key: cord-339568-th2xmhb6 authors: Yan, Meitian; Zheng, Yutong; Sun, Yanmei; Wang, Lan; Luan, Liang; Liu, Jing; Tian, Xiao; Wan, Nan title: Analysis of the diagnostic value of serum specific antibody testing for coronavirus disease 2019 date: 2020-06-27 journal: J Med Virol DOI: 10.1002/jmv.26230 sha: doc_id: 339568 cord_uid: th2xmhb6 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 4,643 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 (SARS‐CoV‐2) infection has become an important laboratory method for the diagnosis of COVID‐19. However, at present, little research on these specific antibodies has been conducted. In this study, retrospective analysis was used to explore the dynamic changes of serum IgM and IgG antibody and factors affecting diagnostic efficacy, so as to provide a theoretical basis for clinical diagnosis and treatment. This article is protected by copyright. All rights reserved. In December 2019, patients with coronavirus disease 2019 began to appear in the city of Wuhan, Hubei Province, China 1-3 . The epidemic rapidly spread to many other regions within China and then to regions across the globe. Although the situation in China is currently under control, the pandemic continues to spread in other countries, increasing the risk of overseas import of the disease to China. COVID-19 is caused by a novel coronavirus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) 4 This article is protected by copyright. All rights reserved. acid by reverse transcription polymerase chain reaction (RT-PCR) is the gold standard for the diagnosis of SARS-CoV-2 infection, this method is complex and time-consuming, with detection results easily affected by factors such as collection time, sample type, and sample preservation, which increases the risk of false-negative 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 Seventh 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 severe acute respiratory syndrome coronavirus (SARS-CoV) 6.7 . Serum IgM antibodies against SARS-CoV can be detected 3-6 days after infection, but levels rapidly decrease thereafter. Conversely, IgG antibodies appear later on, approximately 8 days after the onset of symptoms, with levels increasing over the course of infection and remaining high for an extended period 8 . Therefore, it has been speculated that the dynamic change processes of SARS-CoV-2 antibodies may be similar to that of SARS-CoV. To investigate this, the dynamic changes of Statistical methods Software SPSS26.0 was used for data analysis. Non-normal variables were expressed as medians (Q1,Q3) and were analyzed by the Mann-Whitney U test. Counting data were compared using the chi-squared 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. Among the 802 patients, 58.48% were female with a median age of 63 years (IQR18, range: 13-99 years). The median times for the following factors were follows: virus shedding, 23 days (IQR22, range: 2-61 days); hospitalization,13 days (IQR10, range: 2-55 days); disease duration, 52 days (IQR21, range: 9-101 days). 77.81% of patients had symptomatic infections, the main symptoms being fever (62.84%), cough (60.35%), and fatigue (43.39%). 53.74% of patients had at least one comorbidity, mainly hypertension (37.53%), diabetes (17.21%), or chronic heart disease (13.47%). On admission, 20.25% of the patients had decreased lymphocyte counts, and 64.47%, 17.78%, and 7.37% of patients had elevated D-dimer, C-reactive protein, and white blood cell counts, This article is protected by copyright. All rights reserved. respectively. Patients with severe infections and deaths accounted for 29.05% and 1% of cases, respectively (Table 1) . This article is protected by copyright. All rights reserved. The positive rates of IgM, IgG, and IgM or/and IgG antibodies were 28.55% This article is protected by copyright. All rights reserved. were divided into non-comorbidity (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 non-comorbidity group (47.16%). The positive rate of IgG antibodies in the comorbidity group (53.29%) was also higher than that in the non-comorbidity group (46.71%), but the difference was not statistically significant (p > 0.05). 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 < 0.05). To classify the severity of 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 non-severe group (71.62% and 71.14%, respectively) were higher than that in the severe group (28.38% and 28.86%, respectively), but these differences were not statistically significant (p > 0.05). sex, comorbidity status, symptoms, and severity of illness IgG antibody levels in compared groups varied as follows: significantly higher in males than females, 10.75 S/co(IQR23.79) and 6.82 S/co(IQR17.48), respectively; significantly higher in patients with comorbidity than patients without, 9.84 S/co(IQR23.53) and 6.58 S/co(IQR17.89), respectively; significantly higher in symptomatic patients than asymptomatic patients, 8 .48 S/co(IQR20.70) and 2.96 S/co(IQR12.48), respectively; significantly higher in the severe patient group than non-severe patient group, 11.05 S/co(IQR24.65) and 7.04 S/co(IQR18.50), respectively. All differences were statistically significant (p < 0.05; Figure 3 ). levels, and total protein levels on admission IgG antibody levels correlated positively with age (p < 0.01), negatively with albumin levels (p < 0.05), and showed no correlation with total protein levels (p > 0.05; Figure 4 ). 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, diabetes, or chronic heart disease, which indicates that the elderly and patients with comorbidity were more susceptible to COVID-19. While 65.85% of patients had fevers, 34.16% of the patients had no fever during the course of disease, highlighting the importance of testing suspected cases even in the absence of a fever to prevent missed diagnosis. Other than fevers, the most common symptoms were coughs and fatigue, which are similar to some SARS-CoV infection symptoms 11 . However, other SARS-CoV infection symptoms, such as such as sore throat, runny nose (upper respiratory tract infection symptoms), vomiting, and diarrhea were rarely seen, which indicates that SARS-CoV-2 target cells mainly exist in the lower respiratory tract. Upon admission to hospital, 20.25% of the patients displayed reduced lymphocyte counts, which indicates that SARS-CoV-2 may attack lymphocytes to reduce the immunity of infected individuals, allowing SARS-CoV-2 to replicate in large quantities in the body. This study also found that 17.78%, 64.47%, and 7.37% of patients had elevated C-reactive protein, D-dimer, and white blood cells, respectively. It is well known that C-reactive protein is an indicator of inflammatory response and increases during bacterial or viral infections. Also, D-dimer is an indicator of blood agglutination. Studies have shown that blood hypercoagulability is Accepted Article associated with patients with severe infections, particularly those with respiratory distress syndrome. The level of D-dimer will continue to increase in severe patients with respiratory distress syndrome. 9 . Lan et al. 12 This article is protected by copyright. All rights reserved. are negative; the continued monitoring of nucleic acid and antibody levels for several days is necessary avoid missed diagnosis. On admission, the positive rate of IgG antibodies in non-severe patients was significantly higher than that in severe patients (p < 0.05). 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 COVID-19 patients. 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, 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 of nucleic acid testing. The improved diagnostic efficiency of COVID-19 by this combined approach could have important clinical applications. Severe acute respiratory syndrome-related coronavirus: the species and its viruses -A statement of the Coronavirus Study Group Clinical characteristics of 2019 novel coronavirus infection in China. medRxiv A novel coronavirus from patients with pneumonia in China The proximal origin of SARS-CoV-2 Development and Clinical Application of A Rapid IgM-IgG Combined Antibody Test for SARS-CoV-2 Infection Diagnosis A pneumonia outbreak associated with a new coronavirus of probable bat origin Measures for diagnosing and treating infections by a novel coronavirus responsible for a pneumonia outbreak originating in Wuhan Production of specific antibodies against SARS-coronavirus nucleocapsid protein without cross reactivity with human coronaviruses 229E and OC43 Clinical features of patients infected with 2019 novel coronavirus in wuhan The Novel Coronavirus Originating in Wuhan, China: Challenges for Global Health Governance A major outbreak of severe acute respiratory syndrome in Hong Kong Positive RT-PCR Test Results in Patients Recovered From COVID-19 This study was supported by research grants from the Natural Science This article is protected by copyright. All rights reserved. The authors declare that there are no conflict of interests. MT and NW contributed to data analysis, technical graphics, and writing the paper. MT, NW, YZ, YS, LW and LL contributed to data collection and graphics processing. JL and XT contributed to editing the paper.