Assessment of Herpes Zoster Risk Among Recipients of COVID-19 Vaccine.

Importance: Herpes zoster infection after COVID-19 vaccination has been reported in numerous case studies. It is not known whether these cases represent increased reporting or a true increase in risk. Objective: To assess whether COVID-19 vaccination is associated with an increased risk of herpes zoster infection. Design, Setting, and Participants: This cohort study used a self-controlled risk interval (SCRI) design to compare the risk of herpes zoster in a risk interval of 30 days after COVID-19 vaccination or up to the date of the second vaccine dose with a control interval remote from COVID-19 vaccination (defined as 60-90 days after the last recorded vaccination date for each individual, allowing for a 30-day washout period between control and risk intervals). A supplemental cohort analysis was used to compare the risk of herpes zoster after COVID-19 vaccination with the risk of herpes zoster after influenza vaccination among 2 historical cohorts who received an influenza vaccine in the prepandemic period (January 1, 2018, to December 31, 2019) or the early pandemic period (March 1, 2020, to November 30, 2020). Data were obtained from Optum Labs Data Warehouse, a US national deidentified claims-based database. A total of 2 039 854 individuals who received any dose of a COVID-19 vaccine with emergency use authorization (BNT162b2 [Pfizer-BioNTech], mRNA-1273 [Moderna], or Ad26.COV2.S [Johnson & Johnson]) from December 11, 2020, through June 30, 2021, were eligible for inclusion. Individuals included in the SCRI analysis were a subset of the COVID-19-vaccinated cohort who had herpes zoster during either a risk or control interval. Exposures: Any dose of a COVID-19 vaccine. Main Outcomes and Measures: Incident herpes zoster, defined by International Statistical Classification of Diseases and Related Health Problems, Tenth Revision codes and a prescription of a new antiviral medication or a dose increase in antiviral medication within 5 days of diagnosis. Results: Among 2 039 854 individuals who received any dose of a COVID-19 vaccine during the study period, the mean (SD) age was 43.2 (16.3) years; 1 031 149 individuals (50.6%) were female, and 1 344 318 (65.9%) were White. Of those, 1451 patients (mean [SD] age, 51.6 [12.6] years; 845 [58.2%] female) with a herpes zoster diagnosis were included in the primary SCRI analysis. In the SCRI analysis, COVID-19 vaccination was not associated with an increased risk of herpes zoster after adjustment (incidence rate ratio, 0.91; 95% CI, 0.82-1.01; P = .08). In the supplementary cohort analysis, COVID-19 vaccination was not associated with a higher risk of herpes zoster compared with influenza vaccination in the prepandemic period (first dose of COVID-19 vaccine: hazard ratio [HR], 0.78 [95% CI, 0.70-0.86; P < .001]; second dose of COVID-19 vaccine: HR, 0.79 [95% CI, 0.71-0.88; P < .001]) or the early pandemic period (first dose of COVID-19 vaccine: HR, 0.89 [95% CI, 0.80-1.00; P = .05]; second dose: HR, 0.91 [95% CI, 0.81-1.02; P = .09]). Conclusions and Relevance: In this study, there was no association found between COVID-19 vaccination and an increased risk of herpes zoster infection, which may help to address concerns about the safety profile of the COVID-19 vaccines among patients and clinicians.

Association between Immunosuppressive Drugs and Coronavirus Disease 2019 Outcomes in Patients with Noninfectious Uveitis in a Large US Claims Database.

PURPOSE: To determine the dose-dependent risk of systemic corticosteroids (SCs) and the risk of other immunosuppressive therapies on coronavirus disease 2019 (COVID-19) infection, hospitalization, and death in patients with noninfectious uveitis (NIU). DESIGN: A retrospective cohort study from January 20, 2020, to December 31, 2020 (an era before widespread COVID-19 vaccination), using the Optum Labs Data Warehouse, a US national de-identified claims database. PARTICIPANTS: Patients who had at least 1 NIU diagnosis from January 1, 2017. METHODS: Unadjusted and adjusted hazard ratios (HRs) were estimated for each variable and COVID-19 outcome using Cox proportional hazards models, with time-updated dichotomous indicators for outpatient immunosuppressive medication exposure. To assess the dose-dependent effect of SC exposure, the average daily dose of prednisone over the exposed interval was included in the adjusted models as a continuous variable, in addition to the dichotomous variable. MAIN OUTCOME MEASURES: Incidence rates of COVID-19 infection, COVID-19-related hospitalization, and COVID-19-related in-hospital death. RESULTS: This study included 52 286 NIU patients of whom 12 000 (23.0%) were exposed to immunosuppressive medications during the risk period. In adjusted models, exposure to SCs was associated with increased risk of COVID-19 infection (HR, 2.66; 95% confidence interval [CI], 2.19-3.24; P < 0.001), hospitalization (HR, 3.26; 95% CI, 2.46-4.33; P < 0.001), and in-hospital death (HR, 1.99; 95% CI, 0.93-4.27; P = 0.08). Furthermore, incremental increases in the dosage of SCs were associated with a greater risk for these outcomes. Although tumor necrosis factor-α (TNF-α) inhibitors were associated with an increased risk of infection (HR, 1.48; 95% CI, 1.08-2.04; P = 0.02), other immunosuppressive treatments did not increase the risk of COVID-19 infection, hospitalization, or death. CONCLUSIONS: This study from an era before widespread COVID-19 vaccination demonstrates that outpatient SC exposure is associated with greater risk of COVID-19 infection and severe outcomes in patients with NIU. Future studies should evaluate the impact of immunosuppression in vaccinated NIU patients. Limiting exposure to SCs and use of alternative therapies may be warranted.

The Association between Noninfectious Uveitis and Coronavirus Disease 2019 Outcomes: An Analysis of United States Claims-Based Data.

PURPOSE: To identify if noninfectious uveitis (NIU) is associated with a greater risk of Coronavirus Disease 2019 (COVID-19) infection, hospitalization, and death. DESIGN: A retrospective cohort study from January 20, 2020 to December 31, 2020, using a national claims-based database. PARTICIPANTS: Enrollees who had continuous enrollment with both medical and pharmacy coverage for 3 years before January 20, 2020. Patients with an NIU diagnosis within 3 years of the start of the study were included in the NIU cohort. Those with infectious uveitis codes or new NIU diagnoses during the risk period were excluded. METHODS: Cox proportional hazard models were used to identify unadjusted hazard ratios (HRs) and adjusted HRs for all covariates for each outcome measure. Adjusted models accounted for patient demographics, health status, and immunosuppressive medication use during the risk period. MAIN OUTCOME MEASURES: Rates of COVID-19 infection, COVID-19-related hospitalization, and COVID-19-related in-hospital death identified with International Classification of Disease 10th revision codes. RESULTS: This study included 5 806 227 patients, of whom 29 869 (0.5%) had a diagnosis of NIU. On unadjusted analysis, patients with NIU had a higher rate of COVID-19 infection (5.7% vs. 4.5%, P < 0.001), COVID-19-related hospitalization (1.2% vs. 0.6%, P < 0.001), and COVID-19-related death (0.3% vs. 0.1%, P < 0.001). However, in adjusted models, NIU was not associated with a greater risk of COVID-19 infection (HR, 1.05; 95% confidence interval [CI], 1.00-1.10; P = 0.04), hospitalization (HR, 0.98; 95% CI, 0.88-1.09; P = 0.67), or death (HR, 0.90, 95% CI, 0.72-1.13, P = 0.37). Use of systemic corticosteroids was significantly associated with a higher risk of COVID-19 infection, hospitalization, and death. CONCLUSIONS: Patients with NIU were significantly more likely to be infected with COVID-19 and experience severe disease outcomes. However, this association was due to the demographics, comorbidities, and medications of patients with NIU, rather than NIU alone. Patients using systemic corticosteroids were significantly more likely to be infected with COVID-19 and were at greater risk of hospitalization and in-hospital death. Additional investigation is necessary to identify the impact of corticosteroid exposure on COVID-19-related outcomes.

Effect of Oral Azithromycin vs Placebo on COVID-19 Symptoms in Outpatients With SARS-CoV-2 Infection: A Randomized Clinical Trial.

Importance: Azithromycin has been hypothesized to have activity against SARS-CoV-2. Objective: To determine whether oral azithromycin in outpatients with SARS-CoV-2 infection leads to absence of self-reported COVID-19 symptoms at day 14. Design, Setting, and Participants: Randomized clinical trial of azithromycin vs matching placebo conducted from May 2020 through March 2021. Outpatients from the US were enrolled remotely via internet-based surveys and followed up for 21 days. Eligible participants had a positive SARS-CoV-2 diagnostic test result (nucleic acid amplification or antigen) within 7 days prior to enrollment, were aged 18 years or older, and were not hospitalized at the time of enrollment. Among 604 individuals screened, 297 were ineligible, 44 refused participation, and 263 were enrolled. Participants, investigators, and study staff were masked to treatment randomization. Interventions: Participants were randomized in a 2:1 fashion to a single oral 1.2-g dose of azithromycin (n = 171) or matching placebo (n = 92). Main Outcomes and Measures: The primary outcome was absence of self-reported COVID-19 symptoms at day 14. There were 23 secondary clinical end points, including all-cause hospitalization at day 21. Results: Among 263 participants who were randomized (median age, 43 years; 174 [66%] women; 57% non-Hispanic White and 29% Latinx/Hispanic), 76% completed the trial. The trial was terminated by the data and safety monitoring committee for futility after the interim analysis. At day 14, there was no significant difference in proportion of participants who were symptom free (azithromycin: 50%; placebo: 50%; prevalence difference, 0%; 95% CI, -14% to 15%; P > .99). Of 23 prespecified secondary clinical end points, 18 showed no significant difference. By day 21, 5 participants in the azithromycin group had been hospitalized compared with 0 in the placebo group (prevalence difference, 4%; 95% CI, -1% to 9%; P = .16). Conclusions and Relevance: Among outpatients with SARS-CoV-2 infection, treatment with a single dose of azithromycin compared with placebo did not result in greater likelihood of being symptom free at day 14. These findings do not support the routine use of azithromycin for outpatient SARS-CoV-2 infection. Trial Registration: ClinicalTrials.gov Identifier: NCT04332107.

Differences of SARS-CoV-2 serological test performance between hospitalized and outpatient COVID-19 cases.

BACKGROUND: Serological severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody assays differ in the target antigen specificity, e.g. of antibodies directed against the viral spike or the nucleocapsid protein, and in the spectrum of detected immunoglobulins. The aim of the study was to evaluate the performance of two different routinely used immunoassays in hospitalized and outpatient COVID-19 cases. METHODS: The test characteristics of commercially available spike1 protein-based serological assays (Euroimmun, EI-assays), determining IgA or IgG and nucleocapsid-based assays (Virotech, VT-assays) determining IgA, IgM or IgG were compared in 139 controls and 116 hospitalized and outpatient COVID-19 cases. RESULTS: Hospitalized COVID-19 patients (n = 51; 115 samples) showed significantly higher concentrations of antibodies against SARS-CoV-2 and differed from outpatient cases (n = 65) by higher age, higher disease severity scores and earlier follow up blood sampling. Sensitivity of the two IgG assays was comparable in hospitalized patients tested ≥ 14 days (EI-assay: 88%, CI95% 67.6-99.9; VT-assay: 96%, CI95% 77.7-99.8). In outpatient COVID-19 cases sensitivity was significantly lower in the VT-assay (86.2%, CI95% 74.8-93.1) compared with the EI-assay (98.5%, CI95% 90.6-99.9). Assays for IgA and IgM demonstrated a lack of specificity or sensitivity. CONCLUSIONS: Our results indicate that SARS-CoV-2 serological assays may need to be optimized to produce reliable results in outpatient COVID-19 cases who are low or even asymptomatic. Assays for IgA and IgM have limited diagnostic performance and do not prove an additional value for population-based screening approaches.

Urinary Proteomics Associates with COVID-19 Severity: Pilot Proof-of-Principle Data and Design of a Multicentric Diagnostic Study.

SARS-CoV-2 infection results in a mild-to-moderate disease course in most patients, allowing outpatient self-care and quarantine. However, in approx. 10% of cases a two- or three-phasic critical disease course with starting from day 7 to 10 is observed. To facilitate and plan outpatient care, biomarkers prognosing such worsening at an early stage appear of outmost importance. In this accelerated article, we report on the identification of urinary peptides significantly associated with SARS-CoV-2 infection, and the development of a multi-marker urinary peptide based test, COVID20, that may enable prognosis of critical and fatal outcomes in COVID-19 patients. COVID20 is composed of 20 endogenous peptides mainly derived from various collagen chains that enable differentiating moderate or severe disease from critical state or death with 83% sensitivity at 100% specificity. Based on the performance in this pilot study, testing in a prospective study on 1000 patients has been initiated. This article is protected by copyright. All rights reserved.

Substantial underestimation of SARS-CoV-2 infection in the United States.

Accurate estimates of the burden of SARS-CoV-2 infection are critical to informing pandemic response. Confirmed COVID-19 case counts in the U.S. do not capture the total burden of the pandemic because testing has been primarily restricted to individuals with moderate to severe symptoms due to limited test availability. Here, we use a semi-Bayesian probabilistic bias analysis to account for incomplete testing and imperfect diagnostic accuracy. We estimate 6,454,951 cumulative infections compared to 721,245 confirmed cases (1.9% vs. 0.2% of the population) in the United States as of April 18, 2020. Accounting for uncertainty, the number of infections during this period was 3 to 20 times higher than the number of confirmed cases. 86% (simulation interval: 64-99%) of this difference is due to incomplete testing, while 14% (0.3-36%) is due to imperfect test accuracy. The approach can readily be applied in future studies in other locations or at finer spatial scale to correct for biased testing and imperfect diagnostic accuracy to provide a more realistic assessment of COVID-19 burden.