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

Xinjie Li; Ling Pang; Yue Yin; Yuqi Zhang; Shuyun Xu; Dong Xu; Tao Shen

doi:10.3390/v14010080

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

Viruses. 2022 Jan 2;14(1):80. doi: 10.3390/v14010080.

Authors

Xinjie Li¹, Ling Pang², Yue Yin¹, Yuqi Zhang¹, Shuyun Xu³, Dong Xu², Tao Shen¹

Affiliations

¹ Department of Microbiology and Infectious Disease Center, School of Basic Medical Sciences, Peking University, Beijing 100191, China.
² Department and Institute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
³ Department of Respiratory and Critical Care Medicine, Key Laboratory of Pulmonary Diseases of Health Ministry, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.

Abstract

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^high, n = 153) and low (NAb^low, n = 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^low group, a larger proportion of the NAb^high group received corticosteroids (38.8% vs. 22.4%, p = 0.002) and IVIG therapy (26.5% vs. 16.3%, p = 0.033), and presented with diabetes comorbidity (25.2% vs. 12.2%, p = 0.004); high blood urea (median (IQR): 4.8 (3.7, 6.1) vs. 3.9 (3.5, 5.4) mmol/L; p = 0.017); CRP (31.6 (4.0, 93.7) vs. 16.3 (2.7, 51.4) mg/L; p = 0.027); PCT (0.08 (0.05, 0.17) vs. 0.05 (0.03, 0.09) ng/mL; p = 0.001); SF (838.5 (378.2, 1533.4) vs. 478.5 (222.0, 1133.4) μg/L; p = 0.035); and fibrinogen (5.1 (3.8, 6.4) vs. 4.5 (3.5, 5.7) g/L; p = 0.014) levels, but low SpO₂ levels (96.0 (92.0, 98.0) vs. 97.0 (94.0, 98.0)%; p = 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.

Keywords: coronavirus disease 2019 (COVID-19); corticosteroids; diabetes; neutralizing antibody (NAb); severe acute respiratory syndrome coronavirus (SARS-CoV-2).

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aged
Antibodies, Neutralizing / blood*
Antibodies, Viral / blood
COVID-19 / diagnosis
COVID-19 / immunology*
COVID-19 / therapy
China
Convalescence*
Female
Hospitalization
Humans
Logistic Models
Male
Middle Aged
ROC Curve
SARS-CoV-2 / immunology*

Substances

Antibodies, Neutralizing
Antibodies, Viral

Abstract

Publication types

MeSH terms

Substances

Grants and funding