Specificity and Confirmation of SARS-CoV-2 Serological Test Methods in Emergency Department Populations across the United States.

BACKGROUND: Serological testing for SARS-CoV-2 is integral for understanding prevalence of disease, tracking of infections, confirming humoral response to vaccines, and determining timing and efficacy of boosters. The study objective was to compare the specificity of serology assays in emergency department populations across the United States in 2019 (pre-pandemic) and early 2020, incorporating an automated confirmatory assay. METHODS: Patient specimens (n = 1954) were from 4 regions in the United States: New York, NY; Milwaukee, WI; Miami, FL; and Los Angeles, CA. Specimens were tested with SARS-CoV-2 anti-spike receptor-binding domain assays: SARS-CoV-2 IgG on the Abbott Alinity i (AdviseDx SARS-Cov-2 IgG II) and Beckman Coulter Access 2 (SARS-CoV-2 IgG II), and SARS-CoV-2 IgM on the Abbott Alinity i (AdviseDx SARS-CoV-2 IgM). Reactive samples were tested with a research use only angiotensin-converting enzyme 2 binding inhibition assay (Abbott ARCHITECT) for confirmation of SARS-CoV-2 neutralizing antibodies. Assay specificity was determined and comparisons performed with Fisher's exact test. RESULTS: Overall SARS-CoV-2 IgG specificity was 99.28% (95% confidence interval, 98.80%-99.61%), 99.39% (98.93%-99.68%), and 99.44% (98.99%-99.72%) for SARS-CoV-2 IgG by Abbott and Beckman, and SARS-CoV-2 IgM, respectively. Overall agreement for the two IgG assays was 99.28% (range for the 4 sites: 98.21% to 100%). There were no specificity differences between assays or sites. CONCLUSIONS: The specificity of the serological assays evaluated in a large, diverse emergency department population was >99% and did not vary by geographical site. A confirmatory algorithm with an automated pseudo-neutralization assay allowed testing on the same specimen while reducing the false positivity rate and increasing the value of serology screening methods.

Specificity and Confirmation of SARS-CoV-2 Serological Test Methods in Emergency Department Populations Across the United States in 2019 and Early 2020.

BACKGROUND: Serological testing for SARS-CoV-2 is integral for understanding prevalence of disease, tracking of infections, confirming humoral response to vaccines, and determining timing and efficacy of boosters. The study objective was to compare the specificity of serology assays in emergency department populations across the United States in 2019 (pre-pandemic) early 2020 incorporating an automated confirmatory assay. METHODS: Patient specimens (n = 1954) were from four regions in the United States: New York, NY; Milwaukee, WI; Miami, FL; and Los Angeles, CA. Specimens were tested with SARS-CoV-2 anti-spike receptor binding domain assays: SARS-CoV-2 IgG on the Abbott Alinity i (AdviseDx SARS-Cov-2 IgG II) and Beckman Coulter Access 2 (SARS-CoV-2 IgG II), and SARS-CoV-2 IgM on the Abbott Alinity i (AdviseDx SARS-CoV-2 IgM). Reactive samples were tested with a research use only ACE2 binding inhibition assay (Abbott ARCHITECT) for confirmation of SARS-CoV-2 neutralizing antibodies. Assay specificity was determined and comparisons performed with Fisher's Exact Test. RESULTS: Overall SARS-CoV-2 IgG specificity was 99.28% (95% confidence interval: 98.80%-99.61%), 99.39% (98.93%-99.68%), and 99.44% (98.99%-99.72%) for SARS-CoV-2 IgG by Abbott and Beckman, and SARS-CoV-2 IgM, respectively. Overall agreement for the two IgG assays was 99.28% (range for the four sites: 98.21%-100%). There were no specificity differences between assays or sites. CONCLUSIONS: The specificity of the serological assays evaluated in a large diverse emergency department population was >99% and did not vary by geographical site. A confirmatory algorithm with an automated pseudo-neutralization assay allowed testing on the same specimen while reducing the false positivity rate and increasing the value of serology screening methods.

SARS-CoV-2 Anti-Spike IgG Antibody and ACE2 Receptor Binding Inhibition Levels among Breakthrough Stage Veteran Patients.

SARS-CoV-2 mRNA vaccines have been critical to curbing pandemic COVID-19; however, a major shortcoming has been the inability to assess levels of protection after vaccination. This study assessed serologic status of breakthrough infections in vaccinated patients at a Veterans Administration medical center from June through December 2021 during a SARS-CoV-2 delta variant wave. Breakthrough occurred mostly beyond 150 days after two-dose vaccination with a mean of 239 days. Anti-SARS-CoV-2 spike (S) IgG levels were low at 0 to 2 days postsymptoms but increased in subjects presenting thereafter. Population measurements of anti-S IgG and angiotensin converting enzyme-2 receptor (ACE2-R) binding inhibition among uninfected, vaccinated patients suggested immune decay occurred after 150 days with 62% having anti-S IgG levels at or below 1,000 AU comparable with breakthrough patients at 0 to 2 days postsymptom onset. In contrast, vaccination after resolved infection conferred robust enduring anti-S IgG levels (5,000 to >50,000 AU) with >90% ACE2-R binding inhibition. However, monoclonal antibody (MAb)-treated patients did not benefit from their prior infection suggesting impaired establishment of B cell memory. Analysis of boosted patients confirmed the benefit of a third vaccine dose with most having anti-S IgG levels above 5,000 AU with >90% ACE2-R binding inhibition, but a subset had levels <5,000 AU. Anti-S IgG levels >5,000 AU were associated with >90% ACE2-R binding inhibition and no documented breakthrough infections, whereas levels falling below 5,000 AU and approaching 1,000 AU were associated with breakthrough infections. Thus, quantitative antibody measurements may provide a means to guide vaccination intervals for the individual. IMPORTANCE Currently, clinicians have no guidance for the serologic assessment of SARS-Cov-2 postvaccination status regarding protection and risk of infection. Vaccination and boosters are administered blindly without evaluation of need or outcome at the individual level. The recent development of automated quantitative assays for anti-SARS-CoV-2 spike protein IgG antibodies permits accurate measurement of humoral immunity in standardized units. Clinical studies, such as reported here, will help establish protective antibody levels allowing identification and targeted management of poor vaccine responders and vaccinated subjects undergoing immune decay.

Anti-SARS-CoV-2 IgM improves clinical sensitivity early in disease course.

INTRODUCTION: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is diagnosed by molecular-based detection of SARS-CoV-2 RNA. Serologic testing detects antibodies specific to SARS-CoV-2 and IgM specifically may serve as an adjunct test to PCR early in disease. We evaluated the Abbott anti-SARS-CoV-2 IgM and IgG assays along with DiaSorin anti-SARS-CoV-2 IgG and Roche anti-SARS-CoV-2 Total. METHODS: Specimens from 175 PCR-positive patients and 107 control specimens were analyzed using Abbott IgM and IgG, DiaSorin IgG, and Roche Total (IgA, IgG, IgM) assays. Sensitivity, specificity, cross-reactivity, concordance between assays, trends over time, positive predictive value (PPV), and negative predictive value (NPV) were determined. RESULTS: Abbott IgM sensitivity was 63.6% at 0 days post-PCR positivity, 76.5% at 1-5d, 76.3% at 6-14d, 85.2% at 15-30d, and 63.6% at > 30d. All assays exhibited highest sensitivity 15-30d post-PCR positivity (83.3-85.2%). Combining Abbott IgM and IgG improved sensitivity by 22.7% compared to IgG alone when tested 0d post-PCR positivity. All assays had a specificity of 100% and only Abbott IgG exhibited cross-reactivity (anti-dsDNA). Cohen's kappa varied between 0.86 and 0.93. Time to seroconversion from PCR positivity was lowest for Abbott IgM and highest for Abbott IgG. NPV was highest for Abbott IgM < 14 days post-PCR positivity and Abbott IgG ≥ 14 days. CONCLUSION: The Abbott IgM assay exhibited the earliest response and greatest signal in most patients evaluated for serial sampling and had the highest NPV < 14 days post-PCR positivity, suggesting its potential utility as an adjunct test to PCR early in disease course.

A novel Sigma metric encompasses global multi-site performance of 18 assays on the Abbott Alinity system.

OBJECTIVES: The Abbott Alinity family of chemistry and immunoassay systems recently launched with early adopters contributing imprecision and bias data, which was consolidated to assess the performance of Alinity assays across multiple sites using the Sigma metric. Multi-site Sigma metrics were determined for 3 ion-selective electrodes, 12 photometric assays, and 3 immunoassays across 11 independent laboratory sites in 9 countries. METHODS: Total allowable error (TEa) goals followed a previously defined hierarchy that used CLIA as the primary goal. Bias was calculated against the Abbott ARCHITECT system using Passing-Bablok regression analysis using individual site data or pooled aggregate data. Sigma metrics were calculated as (%TEa - |% bias|)/%CV. For individual-site analysis, the Sigma metrics for each assay were compared using the individual-site and the pooled biases. For multi-site analysis, the average CV and the pooled bias were used to generate a Pooled Sigma metric encompassing the global performance for a given assay. RESULTS: A total of 97 individual-site and 18 Pooled Sigma metrics were calculated for available assays. Individual Sigma metrics varied across sites, with 90% of assays performing 4 Sigma or higher, and 17 of 18 Pooled Sigma metrics indicated performance greater than 4 Sigma. Sigma metrics were significantly improved in 16 assays when using pooled bias rather than individual-site bias. CONCLUSIONS: This multi-center study applies a novel application of Sigma metrics to the first Alinity users and reveals analytical performance of greater than 4 Sigma for vast majority of assays. Laboratories with limited resources can leverage larger data sets for Pooled Sigma metric analysis, providing a tool to assess the consistency of analytical performance from multiple sites.