Big Data analysis to evaluate the clinical utility of IgM anti SARS-CoV-2 determination: The Modena experience

ABSTRACT

Introduction: since the scarce diagnostic accuracy of specific circulating antibodies for SARS-CoV-2, we aimed to assess the clinical utility of IgM detection in SARS-CoV-2 using the Big Data analysis. Methods: this is a retrospective study;all the blood samples collected between March and September 2020 were processed using a lateral flow immunoassay (LFIA) kit for IgG and IgM antybody testing. Positives results were tested again using a chemiluminescent method. Subjects confirmed with a positive result were contacted for a molecular test. Results: more than 69 000 serological tests (from 42 911 subjects) were performed. 94.5% (40 559/42 911) of subjects had negative results for both IgG and IgM. 1.5% (n = 640) subjects had both IgG and IgM positive results, and viral RNA research confirmed positivity in 16% (85/533). Among subjects with IgG negative and IgM positive results (n=271), a positivity was confirmed in 1% (4/270). Conversely, in subjects with IgG positive and IgM negative results, a positivity was confirmed in 8% (97/1 215). Therefore, the analysis suggests that up to 98% of serological test results of IgM positivity and IgG negativity are false positive. Discussion: the study, based on Big Data analysis application, proved the scarce clinical utility of IgM detection in COVID-19 management, and underlines the responsibility of laboratory professionals in highlighting the limitations of the serological tests also due to uncertainty in their interpretation.