Patient and Clinical Factors at Admission Affect the Levels of Neutralizing Antibodies Six Months after Recovering from COVID-19

• Published in: Viruses 2022-01, Vol.14 (1), p.80
• Main Authors: Li, Xinjie, Pang, Ling, Yin, Yue, Zhang, Yuqi, Xu, Shuyun, Xu, Dong, Shen, Tao
• Format: Article
• Language: English
• Subjects: Aged; Antibodies; Antibodies, Neutralizing - blood; Antibodies, Viral - blood; Antigens; China; Convalescence; coronavirus disease 2019 (COVID-19); Coronaviruses; Corticosteroids; COVID-19; COVID-19 - diagnosis; COVID-19 - immunology; COVID-19 - therapy; diabetes; Diabetes mellitus; Female; Fibrinogen; Hospitalization; Hospitals; Humans; Immunoglobulins; Intravenous administration; Logistic Models; Male; Middle Aged; neutralizing antibody (NAb); Oxygen saturation; Pandemics; Patients; Plasma; Prediction models; ROC Curve; SARS-CoV-2 - immunology; severe acute respiratory syndrome coronavirus (SARS-CoV-2); Severe acute respiratory syndrome coronavirus 2; Statistical analysis
• ISSN: 1999-4915; 1999-4915
• DOI: 10.3390/v14010080

The rate of decline in the levels of neutralizing antibodies (NAbs) greatly varies among patients who recover from Coronavirus disease 2019 (COVID-19). However, little is known about factors associated with this phenomenon. The objective of this study is to investigate early factors at admission that can influence long-term NAb levels in patients who recovered from COVID-19. A total of 306 individuals who recovered from COVID-19 at the Tongji Hospital, Wuhan, China, were included in this study. The patients were classified into two groups with high (NAb , = 153) and low (NAb , = 153) levels of NAb, respectively based on the median NAb levels six months after discharge. The majority (300/306, 98.0%) of the COVID-19 convalescents had detected NAbs. The median NAb concentration was 63.1 (34.7, 108.9) AU/mL. Compared with the NAb group, a larger proportion of the NAb group received corticosteroids (38.8% vs. 22.4%, = 0.002) and IVIG therapy (26.5% vs. 16.3%, = 0.033), and presented with diabetes comorbidity (25.2% vs. 12.2%, = 0.004); high blood urea (median (IQR): 4.8 (3.7, 6.1) vs. 3.9 (3.5, 5.4) mmol/L; = 0.017); CRP (31.6 (4.0, 93.7) vs. 16.3 (2.7, 51.4) mg/L; = 0.027); PCT (0.08 (0.05, 0.17) vs. 0.05 (0.03, 0.09) ng/mL; = 0.001); SF (838.5 (378.2, 1533.4) vs. 478.5 (222.0, 1133.4) μg/L; = 0.035); and fibrinogen (5.1 (3.8, 6.4) vs. 4.5 (3.5, 5.7) g/L; = 0.014) levels, but low SpO levels (96.0 (92.0, 98.0) vs. 97.0 (94.0, 98.0)%; = 0.009). The predictive model based on Gaussian mixture models, displayed an average accuracy of 0.7117 in one of the 8191 formulas, and ROC analysis showed an AUC value of 0.715 (0.657-0.772), and specificity and sensitivity were 72.5% and 67.3%, respectively. In conclusion, we found that several factors at admission can contribute to the high level of NAbs in patients after discharge, and constructed a predictive model for long-term NAb levels, which can provide guidance for clinical treatment and monitoring.