scholarly journals Comparison of three serological chemiluminescence immunoassays for SARS-CoV-2, and clinical significance of antibody index with disease severity

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253889
Author(s):  
Nuri Lee ◽  
Seri Jeong ◽  
Min-Jeong Park ◽  
Wonkeun Song
Keyword(s):  
Disease Severity ◽  
Clinical Significance ◽  
Severe Disease ◽  
Clinical Severity ◽  
Clinical Implications ◽  
Antibody Index ◽  
Clinical Markers ◽  
Strong Correlations ◽  
Igg Antibody ◽  
Molecular Tests

Background The clinical significance of the quantitative value of antibodies in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains mostly unidentified. We investigated the dynamics and clinical implications of the SARS-CoV-2 antibody over time using three automated chemiluminescence immunoassays targeting either nucleocapsids or spikes. Methods A total of 126 specimens were collected from 23 patients with confirmed and indeterminate COVID-19 identified by molecular tests. SARS-CoV-2 antibody index was measured using SARS-CoV2 IgG reagent from Alinity (Abbott) and Access (Beckman Coulter) and SARS-CoV2 Total (IgG + IgM) from Atellica (Siemens). Results Three immunoassays showed strong correlations with each other (range of Pearson’ s correlation coefficient (r) = 0.700–0.854, P < 0.001). Eleven (8.7%) specimens showed inconsistencies. SARS-CoV-2 IgG showed a statistically significantly higher value in patients with severe disease than that in non-severe disease patients (P < 0.001) and was significantly associated with clinical markers of disease severity. Conclusion The quantitative value of the SARS-CoV-2 IgG antibody measured using automated immunoassays is a significant indicator of clinical severity in patients with COVID-19.

scholarly journals Complement C5a and Clinical Markers to predict COVID-19 Disease Severity and Mortality in a Multi-ethnic Population

2021 ◽  
Author(s):  
Farhan S Cyprian ◽  
Muhammad Suleman ◽  
Ibrahim Abdelhafez ◽  
Asmma Doudin ◽  
Ibn Mohammed Masud Danjuma ◽  
...  
Keyword(s):  
Disease Severity ◽  
Complete Blood Count ◽  
Severe Disease ◽  
Clinical Severity ◽  
Classification Model ◽  
Clinical Markers ◽  
Hepatocellular Injury ◽  
Risk Of Death ◽  
Markers Of Inflammation ◽  
Wide Range

Abstract Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n = 33), mild (n = 33) and asymptomatic (n = 23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a novel predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that. high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.

scholarly journals Complement C5a and Clinical Markers as Predictors of COVID-19 Disease Severity and Mortality in a Multi-Ethnic Population

2021 ◽  
Vol 12 ◽  
Author(s):  
Farhan S. Cyprian ◽  
Muhammad Suleman ◽  
Ibrahim Abdelhafez ◽  
Asmma Doudin ◽  
Ibn Mohammed Masud Danjuma ◽  
...  
Keyword(s):  
Disease Severity ◽  
Complete Blood Count ◽  
Severe Disease ◽  
Clinical Severity ◽  
Classification Model ◽  
Clinical Markers ◽  
Hepatocellular Injury ◽  
Risk Of Death ◽  
Markers Of Inflammation ◽  
Wide Range

Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n=33), mild (n=33) and asymptomatic (n=23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help in the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly.

scholarly journals Differential Association of Viral Dynamics With Disease Severity Depending on Patients’ Age Group in COVID-19

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuri Kim ◽  
Shinhyea Cheon ◽  
Hyeongseok Jeong ◽  
Uni Park ◽  
Na-Young Ha ◽  
...  
Keyword(s):  
Viral Load ◽  
Elderly Patients ◽  
Disease Severity ◽  
Acute Phase ◽  
Inflammatory Responses ◽  
Severe Disease ◽  
Neutralizing Antibody ◽  
The Elderly ◽  
Clinical Severity ◽  
Younger Patients

Despite a clear association of patient’s age with COVID-19 severity, there has been conflicting data on the association of viral load with disease severity. Here, we investigated the association of viral load dynamics with patient’s age and severity of COVID-19 using a set of respiratory specimens longitudinally collected (mean: 4.8 times/patient) from 64 patients with broad distribution of clinical severity and age during acute phase. Higher viral burden was positively associated with inflammatory responses, as assessed by IL-6, C-reactive protein, and lactate dehydrogenase levels in patients’ plasma collected on the same day, primarily in the younger cohort (≤59 years old) and in mild cases of all ages, whereas these were barely detectable in elderly patients (≥60 years old) with critical disease. In addition, viral load dynamics in elderly patients were not significantly different between mild and critical cases, even though more enhanced inflammation was consistently observed in the elderly group when compared to the younger group during the acute phase of infection. The positive correlation of viral load with disease severity in younger patients may explain the increased therapeutic responsiveness to current antiviral drugs and neutralizing antibody therapies in younger patients compared to elderly patients. More careful intervention against aging-associated inflammation might be required to mitigate severe disease progression and reduce fatality in COVID-19 patients more than 60 years old.

scholarly journals ANTIBODY RESPONSE TO COVID-19 INFECTION- CLINICAL VARIABLES AT PLAY

2020 ◽  
Author(s):  
Anuj Parkash ◽  
Parul Singla ◽  
Meenu Bhatia
Keyword(s):  
Immune Response ◽  
Immune Responses ◽  
Disease Severity ◽  
Statistical Significance ◽  
Severe Disease ◽  
Initial Symptom ◽  
Igg Antibody ◽  
Duration Of Symptoms ◽  
Clinical Variables ◽  
Significant Difference

ABSTRACTBackgroundThe current COVID19 pandemic began in December 2019 and rapidly expanded to become a global pandemic. The COVID 19 presents multitude of clinical disorders, ranges from asymptomatic infection to severe disease, which can accompanied by multisystem failure leading to death. The immune response to SARS CoV 2 is understood to involve all the components of the system that together causes viral elimination and recovery from the infection. However, such immune responses implicated in the disease has varied presentation ranging from mild to a severe form, which appears to hinge on the loss of the immune regulation between protective and altered responses. In this study, we want to unravel this association of immune responses to various clinical variables, which might have a major role to play, while generating the immune response. The objective was to test this hypothesis in our settings and comparing the results of serologic tests from a group of COVID 19 patients and will analyzed the disease severity in comparison.MethodsTesting for SARS COV2 IgG Antibody was done with chemiluminescent assay on the Ortho Clinical Diagnostic’s (OCD) Vitros 5600 platform.ResultsA total of 106 COVID 19 patients were included in this study, of whom 61 were male and 45 were female. Their mean age was 43.7 years (range 17–83) and the median interval between initial symptom onset and sample collection was 12.33 days. Eighty patients (82%) had mild or moderate symptoms and twenty-six patients (18%) had severe symptoms. The antibody titers were positive in 99 patients (93%) and were found negative in 7 patients (7%). When comparing patients with mild/moderate symptoms and patients with severe/critical diseases, no statistically significant difference was observed between their gender ratios (P = 0.373) and age composition (P = 0.224).ConclusionsThe data presented in this research study did not find any statistical significance between SARS CoV 2 IgG antibody levels with COVID 19 disease severity, duration of symptoms, age, gender, and length of convalescence.

scholarly journals D Dimer – Prognostic indicator for disease severity in patients hospitalised with COVID 19

2021 ◽  
Vol 8 (4) ◽  
pp. 461-464
Author(s):  
Vineet Banga ◽  
Stuti Jain
Keyword(s):  
Retrospective Study ◽  
Disease Severity ◽  
Severe Disease ◽  
Prognostic Indicator ◽  
Clinical Severity ◽  
Care Hospital ◽  
Severity Of Disease ◽  
Management Protocol ◽  
Severity Levels ◽  
D Dimer

Patients of Covid 19 infections present with different severity. Levels of D Dimer in these patients can be correlated with disease severity for management and prognosis. To evaluate the usefulness of D-Dimer levels in blood to correlate with disease severity in COVID 19 patients. Retrospective study was done in Department of Pathology of Secondary Care hospital that became designated covid hospital from May 2021 to June 2021 on 60 COVID 19 positive admitted patients. D dimer levels were analysed and correlated with clinical severity of disease. Out of total 60 patients, 33 were in mild, 23 in moderate and 4 were in severe category. In mild cases D Dimer varies from 43 ng/ml to 183 ng/ml. In moderate cases D Dimer varies from 270 ng/ml to 991 ng/ml. In severe cases D Dimer varies from 1043 ng/ml to 2463 ng/ml. The study suggests cut off levels for D Dimer as up to 200 ng/ml for mild, 200-1000 ng/ml for moderate and more than 1000 ng/ml for severe category in COVID 19 patients. D dimer helps in identifying severe disease and can be used as an essential biomarker in developing the management protocol for COVID 19 patients.

scholarly journals Gut microbiota diversity and C-Reactive Protein are predictors of disease severity in COVID-19 patients

2021 ◽  
Author(s):  
André Moreira-Rosário ◽  
Cláudia Marques ◽  
Hélder Pinheiro ◽  
João Ricardo Araújo ◽  
Pedro Ribeiro ◽  
...  
Keyword(s):  
Risk Factors ◽  
Gut Microbiota ◽  
Disease Severity ◽  
Severe Disease ◽  
Clinical Severity ◽  
Rrna Gene ◽  
C Reactive Protein ◽  
Clinical Progression ◽  
Reactive Protein ◽  
Microbiota Diversity

AbstractRisk factors for COVID-19 disease severity are still poorly understood. Considering the pivotal role of gut microbiota on host immune and inflammatory functions, we investigated the association between changes in gut microbiota composition and the clinical severity of COVID-19. We conducted a multicentre cross-sectional study prospectively enrolling 115 COVID-19 patients categorized according to: 1) WHO Clinical Progression Scale - mild 19 (16.5%), moderate 37 (32.2%) or severe 59 (51.3%); and 2) location of recovery from COVID-19 - ambulatory 14 (household isolation; 12.2%), hospitalized in ward 40 (34.8%) or intensive care unit 61 (53.0%). Gut microbiota analysis was performed through 16S rRNA gene sequencing and data obtained was further related with clinical parameters of COVID-19 patients. Risk factors for COVID-19 severity were identified by univariate and multivariable logistic regression models.In comparison with mild COVID-19 patients, the gut microbiota of moderate and severe patients has: a) lower Firmicutes/Bacteroidetes ratio, b) higher abundance of Proteobacteria; and c) lower abundance of beneficial butyrate-producing bacteria such as Roseburia and Lachnospira genera. Multivariable regression analysis showed that Shannon index diversity (odds ratio [OR] 2.85 [95% CI 1.09-7.41]; p=0.032) and C-Reactive Protein (OR 3.45 [95% CI 1.33-8.91]; p=0.011) were risk factors for COVID-19 severe disease (a score of 6 or higher in WHO clinical progression scale).In conclusion, our results demonstrated that hospitalised moderate and severe COVID-19 patients have microbial signatures of gut dysbiosis and for the first time, the gut microbiota diversity is pointed out as a prognostic biomarker for COVID-19 disease severity.

scholarly journals Using secondary cases to characterize the severity of an emerging or re-emerging infection

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Tim K. Tsang ◽  
Can Wang ◽  
Bingyi Yang ◽  
Simon Cauchemez ◽  
Benjamin J. Cowling
Keyword(s):  
Infectious Disease ◽  
Systematic Review ◽  
Statistical Model ◽  
Disease Severity ◽  
Severe Disease ◽  
Clinical Severity ◽  
Contact Tracing ◽  
Emerging Infection ◽  
Index Cases ◽  
Extract Information

AbstractThe methods to ascertain cases of an emerging infectious disease are typically biased toward cases with more severe disease, which can bias the average infection-severity profile. Here, we conducted a systematic review to extract information on disease severity among index cases and secondary cases identified by contact tracing of index cases for COVID-19. We identified 38 studies to extract information on measures of clinical severity. The proportion of index cases with fever was 43% higher than for secondary cases. The proportion of symptomatic, hospitalized, and fatal illnesses among index cases were 12%, 126%, and 179% higher than for secondary cases, respectively. We developed a statistical model to utilize the severity difference, and estimate 55% of index cases were missed in Wuhan, China. Information on disease severity in secondary cases should be less susceptible to ascertainment bias and could inform estimates of disease severity and the proportion of missed index cases.

scholarly journals Assessing disease severity by hsCRP as a biochemical marker for psoriasis

2017 ◽  
Vol 3 (4) ◽  
pp. 501
Author(s):  
Kriti Jain ◽  
Arvind Krishna ◽  
B. S. Rathore
Keyword(s):  
Disease Severity ◽  
Age Of Onset ◽  
Late Onset ◽  
Severe Disease ◽  
High Sensitivity ◽  
The Body ◽  
Clinical Severity ◽  
Positive Correlation ◽  
Reactive Protein ◽  
Pasi Score

<p class="abstract"><strong>Background:</strong> <span lang="EN-IN">For a complex chronic disease like psoriasis, having a biomarker to objectively assess the clinical severity can be very helpful in disease management.</span></p><p class="abstract"><strong>Methods:</strong> <span lang="EN-IN">In a hospital based prospective study, 70 patients of psoriasis diagnosed clinically, were studied. The extent of disease severity was assessed using PASI and BSA and patients were grouped into having mild, moderate and severe disease using these scores. Serum high sensitivity </span>C-reactive protein <span lang="EN-IN">(hsCRP) levels were then estimated for each group</span>.<strong></strong></p><p class="abstract"><strong>Results:</strong> <span lang="EN-IN">Of the 70 psoriasis cases enrolled, 46 patients were male and 24 females. Patients with early onset psoriasis were associated with higher values of hsCRP than those with late onset (r=-0.063; p=0.012). A positive correlation was seen between the PASI score and hsCRP levels (r=0.891; p≤0.001). On comparing mean PASI and mean hsCRP in severity groups (mild, moderate and severe), hsCRP was higher in the group with maximum severity (p≤0.001). </span></p><p class="abstract"><strong>Conclusions:</strong> <span lang="EN-IN">A negative correlation between the age of onset and hsCRP implies that, earlier the age of onset, higher is the value of hsCRP. Our study shows a positive correlation between the body surface area and PASI score both of which varied linearly with hsCRP values. The findings also suggest that patients with severe psoriasis have higher mean serum hsCRP levels than patients with mild psoriasiss.</span><span lang="EN-IN">We proposed hsCRP as a useful marker of psoriasis severity that could be used to monitor psoriasis and, together with PASI, as a global index of disease severity.</span></p><p class="abstract"> </p>

scholarly journals COVID-19 among Minority Children in Detroit, Michigan during the Early National Surge of the Pandemic

2021 ◽  
Vol 8 ◽  
pp. 2333794X2110227
Author(s):  
Jocelyn Y. Ang ◽  
Nirupama Kannikeswaran ◽  
Katherine Parker ◽  
Eric McGrath ◽  
Nahed Abdel-Haq ◽  
...  
Keyword(s):  
Disease Severity ◽  
Care Center ◽  
Severe Disease ◽  
Tertiary Care ◽  
Hospitalization Rate ◽  
Severe Illness ◽  
P Value ◽  
Antibody Testing ◽  
Igg Antibody ◽  
Increased Risk

Background. The COVID-19 pandemic has shed light on communities of racial/ethnic minority groups in the US where long-standing health issues and structural inequities are now known to have resulted in increased risk for infection, severe illness, and death from the virus. The objective of our study was to describe demographic characteristics, clinical presentations, medical interventions and outcomes of pediatric patients with COVID-19 treated at Children’s Hospital of Michigan (CHM), a tertiary care center in urban Detroit, an early hotspot during the initial surge of the SARS-CoV-2 pandemic. Methods. A retrospective chart review was performed of children ≤18 years of age who had polymerase chain reaction (RT-PCR) testing via NP swab or serum IgG antibody testing for SARS-CoV-2 during March 1, 2020–June 30, 2020. Results. Seventy-eight COVID-19 infected children were identified of whom 85.8% (67/78) were from minority populations (African American, Hispanic). Hospitalization rate was 82% (64/78). About 44% (34/78) had an associated comorbidity with asthma and obesity being most common. Although all ages were affected, infants <1 year of age had the highest hospitalization rate (19/64, 30%). In all disease severity categories, dichotomized non-whites had more severe disease by percentage within race/ethnicity than Whites, and also within percent disease severity ( P-value = .197). Overall, 37% of hospitalized patients required intensive care. Conclusions. Extremely high rates of COVID-19 hospitalization and requirement of ICU care were identified in our patient population. Further studies are needed to better understand the contributing factors to this health disparity in disadvantaged communities.

scholarly journals Autoimmune anti-DNA and anti-phosphatidylserine antibodies predict development of severe COVID-19

2021 ◽  
Vol 4 (11) ◽  
pp. e202101180
Author(s):  
Claudia Gomes ◽  
Marisol Zuniga ◽  
Kelly A Crotty ◽  
Kun Qian ◽  
Nubia Catalina Tovar ◽  
...  
Keyword(s):  
Disease Severity ◽  
Cell Injury ◽  
Severe Disease ◽  
Clinical Manifestations ◽  
Predictive Biomarkers ◽  
Strong Correlations ◽  
Autoimmune Antibodies ◽  
Dna Antibodies ◽  
Common Antigens ◽  
Degrees Of Severity

High levels of autoimmune antibodies are observed in COVID-19 patients but their specific contribution to disease severity and clinical manifestations remains poorly understood. We performed a retrospective study of 115 COVID-19 hospitalized patients with different degrees of severity to analyze the generation of autoimmune antibodies to common antigens: a lysate of erythrocytes, the lipid phosphatidylserine (PS) and DNA. High levels of IgG autoantibodies against erythrocyte lysates were observed in a large percentage (up to 36%) of patients. Anti-DNA and anti-PS antibodies determined upon hospital admission correlated strongly with later development of severe disease, showing a positive predictive value of 85.7% and 92.8%, respectively. Patients with positive values for at least one of the two autoantibodies accounted for 24% of total severe cases. Statistical analysis identified strong correlations between anti-DNA antibodies and markers of cell injury, coagulation, neutrophil levels and erythrocyte size. Anti-DNA and anti-PS autoantibodies may play an important role in the pathogenesis of COVID-19 and could be developed as predictive biomarkers for disease severity and specific clinical manifestations.

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