Clinical performance of the Elecsys (R) anti-SARS-CoV-2 combined in an algorithm with two specific anti-IgG immunoassays for the evaluation of the serological response of patients with COVID-19 in a population with a high prevalence of infection

Identificador:  imarina:9226192

Handle: https://hdl.handle.net/20.500.11797/imarina9226192

Autores:  Gabaldó-Barrios, X; Iftimie, S; Hernández-Aguilera, A; Pujol, I; Ballester, F; Fernández, L; Cladellas, S; Castro, A; Joven, J; Camps, J; Simó, JM

Resumen:
Background Anti-SARS-CoV-2 antibodies have been used in the study of the immune response in infected patients. However, differences in sensitivity and specificity have been reported, depending on the method of analysis. The aim of the present study was to evaluate the diagnostic accuracy of an algorithm in which a high-throughput automated assay for total antibodies was used for screening and two semi-automated IgG-specific methods were used to confirm the results, and also to correlate the analytical results with the clinical data and the time elapsed since infection. Methods We studied 306 patients, some hospitalized and some outpatients, belonging to a population with a high prevalence of COVID-19. One-hundred and ten patients were classified as SARS-CoV-2 negative and 196 as positive by polymerase chain reaction. Results The algorithm and automated assay alone had a specificity and a positive predictive value of 100%, although the sensitivity and negative predictive value of the algorithm was higher. Both methods showed a good sensitivity from day 11 of the onset of symptoms in asymptomatic and symptomatic patients. The absorbance of the total antibodies was significantly higher in severely symptomatic than in asymptomatic or mildly symptomatic patients, which suggests the antibody level was higher. We found 15 patients who did not present seroconversion at 12 days from the onset of symptoms or the first polymerase chain reaction test. Conclusion This study highlights the proper functioning of algorithms in the diagnosis of the immune response to COVID-19, which can help to define testing strategies against this disease.