Development of an External Control Arm Using Electronic Health Record-Based Real-World Data to Evaluate the Efficacy of COVID-19 Treatment.

To protect people from severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection, tremendous research efforts have been made toward coronavirus disease 19 (COVID-19) treatment development. Externally controlled trials (ECTs) may help reduce their development time. To evaluate whether ECT using real-world data (RWD) of patients with COVID-19 is feasible enough to be used for regulatory decision making, we built an external control arm (ECA) based on RWD as a control arm of a previously conducted randomized controlled trial (RCT), and compared it to the control arm of the RCT. The electronic health record (EHR)-based COVID-19 cohort dataset was used as RWD, and three Adaptive COVID-19 Treatment Trial (ACTT) datasets were used as RCTs. Among the RWD datasets, eligible patients were evaluated as a pool of external control subjects of the ACTT-1, ACTT-2, and ACTT-3 trials, respectively. The ECAs were built using propensity score matching, and the balance of age, sex, and baseline clinical status ordinal scale as covariates between the treatment arms of Asian patients in each ACTT and the pools of external control subjects was assessed before and after 1:1 matching. There was no statistically significant difference in time to recovery between ECAs and the control arms of each ACTT. Among the covariates, the baseline status ordinal score had the greatest influence on the building of ECA. This study demonstrates that ECA based on EHR data of COVID-19 patients could sufficiently replace the control arm of an RCT, and it is expected to help develop new treatments faster in emergency situations, such as the COVID-19 pandemic.

Influenza viral infection is a risk factor for severe illness in COVID-19 patients: a nationwide population-based cohort study.

In order to prepare for the twindemic of influenza and SARS-CoV-2 infection, we investigated the association between influenza infection and subsequent severity of SARS-CoV-2 infection. A population-based nationwide cohort study was performed using data from the National Health Insurance Service (NHIS) in the Republic of Korea. This study included 274,126 individuals who underwent SARS-CoV-2 PCR testing between 20 January 2020 and 1 October 2020. Among these patients, 28,338 tested positive for SARS-CoV-2, and 4,003 of these individuals had a history of influenza. The control group was selected through 1:1 propensity score matching. In the group of 4,003 COVID-19-positive individuals with no history of influenza, 192 (4.8%) experienced severe illness from COVID-19 infection. In the group of 4,003 COVID-19-positive individuals with a history of influenza, 260 (6.5%) had severe illness from COVID-19, and the overall adjusted odds ratio (aOR) was 1.29 (95% confidence interval 1.04-1.59). Among the 4,003 COVID-19-positive individuals with a history of influenza, severe COVID-19 infection was experienced by 143 of 1,760 (8.1%) with an influenza history within 1 year before the onset of COVID-19, 48 of 1,129 (4.3%) between 1 and 2 years, and 69 of 1,114 (6.2%) between 2 and 3 years before COVID-19 onset, and the aORs were 1.54 (1.20-1.98), 1.19 (0.84-1.70), and 1.00 (0.73-1.37), respectively. In conclusion, individuals who had an influenza infection less than 1 year before COVID-19 infection were at an increased risk of experiencing severe illness from the SARS-CoV-2 infection. To control the public health burden, it is essential that effective public health control measures, which include influenza vaccination, hand washing, cough etiquette, and mask use are in place.

Bean Extract-Based Gargle for Efficient Diagnosis of Active COVID-19 Infection Using Rapid Antigen Tests.

The antigen-based rapid diagnostic test (Ag-RDT) using saliva specimens is fast, noninvasive, and suitable for SARS-CoV-2 self-testing, unlike nasopharyngeal swab (NPS) testing. We evaluated a novel Beanguard gargle (BG)-based virus collection method that can be applied to Ag-RDT as an alternative to the current RT-PCR with an NPS for early diagnosis of COVID-19. This clinical trial comprised 102 COVID-19-positive patients hospitalized after a governmental screening process and 100 healthy individuals. Paired NPS and BG-based saliva specimens from COVID-19 patients and healthy individuals were analyzed using NPS-RT-PCR, BG-RT-PCR, and BG-Ag-RDTs, whose diagnostic performance for detecting SARS-CoV-2 was compared. BG-Ag-RDTs showed high sensitivity (97.8%) and specificity (100%) in 45 patients within 6 days of illness and detected all cases of SARS-CoV-2 Alpha and Delta variants. In 11 asymptomatic active COVID-19 cases, both BG-Ag-RDTs and BG-RT-PCR showed sensitivities and specificities of 100%. Sensitivities of BG-Ag-RDT and BG-RT-PCR toward salivary viral detection were highly concordant, with no discrimination between symptomatic (97.0%), asymptomatic (100%), or SARS-CoV-2 variant (100%) cases. The intermolecular interactions between SARS-CoV-2 spike proteins and truncated canavalin, an active ingredient from the bean extract (BE), were observed in terms of physicochemical properties. The detachment of the SARS-CoV-2 receptor-binding domain from hACE2 increased as the BE concentration increased, allowing the release of the virus from hACE2 for early diagnosis. Using BG-based saliva specimens remarkably enhances the Ag-RDT diagnostic performance as an alternative to NPS and enables noninvasive, rapid, and accurate COVID-19 self-testing and mass screening, supporting efficient COVID-19 management. IMPORTANCE An Ag-RDT is less likely to be accepted as an initial test method for early diagnosis owing to its low sensitivity. However, our self-collection method, Ag-RDT using BG-based saliva specimens, showed significantly enhanced detection sensitivity and specificity toward SARS-CoV-2 including the Alpha and Delta variants in all patients tested within 6 days of illness. The method represents an attractive alternative to nasopharyngeal swabs for the early diagnosis of symptomatic and asymptomatic COVID-19 cases. The evidence suggests that the method could have a potential for mass screening and monitoring of COVID-19 cases.