Measurement of SARS-CoV-2 Antibody Titers Improves the Prediction Accuracy of COVID-19 Maximum Severity by Machine Learning in Non-Vaccinated Patients

• Published in: Frontiers in immunology Vol. 13; p. 811952
• Main Authors: Kurano, Makoto, Ohmiya, Hiroko, Kishi, Yoshiro, Okada, Jun, Nakano, Yuki, Yokoyama, Rin, Qian, Chungen, Xia, Fuzhen, He, Fan, Zheng, Liang, Yu, Yi, Jubishi, Daisuke, Okamoto, Koh, Moriya, Kyoji, Kodama, Tatsuhiko, Yatomi, Yutaka
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 21.01.2022
• Subjects: Antibodies, Viral - blood; Antibody Formation - immunology; Coronavirus Nucleocapsid Proteins - immunology; COVID-19; COVID-19 - blood; COVID-19 - immunology; COVID-19 - pathology; COVID-19 Vaccines - blood; COVID-19 Vaccines - immunology; Humans; IgA; IgG; IgM; Immunoglobulin A - blood; Immunoglobulin G - blood; Immunoglobulin M - blood; Immunology; Machine Learning; Protein Domains - immunology; SARS-CoV-2 - immunology; severity; Severity of Illness Index; Spike Glycoprotein, Coronavirus - immunology; Time Factors; Vaccination; Vaccination Hesitancy; COVID-19; severity; IgA; spike protein; IgG; nucleocapsid protein; machine learning; IgM

Numerous studies have suggested that the titers of antibodies against SARS-CoV-2 are associated with the COVID-19 severity, however, the types of antibodies associated with the disease maximum severity and the timing at which the associations are best observed, especially within one week after sympt...