways including those regulating IRF1 and IRF7, whereas in moderate disease these classical antiviral signals diminish suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.

Single-cell genome-wide association reveals that a nonsynonymous variant in ERAP1 confers increased susceptibility to influenza virus.

During pandemics, individuals exhibit differences in risk and clinical outcomes. Here, we developed single-cell high-throughput human in vitro susceptibility testing (scHi-HOST), a method for rapidly identifying genetic variants that confer resistance and susceptibility. We applied this method to influenza A virus (IAV), the cause of four pandemics since the start of the 20th century. scHi-HOST leverages single-cell RNA sequencing (scRNA-seq) to simultaneously assign genetic identity to cells in mixed infections of cell lines of European, African, and Asian origin, reveal associated genetic variants for viral burden, and identify expression quantitative trait loci. Integration of scHi-HOST with human challenge and experimental validation demonstrated that a missense variant in endoplasmic reticulum aminopeptidase 1 (ERAP1; rs27895) increased IAV burden in cells and human volunteers. rs27895 exhibits population differentiation, likely contributing to greater permissivity of cells from African populations to IAV. scHi-HOST is a broadly applicable method and resource for decoding infectious-disease genetics.

Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion.

SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associated with mild or moderate symptoms were already robust and included severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity was marked by upregulation of classical antiviral pathways, including those regulating IRF1 and IRF7, whereas in moderate disease, these classical antiviral signals diminished, suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.

Prospective Validation of a Rapid Host Gene Expression Test to Discriminate Bacterial From Viral Respiratory Infection.

Importance: Bacterial and viral causes of acute respiratory illness (ARI) are difficult to clinically distinguish, resulting in the inappropriate use of antibacterial therapy. The use of a host gene expression-based test that is able to discriminate bacterial from viral infection in less than 1 hour may improve care and antimicrobial stewardship. Objective: To validate the host response bacterial/viral (HR-B/V) test and assess its ability to accurately differentiate bacterial from viral infection among patients with ARI. Design, Setting, and Participants: This prospective multicenter diagnostic study enrolled 755 children and adults with febrile ARI of 7 or fewer days' duration from 10 US emergency departments. Participants were enrolled from October 3, 2014, to September 1, 2019, followed by additional enrollment of patients with COVID-19 from March 20 to December 3, 2020. Clinical adjudication of enrolled participants identified 616 individuals as having bacterial or viral infection. The primary analysis cohort included 334 participants with high-confidence reference adjudications (based on adjudicator concordance and the presence of an identified pathogen confirmed by microbiological testing). A secondary analysis of the entire cohort of 616 participants included cases with low-confidence reference adjudications (based on adjudicator discordance or the absence of an identified pathogen in microbiological testing). Thirty-three participants with COVID-19 were included post hoc. Interventions: The HR-B/V test quantified the expression of 45 host messenger RNAs in approximately 45 minutes to derive a probability of bacterial infection. Main Outcomes and Measures: Performance characteristics for the HR-B/V test compared with clinical adjudication were reported as either bacterial or viral infection or categorized into 4 likelihood groups (viral very likely [probability score <0.19], viral likely [probability score of 0.19-0.40], bacterial likely [probability score of 0.41-0.73], and bacterial very likely [probability score >0.73]) and compared with procalcitonin measurement. Results: Among 755 enrolled participants, the median age was 26 years (IQR, 16-52 years); 360 participants (47.7%) were female, and 395 (52.3%) were male. A total of 13 participants (1.7%) were American Indian, 13 (1.7%) were Asian, 368 (48.7%) were Black, 131 (17.4%) were Hispanic, 3 (0.4%) were Native Hawaiian or Pacific Islander, 297 (39.3%) were White, and 60 (7.9%) were of unspecified race and/or ethnicity. In the primary analysis involving 334 participants, the HR-B/V test had sensitivity of 89.8% (95% CI, 77.8%-96.2%), specificity of 82.1% (95% CI, 77.4%-86.6%), and a negative predictive value (NPV) of 97.9% (95% CI, 95.3%-99.1%) for bacterial infection. In comparison, the sensitivity of procalcitonin measurement was 28.6% (95% CI, 16.2%-40.9%; P < .001), the specificity was 87.0% (95% CI, 82.7%-90.7%; P = .006), and the NPV was 87.6% (95% CI, 85.5%-89.5%; P < .001). When stratified into likelihood groups, the HR-B/V test had an NPV of 98.9% (95% CI, 96.1%-100%) for bacterial infection in the viral very likely group and a positive predictive value of 63.4% (95% CI, 47.2%-77.9%) for bacterial infection in the bacterial very likely group. The HR-B/V test correctly identified 30 of 33 participants (90.9%) with acute COVID-19 as having a viral infection. Conclusions and Relevance: In this study, the HR-B/V test accurately discriminated bacterial from viral infection among patients with febrile ARI and was superior to procalcitonin measurement. The findings suggest that an accurate point-of-need host response test with high NPV may offer an opportunity to improve antibiotic stewardship and patient outcomes.

Baricitinib versus dexamethasone for adults hospitalised with COVID-19 (ACTT-4): a randomised, double-blind, double placebo-controlled trial.

BACKGROUND: Baricitinib and dexamethasone have randomised trials supporting their use for the treatment of patients with COVID-19. We assessed the combination of baricitinib plus remdesivir versus dexamethasone plus remdesivir in preventing progression to mechanical ventilation or death in hospitalised patients with COVID-19. METHODS: In this randomised, double-blind, double placebo-controlled trial, patients were enrolled at 67 trial sites in the USA (60 sites), South Korea (two sites), Mexico (two sites), Singapore (two sites), and Japan (one site). Hospitalised adults (≥18 years) with COVID-19 who required supplemental oxygen administered by low-flow (≤15 L/min), high-flow (>15 L/min), or non-invasive mechanical ventilation modalities who met the study eligibility criteria (male or non-pregnant female adults ≥18 years old with laboratory-confirmed SARS-CoV-2 infection) were enrolled in the study. Patients were randomly assigned (1:1) to receive either baricitinib, remdesivir, and placebo, or dexamethasone, remdesivir, and placebo using a permuted block design. Randomisation was stratified by study site and baseline ordinal score at enrolment. All patients received remdesivir (≤10 days) and either baricitinib (or matching oral placebo) for a maximum of 14 days or dexamethasone (or matching intravenous placebo) for a maximum of 10 days. The primary outcome was the difference in mechanical ventilation-free survival by day 29 between the two treatment groups in the modified intention-to-treat population. Safety analyses were done in the as-treated population, comprising all participants who received one dose of the study drug. The trial is registered with ClinicalTrials.gov, NCT04640168. FINDINGS: Between Dec 1, 2020, and April 13, 2021, 1047 patients were assessed for eligibility. 1010 patients were enrolled and randomly assigned, 516 (51%) to baricitinib plus remdesivir plus placebo and 494 (49%) to dexamethasone plus remdesivir plus placebo. The mean age of the patients was 58·3 years (SD 14·0) and 590 (58%) of 1010 patients were male. 588 (58%) of 1010 patients were White, 188 (19%) were Black, 70 (7%) were Asian, and 18 (2%) were American Indian or Alaska Native. 347 (34%) of 1010 patients were Hispanic or Latino. Mechanical ventilation-free survival by day 29 was similar between the study groups (Kaplan-Meier estimates of 87·0% [95% CI 83·7 to 89·6] in the baricitinib plus remdesivir plus placebo group and 87·6% [84·2 to 90·3] in the dexamethasone plus remdesivir plus placebo group; risk difference 0·6 [95% CI -3·6 to 4·8]; p=0·91). The odds ratio for improved status in the dexamethasone plus remdesivir plus placebo group compared with the baricitinib plus remdesivir plus placebo group was 1·01 (95% CI 0·80 to 1·27). At least one adverse event occurred in 149 (30%) of 503 patients in the baricitinib plus remdesivir plus placebo group and 179 (37%) of 482 patients in the dexamethasone plus remdesivir plus placebo group (risk difference 7·5% [1·6 to 13·3]; p=0·014). 21 (4%) of 503 patients in the baricitinib plus remdesivir plus placebo group had at least one treatment-related adverse event versus 49 (10%) of 482 patients in the dexamethasone plus remdesivir plus placebo group (risk difference 6·0% [2·8 to 9·3]; p=0·00041). Severe or life-threatening grade 3 or 4 adverse events occurred in 143 (28%) of 503 patients in the baricitinib plus remdesivir plus placebo group and 174 (36%) of 482 patients in the dexamethasone plus remdesivir plus placebo group (risk difference 7·7% [1·8 to 13·4]; p=0·012). INTERPRETATION: In hospitalised patients with COVID-19 requiring supplemental oxygen by low-flow, high-flow, or non-invasive ventilation, baricitinib plus remdesivir and dexamethasone plus remdesivir resulted in similar mechanical ventilation-free survival by day 29, but dexamethasone was associated with significantly more adverse events, treatment-related adverse events, and severe or life-threatening adverse events. A more individually tailored choice of immunomodulation now appears possible, where side-effect profile, ease of administration, cost, and patient comorbidities can all be considered. FUNDING: National Institute of Allergy and Infectious Diseases.

Abatacept for Treatment of Adults Hospitalized with Moderate or Severe Covid-19.

Background: We investigated whether abatacept, a selective costimulation modulator, provides additional benefit when added to standard-of-care for patients hospitalized with Covid-19. Methods: We conducted a master protocol to investigate immunomodulators for potential benefit treating patients hospitalized with Covid-19 and report results for abatacept. Intravenous abatacept (one-time dose 10 mg/kg, maximum dose 1000 mg) plus standard of care (SOC) was compared with shared placebo plus SOC. Primary outcome was time-to-recovery by day 28. Key secondary endpoints included 28-day mortality. Results: Between October 16, 2020 and December 31, 2021, a total of 1019 participants received study treatment (509 abatacept; 510 shared placebo), constituting the modified intention-to-treat cohort. Participants had a mean age 54.8 (SD 14.6) years, 60.5% were male, 44.2% Hispanic/Latino and 13.7% Black. No statistically significant difference for the primary endpoint of time-to-recovery was found with a recovery-rate-ratio of 1.14 (95% CI 1.00-1.29; p=0.057) compared with placebo. We observed a substantial improvement in 28-day all-cause mortality with abatacept versus placebo (11.0% vs. 15.1%; odds ratio [OR] 0.62 [95% CI 0.41- 0.94]), leading to 38% lower odds of dying. Improvement in mortality occurred for participants requiring oxygen/noninvasive ventilation at randomization. Subgroup analysis identified the strongest effect in those with baseline C-reactive protein >75mg/L. We found no statistically significant differences in adverse events, with safety composite index slightly favoring abatacept. Rates of secondary infections were similar (16.1% for abatacept; 14.3% for placebo). Conclusions: Addition of single-dose intravenous abatacept to standard-of-care demonstrated no statistically significant change in time-to-recovery, but improved 28-day mortality. Trial registration: ClinicalTrials.gov ( NCT04593940 ).

Infliximab for Treatment of Adults Hospitalized with Moderate or Severe Covid-19.

Background: Immune dysregulation contributes to poorer outcomes in severe Covid-19. Immunomodulators targeting various pathways have improved outcomes. We investigated whether infliximab provides benefit over standard of care. Methods: We conducted a master protocol investigating immunomodulators for potential benefit in treatment of participants hospitalized with Covid-19 pneumonia. We report results for infliximab (single dose infusion) versus shared placebo both with standard of care. Primary outcome was time to recovery by day 29 (28 days after randomization). Key secondary endpoints included 14-day clinical status and 28-day mortality. Results: A total of 1033 participants received study drug (517 infliximab, 516 placebo). Mean age was 54.8 years, 60.3% were male, 48.6% Hispanic or Latino, and 14% Black. No statistically significant difference in the primary endpoint was seen with infliximab compared with placebo (recovery rate ratio 1.13, 95% CI 0.99-1.29; p=0.063). Median (IQR) time to recovery was 8 days (7, 9) for infliximab and 9 days (8, 10) for placebo. Participants assigned to infliximab were more likely to have an improved clinical status at day 14 (OR 1.32, 95% CI 1.05-1.66). Twenty-eight-day mortality was 10.1% with infliximab versus 14.5% with placebo, with 41% lower odds of dying in those receiving infliximab (OR 0.59, 95% CI 0.39-0.90). No differences in risk of serious adverse events including secondary infections. Conclusions: Infliximab did not demonstrate statistically significant improvement in time to recovery. It was associated with improved 14-day clinical status and substantial reduction in 28- day mortality compared with standard of care. Trial registration: ClinicalTrials.gov ( NCT04593940 ).

A comparison of host response strategies to distinguish bacterial and viral infection.

OBJECTIVES: Compare three host response strategies to distinguish bacterial and viral etiologies of acute respiratory illness (ARI). METHODS: In this observational cohort study, procalcitonin, a 3-protein panel (CRP, IP-10, TRAIL), and a host gene expression mRNA panel were measured in 286 subjects with ARI from four emergency departments. Multinomial logistic regression and leave-one-out cross validation were used to evaluate the protein and mRNA tests. RESULTS: The mRNA panel performed better than alternative strategies to identify bacterial infection: AUC 0.93 vs. 0.83 for the protein panel and 0.84 for procalcitonin (P<0.02 for each comparison). This corresponded to a sensitivity and specificity of 92% and 83% for the mRNA panel, 81% and 73% for the protein panel, and 68% and 87% for procalcitonin, respectively. A model utilizing all three strategies was the same as mRNA alone. For the diagnosis of viral infection, the AUC was 0.93 for mRNA and 0.84 for the protein panel (p<0.05). This corresponded to a sensitivity and specificity of 89% and 82% for the mRNA panel, and 85% and 62% for the protein panel, respectively. CONCLUSIONS: A gene expression signature was the most accurate host response strategy for classifying subjects with bacterial, viral, or non-infectious ARI.

Comparing the Diagnostic Accuracy of Clinician Judgment to a Novel Host Response Diagnostic for Acute Respiratory Illness.

BACKGROUND: Difficulty discriminating bacterial from viral infections drives antibacterial misuse. Host gene expression tests discriminate bacterial and viral etiologies, but their clinical utility has not been evaluated. METHODS: Host gene expression and procalcitonin levels were measured in 582 emergency department participants with suspected infection. We also recorded clinician diagnosis and clinician-recommended treatment. These 4 diagnostic strategies were compared with clinical adjudication as the reference. To estimate the clinical impact of host gene expression, we calculated the change in overall Net Benefit (∆NB; the difference in Net Benefit comparing 1 diagnostic strategy with a reference) across a range of prevalence estimates while factoring in the clinical significance of false-positive and -negative errors. RESULTS: Gene expression correctly classified bacterial, viral, or noninfectious illness in 74.1% of subjects, similar to the other strategies. Clinical diagnosis and clinician-recommended treatment revealed a bias toward overdiagnosis of bacterial infection resulting in high sensitivity (92.6% and 94.5%, respectively) but poor specificity (67.2% and 58.8%, respectively), resulting in a 33.3% rate of inappropriate antibacterial use. Gene expression offered a more balanced sensitivity (79.0%) and specificity (80.7%), which corresponded to a statistically significant improvement in average weighted accuracy (79.9% vs 71.5% for procalcitonin and 76.3% for clinician-recommended treatment; P<.0001 for both). Consequently, host gene expression had greater Net Benefit in diagnosing bacterial infection than clinician-recommended treatment (∆NB=6.4%) and procalcitonin (∆NB=17.4%). CONCLUSIONS: Host gene expression-based tests to distinguish bacterial and viral infection can facilitate appropriate treatment, improving patient outcomes and mitigating the antibacterial resistance crisis.

Rationale and design of the Prone Position and Respiratory Outcomes in Non-intubated COVID-19 PatiEnts: The "PRONE" Study.

While benefits of prone position in mechanically-ventilated patients have been well-described, a randomized-control trial to determine the effects of prone positioning in awake, spontaneously-breathing patients with an acute pneumonia has not been previously conducted. Prone Position and Respiratory Outcomes in Non-Intubated COVID-19 PatiEnts: the "PRONE" Study (PRONE) was conducted in non-intubated hospitalized patients with coronavirus disease 2019 (COVID-19) pneumonia as defined by respiratory rate ≥ 20/min or an oxyhemoglobin saturation (SpO2) ≤ 93% without supplemental oxygen [1]. The PRONE trial was designed to investigate the effects of prone positioning on need for escalation in respiratory support, as defined by need for transition to a higher acuity level of care, increased fraction of inspired oxygen (FiO2), or the initiation of invasive mechanical ventilation. Secondary objectives were to assess the duration of effect of prone positioning on respiratory parameters such as respiratory rate and SpO2, as well as other outcomes such as time to discharge or transition in level of care.