ABSTRACT
Background: In 2020 the current outbreak of Coronavirus Disease 2019(COVID-19) has constituted a global pandemic. But the question about the immune mechanism of patients with COVID-19 is unclear and cause particular concern to the world. Here, we launched a follow-up analysis of antibodies against SARS-CoV-2 of 192 COVID-19 patients, aiming to depict a kinetics profile of antibodies against SARS-CoV-2 and explore the related factors of antibodies expression against SARS-CoV-2 in COVID-19 patient. Methods: A total of 192 COVID-19 patients enrolled in the designated hospital of Guangzhou , Guangzhou Eighth People's Hospital, from January to February 2020 were selected as the study cohort. A cohort of 130 COVID-19 suspects who had been excluded from SARS-CoV-2 infected by negative RT-PCR result and 209 healthy people were enrolled in this study. Detection of IgM and IgG against SARS-CoV-2 were performed by Chemiluminescence immunoassay in different groups . Results: It has been found that the seroconversion time of IgM against SARS-CoV-2 in most patients was 5-10 days after the symptoms onset , and then rose rapidly, reaching a peak around 2 to 3 weeks, and the median peak concentration was 2.705 AU / mL. The peak of IgM maintained within one week, and then enters the descending channel. IgG seroconverted later than or synchronously with IgM, reaching peaks around 3 to 4 weeks.The median peak concentration was 33.998AU / ml,which was higher than that of IgM . IgM titers begins to gradually decrease after reaching the peak in the 4th week, after the 8th week, a majority of IgM in patient's serum started to turn negative. On the contrary, titers of IgG began to decline slightly after the fifth week, and more than 90% of results of patients were positive after 8 weeks. Additionally, the concentration of antibodies positively correlated with the severity of the disease and the duration of virus exist in host. Conclusion: We depict a kinetics profile of antibodies against SARS-CoV-2 in COVID-19 patients and found out that the levels of antibodies were related to the disease severity,age, gender and virus clearance or continuous proliferation of COVID-19 patients.
Subject(s)
COVID-19 , Severe Acute Respiratory Syndrome , HallucinationsABSTRACT
Objective@#To explore the Expressions of multiple inflammation markers in the patients with 2019 novel coronavirus pneumonia (COVID-19) and their clinical values, and to provide theoretical basis for clinical diagnosis and treatment.@*Methods@#A total of 164 patients, diagnosed with COVID-19 and admitted to Guangzhou Eighth People's Hospital from January to February 2020, were selected as the research group and divided into three groups (ordinary, severe, and critically severe pneumonia) according to the disease severity. Meandwhile 66 non-infected patients during the same period were selected as negative control group. The expressions of WBC, LYM, CRP, SAA, and PCT were retrospective studied and compared between groups. The diagnostic values of WBC, CRP, SAA and the combination of these three markers in all patients with COVID-19 and in different severity groups were analyzed by ROC curve.@*Results@#Compared with control group (WBC count :8.13(6.51,9.42)×109/L, LYM count:2.00(1.28,2.43)×109/L), WBC count [4.94(4.05, 6.67) ×109/L] and LYM count [1.33(0.94, 1.96) ×109/L] of COVID-19 patients were significantly reduced (Z=-7.435, P<0.01; Z=-4.906, P<0.01) . Compared with the control group [CRP: 1.36 (0.57~5.67) mg/ml; SAA:[4.98 (4.80~15.75) mg/mL], CRP [7.93 (2.45~23.98) mg/ml] and SAA [34.13 (4.83~198.40) mg/ml] were increased in research group (Z=-5.72, P<0.01; Z=-4.166, P<0.01) . PCT in the control group and the research group were 0.100 0(0.030 6~0.100 0)ng/ml and 0.044 5(0.031 6~0.077 0)ng/ml, respectively. There was no statistical difference between two groups (Z=-1.451, P=0.147) . The areas under the ROC curve (AUC) of WBC, CRP and SAA in patients with COVID-19 were 0.814, 0.742, 0.673, respectively (P<0.01), while the AUC of the combination of three indexes for COVID-19 diagnosis was 0.882, with 83.33%(55/66) specificity and 84.76% (139/164) sensitivity, P<0.01.The AUCs of WBC, CRP, and SAA for predicting severe and critically severe COVID-19 were 0.799, 0.779, and 0.886 , respectively (P<0.01), and the AUC of the combination of three indexes for the diagnosis of severe and critically severe COVID-19 was 0.924, with 78.67% (118/150) specificity and 14/14 sensitivity (P<0.01).@*Conclusion@#Combining detection of WBC, CRP and SAA can improve the specificity and sensitivity of COVID-19 diagnosis, with a high diagnostic value for severe and critically severe COVID-19.
ABSTRACT
Background Severe cases of coronavirus disease 2019 (COVID-19) rapidly develop acute respiratory distress leading to respiratory failure, with high short-term mortality rates. At present, there is no reliable risk stratification tool for non-severe COVID-19 patients at admission. We aimed to construct an effective model for early identifying cases at high risk of progression to severe COVID-19. Methods SARS-CoV-2 infected patients from one center in Wuhan city and two centers in Guangzhou city, China were included retrospectively. All patients with non-severe COVID-19 during hospitalization were followed for more than 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and patients who kept non-severe state were assigned to the severe and non-severe group, respectively. We compared the demographic, clinical, and laboratory data between severe and non-severe group. Based on baseline data, least absolute shrinkage and selection operator (LASSO) algorithm and logistic regression model were used to construct a nomogram for risk prediction in the train cohort. The predictive accuracy and discriminative ability of nomogram were evaluated by area under the curve (AUC) and calibration curve. Decision curve analysis (DCA) and clinical impact curve analysis (CICA) were conducted to evaluate the clinical applicability of our nomogram. Findings The train cohort consisted of 189 patients, while the two independent validation cohorts consisted of 165 and 18 patients. Among all cases, 72 (19.35%) patients developed severe COVID-19 and 107 (28.76%) patients had one of the following basic disease, including hypertension, diabetes, coronary heart disease, chronic respiratory disease, tuberculosis disease. We found one demographic and six serological indicators (age, serum lactate dehydrogenase, C-reactive protein, the coefficient of variation of red blood cell distribution width (RDW), blood urea nitrogen, albumin, direct bilirubin) are associated with severe COVID-19. Based on these features, we generated the nomogram, which has remarkably high diagnostic accuracy in distinguishing individuals who exacerbated to severe COVID-19 from non-severe COVID-19 (AUC 0.912 [95% CI 0.846-0.978]) in the train cohort with a sensitivity of 85.71 % and specificity of 87.58% ; 0.853 [0.790-0.916] in validation cohort with a sensitivity of 77.5 % and specificity of 78.4%. The calibration curve for probability of severe COVID-19 showed optimal agreement between prediction by nomogram and actual observation. DCA and CICA further indicated that our nomogram conferred significantly high clinical net benefit. Interpretation Our nomogram could help clinicians to early identify patients who will exacerbate to severe COVID-19. And this risk stratification tool will enable better centralized management and early treatment of severe patients, and optimal use of medical resources via patient prioritization and thus significantly reduce mortality rates. The RDW plays an important role in predicting severe COVID-19, implying that the role of RBC in severe disease is underestimated.
Subject(s)
Respiratory Distress Syndrome , Severe Acute Respiratory Syndrome , Diabetes Mellitus , Coronary Disease , Chronic Disease , Hypertension , Tuberculosis , COVID-19 , Respiratory InsufficiencyABSTRACT
Coronavirus disease 2019 (COVID-19) is a respiratory disorder caused by the highly contagious SARS-CoV-2. The immunopathological characteristics of COVID-19 patients, either systemic or local, have not been thoroughly studied. In the present study, we analyzed both the changes in the cellularity of various immune cell types as well as cytokines important for immune reactions and inflammation. Our data indicate that patients with severe COVID-19 exhibited an overall decline of lymphocytes including CD4+ and CD8+ T cells, B cells, and NK cells. The number of immunosuppressive regulatory T cells was moderately increased in patients with mild COVID-19. IL-2, IL-6, and IL-10 were remarkably up-regulated in patients with severe COVID-19. The levels of IL-2 and IL-6 relative to the length of hospital stay underwent a similar "rise-decline" pattern, probably reflecting the therapeutic effect. In conclusion, our study shows that the comprehensive decrease of lymphocytes, and the elevation of IL-2 and IL-6 are reliable indicators of severe COVID-19.