Outpatient treatment of COVID-19 and incidence of post-COVID-19 condition over 10 months (COVID-OUT): a multicentre, randomised, quadruple-blind, parallel-group, phase 3 trial.

BACKGROUND: Post-COVID-19 condition (also known as long COVID) is an emerging chronic illness potentially affecting millions of people. We aimed to evaluate whether outpatient COVID-19 treatment with metformin, ivermectin, or fluvoxamine soon after SARS-CoV-2 infection could reduce the risk of long COVID. METHODS: We conducted a decentralised, randomised, quadruple-blind, parallel-group, phase 3 trial (COVID-OUT) at six sites in the USA. We included adults aged 30-85 years with overweight or obesity who had COVID-19 symptoms for fewer than 7 days and a documented SARS-CoV-2 positive PCR or antigen test within 3 days before enrolment. Participants were randomly assigned via 2 × 3 parallel factorial randomisation (1:1:1:1:1:1) to receive metformin plus ivermectin, metformin plus fluvoxamine, metformin plus placebo, ivermectin plus placebo, fluvoxamine plus placebo, or placebo plus placebo. Participants, investigators, care providers, and outcomes assessors were masked to study group assignment. The primary outcome was severe COVID-19 by day 14, and those data have been published previously. Because the trial was delivered remotely nationwide, the a priori primary sample was a modified intention-to-treat sample, meaning that participants who did not receive any dose of study treatment were excluded. Long COVID diagnosis by a medical provider was a prespecified, long-term secondary outcome. This trial is complete and is registered with ClinicalTrials.gov, NCT04510194. FINDINGS: Between Dec 30, 2020, and Jan 28, 2022, 6602 people were assessed for eligibility and 1431 were enrolled and randomly assigned. Of 1323 participants who received a dose of study treatment and were included in the modified intention-to-treat population, 1126 consented for long-term follow-up and completed at least one survey after the assessment for long COVID at day 180 (564 received metformin and 562 received matched placebo; a subset of participants in the metformin vs placebo trial were also randomly assigned to receive ivermectin or fluvoxamine). 1074 (95%) of 1126 participants completed at least 9 months of follow-up. 632 (56·1%) of 1126 participants were female and 494 (43·9%) were male; 44 (7·0%) of 632 women were pregnant. The median age was 45 years (IQR 37-54) and median BMI was 29·8 kg/m2 (IQR 27·0-34·2). Overall, 93 (8·3%) of 1126 participants reported receipt of a long COVID diagnosis by day 300. The cumulative incidence of long COVID by day 300 was 6·3% (95% CI 4·2-8·2) in participants who received metformin and 10·4% (7·8-12·9) in those who received identical metformin placebo (hazard ratio [HR] 0·59, 95% CI 0·39-0·89; p=0·012). The metformin beneficial effect was consistent across prespecified subgroups. When metformin was started within 3 days of symptom onset, the HR was 0·37 (95% CI 0·15-0·95). There was no effect on cumulative incidence of long COVID with ivermectin (HR 0·99, 95% CI 0·59-1·64) or fluvoxamine (1·36, 0·78-2·34) compared with placebo. INTERPRETATION: Outpatient treatment with metformin reduced long COVID incidence by about 41%, with an absolute reduction of 4·1%, compared with placebo. Metformin has clinical benefits when used as outpatient treatment for COVID-19 and is globally available, low-cost, and safe. FUNDING: Parsemus Foundation; Rainwater Charitable Foundation; Fast Grants; UnitedHealth Group Foundation; National Institute of Diabetes, Digestive and Kidney Diseases; National Institutes of Health; and National Center for Advancing Translational Sciences.

Impact of SARS-CoV-2 vaccination and booster on COVID-19 symptom severity over time in the COVID-OUT trial.

BACKGROUND: SARS-CoV-2 vaccination has decreasing protection from acquiring any infection with emergence of new variants; however, vaccination continues to protect against progression to severe COVID-19. The impact of vaccination status on symptoms over time is less clear. METHODS: Within a randomized trial on early outpatient COVID-19 therapy testing metformin, ivermectin, and/or fluvoxamine, participants recorded symptoms daily for 14 days. Participants were given a paper symptom diary allowing them to circle the severity of 14 symptoms as none (0), mild (1), moderate (2), or severe (3). This is a secondary analysis of clinical trial data on symptom severity over time using generalized estimating equations comparing those unvaccinated, SARS-CoV-2 vaccinated with primary vaccine series only, or vaccine-boosted. RESULTS: The parent clinical trial prospectively enrolled 1323 participants, of whom 1062 (80%) prospectively recorded some daily symptom data. Of these, 480 (45%) were unvaccinated, 530 (50%) were vaccinated with primary series only, and 52 (5%) vaccine-boosted. Overall symptom severity was least for the vaccine-boosted group and most severe for unvaccinated at baseline and over the 14 days (P < 0.001). Individual symptoms were least severe in the vaccine-boosted group including: cough, chills, fever, nausea, fatigue, myalgia, headache, and diarrhea, as well as smell and taste abnormalities. Results were consistent over delta and omicron variant time periods. CONCLUSIONS: SARS-CoV-2 vaccine-boosted participants had the least severe symptoms during COVID-19 which abated the quickest over time.

An Evaluation of Point-of-Care HbA1c, HbA1c Home Kits, and Glucose Management Indicator: Potential Solutions for Telehealth Glycemic Assessments.

During the COVID-19 pandemic, fewer in-person clinic visits resulted in fewer point-of-care (POC) HbA1c measurements. In this sub-study, we assessed the performance of alternative glycemic measures that can be obtained remotely, such as HbA1c home kits and Glucose Management Indicator (GMI) values from Dexcom Clarity. Home kit HbA1c (n = 99), GMI, (n = 88), and POC HbA1c (n = 32) were collected from youth with T1D (age 9.7 ± 4.6 years). Bland-Altman analyses and Lin's concordance correlation coefficient (ρc) were used to characterize the agreement between paired HbA1c measures. Both the HbA1c home kit and GMI showed a slight positive bias (mean difference 0.18% and 0.34%, respectively) and strong concordance with POC HbA1c (ρc = 0.982 [0.965, 0.991] and 0.823 [0.686, 0.904], respectively). GMI showed a slight positive bias (mean difference 0.28%) and fair concordance (ρc = 0.750 [0.658, 0.820]) to the HbA1c home kit. In conclusion, the strong concordance of GMI and home kits to POC A1c measures suggest their utility in telehealth visits assessments. Although these are not candidates for replacement, these measures can facilitate telehealth visits, particularly in the context of other POC HbA1c measurements from an individual.

Randomized Trial of Metformin, Ivermectin, and Fluvoxamine for Covid-19.

BACKGROUND: Early treatment to prevent severe coronavirus disease 2019 (Covid-19) is an important component of the comprehensive response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. METHODS: In this phase 3, double-blind, randomized, placebo-controlled trial, we used a 2-by-3 factorial design to test the effectiveness of three repurposed drugs - metformin, ivermectin, and fluvoxamine - in preventing serious SARS-CoV-2 infection in nonhospitalized adults who had been enrolled within 3 days after a confirmed diagnosis of infection and less than 7 days after the onset of symptoms. The patients were between the ages of 30 and 85 years, and all had either overweight or obesity. The primary composite end point was hypoxemia (≤93% oxygen saturation on home oximetry), emergency department visit, hospitalization, or death. All analyses used controls who had undergone concurrent randomization and were adjusted for SARS-CoV-2 vaccination and receipt of other trial medications. RESULTS: A total of 1431 patients underwent randomization; of these patients, 1323 were included in the primary analysis. The median age of the patients was 46 years; 56% were female (6% of whom were pregnant), and 52% had been vaccinated. The adjusted odds ratio for a primary event was 0.84 (95% confidence interval [CI], 0.66 to 1.09; P = 0.19) with metformin, 1.05 (95% CI, 0.76 to 1.45; P = 0.78) with ivermectin, and 0.94 (95% CI, 0.66 to 1.36; P = 0.75) with fluvoxamine. In prespecified secondary analyses, the adjusted odds ratio for emergency department visit, hospitalization, or death was 0.58 (95% CI, 0.35 to 0.94) with metformin, 1.39 (95% CI, 0.72 to 2.69) with ivermectin, and 1.17 (95% CI, 0.57 to 2.40) with fluvoxamine. The adjusted odds ratio for hospitalization or death was 0.47 (95% CI, 0.20 to 1.11) with metformin, 0.73 (95% CI, 0.19 to 2.77) with ivermectin, and 1.11 (95% CI, 0.33 to 3.76) with fluvoxamine. CONCLUSIONS: None of the three medications that were evaluated prevented the occurrence of hypoxemia, an emergency department visit, hospitalization, or death associated with Covid-19. (Funded by the Parsemus Foundation and others; COVID-OUT ClinicalTrials.gov number, NCT04510194.).

The Serological Sciences Network (SeroNet) for COVID-19: Depth and Breadth of Serology Assays and Plans for Assay Harmonization.

In October 2020, the National Cancer Institute (NCI) Serological Sciences Network (SeroNet) was established to study the immune response to COVID-19, and "to develop, validate, improve, and implement serological testing and associated technologies" (https://www.cancer.gov/research/key-initiatives/covid-19/coronavirus-research-initiatives/serological-sciences-network). SeroNet is comprised of 25 participating research institutions partnering with the Frederick National Laboratory for Cancer Research (FNLCR) and the SeroNet Coordinating Center. Since its inception, SeroNet has supported collaborative development and sharing of COVID-19 serological assay procedures and has set forth plans for assay harmonization. To facilitate collaboration and procedure sharing, a detailed survey was sent to collate comprehensive assay details and performance metrics on COVID-19 serological assays within SeroNet. In addition, FNLCR established a protocol to calibrate SeroNet serological assays to reference standards, such as the U.S. severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) serology standard reference material and first WHO international standard (IS) for anti-SARS-CoV-2 immunoglobulin (20/136), to facilitate harmonization of assay reporting units and cross-comparison of study data. SeroNet institutions reported development of a total of 27 enzyme-linked immunosorbent assay (ELISA) methods, 13 multiplex assays, and 9 neutralization assays and use of 12 different commercial serological methods. FNLCR developed a standardized protocol for SeroNet institutions to calibrate these diverse serological assays to reference standards. In conclusion, SeroNet institutions have established a diverse array of COVID-19 serological assays to study the immune response to SARS-CoV-2 and vaccines. Calibration of SeroNet serological assays to harmonize results reporting will facilitate future pooled data analyses and study cross-comparisons. IMPORTANCE SeroNet institutions have developed or implemented 61 diverse COVID-19 serological assays and are collaboratively working to harmonize these assays using reference materials to establish standardized reporting units. This will facilitate clinical interpretation of serology results and cross-comparison of research data.

Ultrasensitive detection of salivary SARS-CoV-2 IgG antibodies in individuals with natural and COVID-19 vaccine-induced immunity.

We assessed the feasibility of a highly sensitive immunoassay method based on single molecule array (Simoa) technology to detect IgG and IgA antibodies against SARS-CoV-2 spike protein receptor binding domain (RBD) in saliva from individuals with natural or vaccine-induced COVID-19 immunity. The performance of the method was compared to a laboratory-developed SARS-CoV-2 RBD total antibody enzyme-linked immunosorbent assay (ELISA). Paired serum and saliva specimens were collected from individuals (n = 40) prior to and 2 weeks after receiving an initial prime COVID-19 vaccine dose (Pfizer/BioNTech BNT162b2 or Moderna mRNA-1273). Saliva was collected using a commercially available collection device (OraSure Inc.) and SARS-CoV-2 RBD IgG antibodies were measured by an indirect ELISA using concentrated saliva samples and a Simoa immunoassay using unconcentrated saliva samples. The IgG results were compared with paired serum specimens that were analyzed for total RBD antibodies using the ELISA method. The analytical sensitivity of the saliva-based Simoa immunoassay was five orders of magnitude higher than the ELISA assay: 0.24 pg/mL compared to 15 ng/mL. The diagnostic sensitivity of the saliva ELISA method was 90% (95% CI 76.3-97.2%) compared to 91.7% (95% CI 77.5-98.2%) for the Simoa immunoassay without total IgG-normalization and 100% (95% CI 90.3-100%) for the Simoa immunoassay after total IgG-normalization when compared to the serum ELISA assay. When analyzed using the SARS-CoV-2 RBD IgG antibody ELISA, the average relative increase in antibody index (AI) between the saliva of the post- and pre-vaccinated individuals was 8.7 (AIpost/pre). An average relative increase of 431 pg/mL was observed when the unconcentrated saliva specimens were analyzed using the Simoa immunoassay (SARS-CoV-2 RBD IgGpost/pre). These findings support the suitability of concentrated saliva specimens for the measurement of SARS-CoV-2 RBD IgG antibodies via ELISA, and unconcentrated saliva specimens for the measurement of SARS-CoV-2 RBD IgG and IgA using an ultrasensitive Simoa immunoassay.

Vaccination Against SARS-CoV-2 Is Associated With a Lower Viral Load and Likelihood of Systemic Symptoms.

Background: Data conflict on whether vaccination decreases severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral load. The objective of this analysis was to compare baseline viral load and symptoms between vaccinated and unvaccinated adults enrolled in a randomized trial of outpatient coronavirus disease 2019 (COVID-19) treatment. Methods: Baseline data from the first 433 sequential participants enrolling into the COVID-OUT trial were analyzed. Adults aged 30-85 with a body mass index (BMI) ≥25 kg/m2 were eligible within 3 days of a positive SARS-CoV-2 test and <7 days of symptoms. Log10 polymerase chain reaction viral loads were normalized to human RNase P by vaccination status, by time from vaccination, and by symptoms. Results: Two hundred seventy-four participants with known vaccination status contributed optional nasal swabs for viral load measurement: median age, 46 years; median (interquartile range) BMI 31.2 (27.4-36.4) kg/m2. Overall, 159 (58%) were women, and 217 (80%) were White. The mean relative log10 viral load for those vaccinated <6 months from the date of enrollment was 0.11 (95% CI, -0.48 to 0.71), which was significantly lower than the unvaccinated group (P = .01). Those vaccinated ≥6 months before enrollment did not differ from the unvaccinated with respect to viral load (mean, 0.99; 95% CI, -0.41 to 2.40; P = .85). The vaccinated group had fewer moderate/severe symptoms of subjective fever, chills, myalgias, nausea, and diarrhea (all P < .05). Conclusions: These data suggest that vaccination within 6 months of infection is associated with a lower viral load, and vaccination was associated with a lower likelihood of having systemic symptoms.

Prediction of False-Positive Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Molecular Results in a High-Throughput Open-Platform System.

Widespread high-throughput testing for identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection by RT-PCR has been a foundation in the response to the coronavirus disease 2019 (COVID-19) pandemic. Quality assurance metrics for these RT-PCR tests are still evolving as testing is widely implemented. As testing increases, it is important to understand performance characteristics and the errors associated with these tests. Herein, we investigate a high-throughput, laboratory-developed SARS-CoV-2 RT-PCR assay to determine whether modeling can generate quality control metrics that identify false-positive (FP) results due to contamination. This study reviewed repeated clinical samples focusing on positive samples that test negative on re-extraction and PCR, likely representing false positives. To identify and predict false-positive samples, we constructed machine learning-derived models based on the extraction method used. These models identified variables associated with false-positive results across all methods, with sensitivities for predicting FP results ranging between 67% and 100%. Application of the models to all results predicted a total FP rate of 0.08% across all samples, or 2.3% of positive results, similar to reports for other RT-PCR tests for RNA viruses. These models can predict quality control parameters, enabling laboratories to generate decision trees that reduce interpretation errors, allow for automated reflex testing of samples with a high FP probability, improve workflow efficiency, and increase diagnostic accuracy for patient care.

Good Concordance between Home Kit A1C, Glucose Management Indicator, and Point-of-Care A1C: Potential Solutions to Glycemic Assessment during the SARS CoV-2 Pandemic

Due to the SARS CoV-2 pandemic, fewer in-person clinic visits have resulted in fewer point-of-care (POC) A1c measurements in youth with T1D. Therefore, there is an increased need to use alternate methods to assess A1c, including continuous glucose monitoring-derived Glucose Management Indicator (GMI) and home kit A1c. The University of Minnesota's home kit A1c (n=59), GMI (n=56), and POC A1c (n=16) were collected from youth with T1D (age 10.0 [5.3, 13.0] years, 42% female, and baseline A1c 12.4 ± 2.2%). Matched pairs were used for Bland Altman analyses and Lin's concordance correlation coefficient (pc) to evaluate the agreement between A1c measures. GMI data (up to 90 days) was captured using Dexcom Clarity. In relation to POC A1c, both home kit A1c (panel A) and GMI (panel B) showed a slight positive bias (mean difference 0.13 and 0.22%, respectively). Home kit A1c and GMI showed strong concordance to POC A1c (pc = 0.987 [0.963, 0.995] and 0.930 [0.835, 0.971], respectively). GMI (panel C) also showed a slight positive bias (mean difference 0.26%) and good concordance (pc = 0.803 [0.703, 0.871]) to home kit A1c. These data demonstrate that home kit A1c and GMI show strong concordance with POC A1c. Overall, home kit A1c and GMI may be potential solutions to glycemic assessment for telehealth visits, including during the SARS CoV-2 pandemic.

Initial determination of COVID-19 seroprevalence among outpatients and healthcare workers in Minnesota using a novel SARS-CoV-2 total antibody ELISA.

OBJECTIVES: To avoid the significant risks posed by the use of COVID-19 serology tests with supply chain constraints or poor performance characteristics, we developed an in-house SARS-CoV-2 total antibody test. Our test was compared with three commercial methods, and was used to determine COVID-19 seroprevalence among healthcare workers and outpatients in Minnesota. METHODS: Seventy-nine plasma and serum samples from 50 patients 4-69 days after symptom onset who tested positive by a SARS-CoV-2 PCR method using a nasopharyngeal (NP) swab were used to evaluate our test's clinical performance. Seropositive samples were analyzed for IgG titers in a follow-up assay. Thirty plasma and serum from 12 patients who tested negative by a SARS-CoV-2 PCR method using a nasopharyngeal (NP) swab and 210 negative pre-pandemic serum samples were also analyzed. Among samples from patients > 14 days after symptom onset, the assay had 100% clinical sensitivity and 100% clinical specificity, 100% positive predictive value and 100% negative predictive value. Analytical specificity was 99.8%, indicating minimal cross-reactivity. A screening study was conducted to ascertain COVID-19 seroprevalence among healthcare workers and outpatients in Minnesota. RESULTS: Analysis of serum collected between April 13 and May 21, 2020 indicated a COVID-19 seroprevalence of 2.96% among 1,282 healthcare workers and 4.46% among 2,379 outpatients. CONCLUSIONS: Our in-house SARS-CoV-2 total antibody test can be used to conduct reliable epidemiological studies to inform public health decisions during the COVID-19 pandemic.