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Analysis of the diagnostic value of serum specific antibody testing for coronavirus disease 2019

Abstract The coronavirus disease 2019 (COVID‐19) pandemic has spread to various regions worldwide. As of 27 April 2020, according to real‐time statistics released by the World Health Organization, there have been 84 341 confirmed cases and 4643 deaths in China, with more than 2 979 484 confirmed cases and 206 450 deaths outside China. The detection of antibodies produced during the immune response to severe acute respiratory syndrome coronavirus 2 infections has become an important laboratory method for the diagnosis of COVID‐19. However, at present, a little research on these specific antibodies has been conducted. In this study, a retrospective analysis was used to explore the dynamic changes of serum immunoglobulin M (IgM) and IgG antibody and factors affecting diagnostic efficacy, so as to provide a theoretical basis for clinical diagnosis and treatment.

type, and sample preservation, which increase the risk of falsenegative results. 5 Furthermore, this method is unable to meet the principles of early detection, early isolation, and early treatment, and is, therefore, not conducive to the prevention and control of the epidemic. As a product of the immune response to infection, antibody detection has the advantage of being easier and more convenient to conduct, more efficient, easier to preserve samples and having lower laboratory and personnel requirements. Diagnosis and treatment plan (trial 7th edition) clearly proposed that antibody detection is an important laboratory method for the diagnosis of COVID-19. However, as SARS-CoV-2 is a novel virus, a thorough understanding of the dynamic changes of these antibodies in patients and influencing factors is required. SARS-CoV-2 belongs to the β-coronavirus genus, sharing high-sequence similarity (87.9% and 98.7%) with the SARS-CoV. 6

| Antibody and nucleic acid detection
Fasting venous blood (2-5 mL) was centrifuged, and the upper serum was separated and stored at −20°C. Serum IgM and IgG antibodies were quantitatively detected by the Axceed 260 (Bioscience, Tianjin, China) magnetic particle-based chemiluminescence immunoanalyzer.
Chemiluminescence signal-to-cutoff (S/co) values showed that S/co less than 1 was regarded as negative for the antibody and S/co greater than 1 as positive. Nasopharyngeal swab samples were collected and nucleic acid detection using model 7500 PCR gene amplification instrument (AMI). C t values of greater than 40 were considered negative for SARS-CoV-2 and values less than 40 were positive.

| Statistical methods
Software SPSS26.0 was used for data analysis. Nonnormal variables were expressed as medians (Q1 and Q3) and were analyzed by the Mann-Whitney U test. Counting data were compared using the χ 2 test. Correlation analysis was performed using the Spearman correlation coefficient. Data consistency was measured by calculating the Kappa coefficient using the Kappa consistency test. GraphPad Prism 8.0 was used to produce charts.  The patients were divided into female (n = 469) and male (n = 333) groups. On admission, the positive rates of IgM antibodies in the female and male groups were 53.71% and 46.29%, respectively, and the positive rates of IgG antibodies in these groups were 58.86% and 41.14%, respectively. Although the positive rates of IgM and IgG detection in the female group were higher than those in the male group on admission, these differences were not statistically significant (P > .05).

| The relationship between the positive rates of IgM and IgG antibodies on admission and patient comorbidity status
The patients were divided into noncomorbidity (n = 371) and comorbidity (n = 431) groups. The positive rate of IgM antibodies in the comorbidity group (52.84%) was higher than that in the noncomorbidity group (47.16%). The positive rate of IgG antibodies in the comorbidity group (53.29%) was also higher than that in the noncomorbidity group (46.71%), but the difference was not statistically significant (P > .05).

| The relationship between the positive rates of IgM and IgG antibodies on admission and whether the patient had a symptomatic infection
The patients were divided into asymptomatic (n = 178) and symptomatic (n = 624) infection groups. The positive rates of IgM and IgG antibodies in the symptomatic infection group (95.63% and 95.57%, respectively) were significantly higher than those in the asymptomatic infection group (4.37% and 4.43%, respectively), but only the difference between IgG detection was statistically significant (P < .05).

| The relationship between the positive rate of IgM and IgG antibodies on admission and the severity of illness
To classify the severity of the illness of participants, those displaying mild and normal symptoms were classified as the "non-severe group," and severe and critically ill patients were classified as the "severe group." The positive rates of IgM and IgG antibodies in the nonsevere group (71.62% and 71.14%, respectively) were higher than those in the severe group (28.38% and 28.86%, respectively), but these differences were not statistically significant (P > .05).

| The relationship between IgG antibody levels and age, albumin levels, and total protein levels on admission
IgG antibody levels correlated positively with age (P < .01), negatively with albumin levels (P < .05), and showed no correlation with total protein levels (P > .05; Figure 4).

| DISCUSSION
The COVID-19 epidemic has rapidly developed into a serious global situation, threatening the physical and mental health of millions across the globe. 9,10 The median age of the 802 patients included in this study was 63 years, with slightly more females than men. 53.74% of the patients had at least one comorbidity, such as hypertension, syndrome. The level of D-dimer will continue to increase in severe patients with respiratory distress syndrome. 9 Lan et al 12 found that some patients who met the discharge criteria were repositive for nucleic acid a few days after discharge. The positive rate of IgG antibodies in patients with asymptomatic infections was significantly lower than that in patients with symptomatic infections, the positive rate of which was less than 5%. It is speculated that asymptomatic infections may affect IgG antibody conversion. Therefore, asymptomatic patients with a clear history of the disease should not be deemed clear of infection even if the antibody and nucleic acid screenings are negative; the continued monitoring of nucleic acid and antibody levels for several days is necessary to avoid missed diagnosis. On admission, the positive rate of IgG antibodies in nonsevere patients was significantly higher than that in severe patients (P < .05). This implies that the severity of the disease affects the conversion of IgG antibodies. If the IgG antibody level is high, the level of albumin will decrease accordingly. As albumin is often used as an indicator of the body's nutritional status, this decrease suggests that the increased antibody production during infection may consume nutrients. IgG is a protective antibody and it may, therefore, be necessary to closely monitor albumin levels of patients with COVID-19. If the albumin level decreases, intervention may be necessary to ensure the body can produce enough antibodies to battle and recover from the disease. The results of this study also showed that sex, comorbidity status, symptoms, the severity of illness, and age all affected the levels of IgG antibodies; these factors will all likely influence the accuracy of diagnosis.
In this study, we described the dynamic changes of antibody seroconversion and discussed factors that could affect the diagnostic efficacy of antibodies. Antibody detection can be used as a supplementary diagnostic tool for nucleic acid testing. The improved diagnostic efficiency of COVID-19 by this combined approach could have important clinical applications.