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. 2021 Jul 7;6(4):942-952.
doi: 10.1093/jalm/jfab014.

Performance of 4 Automated SARS-CoV-2 Serology Assay Platforms in a Large Cohort Including Susceptible COVID-19-Negative and COVID-19-Positive Patients

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Performance of 4 Automated SARS-CoV-2 Serology Assay Platforms in a Large Cohort Including Susceptible COVID-19-Negative and COVID-19-Positive Patients

Matthew D Ward et al. J Appl Lab Med. .

Abstract

Background: Anti-SARS-CoV-2 serological responses may have a vital role in controlling the spread of the disease. However, the comparative performance of automated serological assays has not been determined in susceptible patients with significant comorbidities.

Methods: In this study, we used large numbers of samples from patients who were negative (n = 2030) or positive (n = 112) for COVID-19 to compare the performance of 4 serological assay platforms: Siemens Healthineers Atellica IM Analyzer, Siemens Healthineers Dimension EXL Systems, Abbott ARCHITECT, and Roche cobas.

Results: All 4 serology assay platforms exhibited comparable negative percentage of agreement with negative COVID-19 status ranging from 99.2% to 99.7% and positive percentage of agreement from 84.8% to 87.5% with positive real-time reverse transcriptase PCR results. Of the 2142 total samples, only 38 samples (1.8%) yielded discordant results on one or more platforms. However, only 1.1% (23/2030) of results from the COVID-19-negative cohort were discordant. whereas discordance was 10-fold higher for the COVID-19-positive cohort, at 11.3% (15/112). Of the total 38 discordant results, 34 were discordant on only one platform.

Conclusions: Serology assay performance was comparable across the 4 platforms assessed in a large population of patients who were COVID-19 negative with relevant comorbidities. The pattern of discordance shows that samples were discordant on a single assay platform, and the discordance rate was 10-fold higher in the population that was COVID-19 positive.

Keywords: COVID-19; SARS-CoV-2; automated platforms; serology.

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