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2.
J Hepatol ; 75(2): 435-438, 2021 08.
Article in English | MEDLINE | ID: covidwho-1454287

ABSTRACT

BACKGROUND & AIMS: Two SARS-CoV-2 mRNA vaccines were approved to prevent COVID-19 infection, with reported vaccine efficacy of 95%. Liver transplant (LT) recipients are at risk of lower vaccine immunogenicity and were not included in the registration trials. We assessed vaccine immunogenicity and safety in this special population. METHODS: LT recipients followed at the Tel-Aviv Sourasky Medical Center and healthy volunteers were tested for SARS-CoV-2 IgG antibodies directed against the Spike-protein (S) and Nucleocapsid-protein (N) 10-20 days after receiving the second Pfizer-BioNTech BNT162b2 SARS-CoV-2 vaccine dose. Information regarding vaccine side effects and clinical data was collected from patients and medical records. RESULTS: Eighty LT recipients were enrolled. Mean age was 60 years and 30% were female. Twenty-five healthy volunteer controls were younger (mean age 52.7 years, p = 0.013) and mostly female (68%, p = 0.002). All participants were negative for IgG N-protein serology, indicating immunity did not result from prior COVID-19 infection. All controls were positive for IgG S-protein serology. Immunogenicity among LT recipients was significantly lower with positive serology in only 47.5% (p <0.001). Antibody titer was also significantly lower in this group (mean 95.41 AU/ml vs. 200.5 AU/ml in controls, p <0.001). Predictors for negative response among LT recipients were older age, lower estimated glomerular filtration rate, and treatment with high dose steroids and mycophenolate mofetil. No serious adverse events were reported in either group. CONCLUSION: LT recipients developed substantially lower immunological response to the Pfizer-BioNTech SARS-CoV-2 mRNA-based vaccine. Factors influencing serological antibody responses include age, renal function and immunosuppressive medications. The findings require re-evaluation of vaccine regimens in this population. LAY SUMMARY: The Pfizer-BioNTech BNT162b2 SARS-CoV-2 vaccine elicited substantially inferior immunity in liver transplant recipients. Less than half of the patients developed sufficient levels of antibodies against the virus, and in those who were positive, average antibody levels were 2x less compared to healthy controls. Factors predicting non-response were older age, renal function and immunosuppressive medications.


Subject(s)
Antibodies, Viral/blood , COVID-19 Vaccines , COVID-19 , Immunogenicity, Vaccine/immunology , Immunoglobulin G/blood , Immunosuppressive Agents/therapeutic use , Liver Transplantation/methods , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines/administration & dosage , COVID-19 Vaccines/adverse effects , COVID-19 Vaccines/immunology , Female , Humans , Israel/epidemiology , Kidney Function Tests , Male , Middle Aged , Risk Factors , SARS-CoV-2/immunology , Serologic Tests/methods , Serologic Tests/statistics & numerical data , Vaccination/adverse effects , Vaccination/methods
4.
Epidemiol. serv. saúde ; 30(2): e2020722, 2021. graf
Article in English, Portuguese | LILACS (Americas) | ID: covidwho-1234612

ABSTRACT

Objetivo: Analisar como a testagem da população influencia os indicadores de saúde usados para monitorar a pandemia de COVID-19 nos 50 países com maior número de casos diagnosticados. Métodos: Estudo ecológico sobre dados secundários, extraídos em 19/08/2020. Foram calculadas incidência acumulada, taxa de mortalidade, letalidade e proporção de testes positivos. Os dados foram descritos e apresentados graficamente, com o respectivo coeficiente de correlação de Spearman. Resultados: A taxa de testagem variou enormemente entre os países. A incidência acumulada e a proporção de testes positivos foram correlacionadas ao número de testes, enquanto a taxa de mortalidade e a letalidade apresentaram correlação baixa com esse indicador. Conclusão: A maioria dos países não testa o suficiente para garantir adequado monitoramento da pandemia, com reflexo na qualidade dos indicadores. A ampliação do número de testes é fundamental; porém, ela deve ser acompanhada de outras medidas, como isolamento de casos diagnosticados e rastreamento de contatos.


Objetivo: Analizar cómo el testeo poblacional influye en los indicadores de salud utilizados para monitorear la pandemia de COVID-19 en los 50 países con mayor número de casos diagnosticados. Métodos: Estudio ecológico, con datos secundarios, recogidos el 19/8/2020. Se calcularon la incidencia acumulada, la tasa de mortalidad, la letalidad y la proporción de pruebas positivas. Los datos fueron descritos y presentados gráficamente, con el respectivo Coeficiente de Correlación de Spearman. Resultados: La tasa de testeo varió enormemente entre los países. La incidencia acumulada y la proporción de pruebas positivas se correlacionaron con el número de pruebas, mientras que la tasa de mortalidad y de letalidad mostraron una baja correlación con este indicador. Conclusión: La mayoría de los países no realizan suficientes pruebas para garantizar un seguimiento adecuado de la pandemia, lo que se refleja en la calidad de los indicadores. La ampliación del número de pruebas es fundamental, y debe ir acompañada de aislamiento de casos y seguimiento de contactos.


Objective: To analyse how testing the population influences the health indicators used to monitor the COVID-19 pandemic in the 50 countries with the highest number of diagnosed cases. Methods:This was an ecological study using secondary data retrieved on 8/19/2020. Cumulative incidence, mortality rate, case-fatality rate, and proportion of positive tests were calculated. The data were described and presented graphically, with their respective Spearman Correlation Coefficients. Results: The testing rate varied enormously between countries. Cumulative incidence and the proportion of positive tests were correlated with the number of tests, while the mortality rate and case-fatality rate showed low correlation with this indicator. Conclusion: Most countries do not test enough to ensure adequate monitoring of the pandemic, and this is reflected in the quality of the indicators. Expanding the number of tests is essential, but it needs to be accompanied by other measures, such as isolation of diagnosed cases and contact tracing.


Subject(s)
Humans , Incidence , Coronavirus Infections/diagnosis , Coronavirus Infections/mortality , Coronavirus Infections/epidemiology , Laboratory Test/statistics & numerical data , Serologic Tests/statistics & numerical data , Global Health/statistics & numerical data , Health Status Indicators , Reverse Transcriptase Polymerase Chain Reaction , Pandemics/statistics & numerical data
5.
Epidemiol. serv. saúde ; 30(1): e2020788, 2021. tab, graf
Article in English, Portuguese | LILACS (Americas) | ID: covidwho-1127861

ABSTRACT

Objetivo: Analisar as notificações de síndrome gripal segundo o intervalo de tempo decorrido entre início dos sintomas e realização do exame para COVID-19. Métodos: Estudo transversal, utilizando registros de casos de síndrome gripal contendo resultados de testes diagnósticos da COVID-19 nas capitais brasileiras e no Distrito Federal, no sistema e-SUS Notifica, entre 1º/março/2020 e 18/agosto/2020. Comparou-se o intervalo de tempo entre início dos sintomas e realização do exame (teste ANOVA), classificando-o segundo a adequação/oportunidade do exame. Resultados: Entre 1.942.514 notificações, o tempo médio entre início dos sintomas e execução dos testes foi de 10,2 dias (±17,1). Entre testados, predominou o sexo feminino (55,1%), idade de 20-39 anos (43,8%) e região Sudeste (43,0%). O teste ELISA IgM foi realizado em tempo adequado para 58,8%; e o teste rápido-antígeno, em tempo inadequado para 68,0%. Conclusão: Observou-se inadequação entre início dos sintomas e realização dos testes para COVID-19 nas regiões brasileiras.


Objetivo: Analizar las notificaciones de síndrome gripal según el intervalo de tiempo entre el inicio de los síntomas y el examen de COVID-19. Métodos: Estudio transversal utilizando registros de casos de síndrome gripal que contienen resultados de pruebas diagnósticas de COVID-19 en las capitales brasileñas y el Distrito Federal del sistema e-SUS Notifica, entre 1/marzo/2020 y 18/agosto/2020. El intervalo de tiempo se comparó entre el inicio de los síntomas y la realización del examen mediante la prueba ANOVA, clasificándolo según la adecuación/ oportunidad del examen. Resultados: Entre 1.942.514 notificaciones, el tiempo promedio entre el inicio de los síntomas y la ejecución del examen fue de 10,2 días (±17,1). Entre los evaluados, predominaron las mujeres (55,1%), 20-39 años (43,8%) y la región Sudeste (43,0%). El ELISA IgM se realizó en momento adecuado para 58,8% y la prueba de Antígeno Rápido en momento inadecuado para 68,0%. Conclusión: Se constata inadecuación de tiempo entre el inicio de los síntomas y las pruebas para COVID-19 en las regiones brasileñas.


Objective: To analyze notifications of flu-like syndrome according to the time interval between onset of symptoms and testing for COVID-19. Methods: This was a cross-sectional study using records of flu-like syndrome cases containing results of COVID-19 diagnostic tests in the Brazilian state capitals and Federal District, held on the e-SUS Notifica system, from March 1st, 2020 to August 18th, 2020. The time interval between symptom onset and testing was compared using the ANOVA test, classifying it according to test adequacy/timeliness. Results: Taking 1,942,514 notifications, average time between symptom onset and testing was 10.2 days (±17.1). Among those tested, females (55.1%), people aged 20-39 years (43.8%), and the Southeast region of Brazil (43.0%) predominated. 58.8% of IgM ELISA tests were performed at an adequate time while 68.0% of rapid antigen tests were not performed at an adequate time. Conclusion: Inadequacy was found between symptom onset and time taken to test for COVID-19 in the Brazilian regions.


Subject(s)
Humans , Serologic Tests/statistics & numerical data , Seroepidemiologic Studies , Coronavirus Infections/diagnosis , Coronavirus Infections/epidemiology , Laboratory Test , Brazil/epidemiology , Enzyme-Linked Immunosorbent Assay/statistics & numerical data , Cross-Sectional Studies , Public Health Surveillance
6.
Clin Lab ; 66(11)2020 Nov 01.
Article in English | MEDLINE | ID: covidwho-922948

ABSTRACT

BACKGROUND: On January 30, 2020, WHO declared COVID-19 a pandemic. In this article we describe our experience at Richmond University Medical Center with Chembio serological IgM, IgG testing. METHODS: In this prospective cohort study of patients and hospital employees, we utilized Chembio COVID-19 IgM/IgG serological testing in addition to Cepheid RT-PCR analysis. RESULTS: We evaluated the performance of Chembio serological test for IgM and IgG as an employee screening tool in a community hospital setting. The total number of currently asymptomatic employees screened was 1,866 from the Richmond University Medical Center. The non-exposed group included 1,253 (67.1%) employees with no significant clinical history and non-reactive IgM and IgG antibodies. The convalescent group included 255 (13.7%) of the employees with elevation of IgG only, 18 (1%) employees with past history of positive PCR and COVID-19 who currently have non-reactive IgM and IgG antibodies or demonstrate elevated IgG only, followed by 3 employees (< 1%) with no past clinical history who demonstrated reactive IgM and IgG antibodies and negative follow up by PCR. The reported 14.9% exposure/convalescent rate is lower than the reported 20% by the Department of Health and Governor Andrew Cuomo and may represent a better utilization of personal protective equipment, better hand washing techniques, and better disinfection procedures combined with strict social distancing. CONCLUSIONS: Chembio's performance is satisfactory; however, hospitals must design their own policies addressing: who needs to be screened and who will interpret the results as well as constructing management algorithms for employees with no previous history and current double positive antibodies.


Subject(s)
Clinical Laboratory Techniques/methods , Immunoglobulin G/analysis , Immunoglobulin M/analysis , Mass Screening/methods , Serologic Tests/statistics & numerical data , COVID-19 , COVID-19 Testing , Coronavirus Infections/blood , Coronavirus Infections/diagnosis , Guidelines as Topic , Humans , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/diagnosis
8.
Eur Rev Med Pharmacol Sci ; 24(19): 10208-10218, 2020 Oct.
Article in English | MEDLINE | ID: covidwho-890954

ABSTRACT

OBJECTIVE: Currently, detection of SARS-CoV-2 RNA is standard in the diagnosis of COVID-19 (2019-nCoV). However, reliable and rapid serological diagnostic methods to screen SARS-CoV-2 infected patients, including those who do not have overt symptoms, are urgently needed. Most studies have described serological tests based on the detection of SARS-CoV-2-specific IgM and IgG. Here, we attempted to systematically analyze the positive rates and comprehensive diagnostic efficacy of IgM and IgG in response to SARS-CoV-2 infection. MATERIALS AND METHODS: By systematically searching PubMed, medRxiv, bioRxiv and other databases, studies regarding the detection of peripheral blood IgM and/or IgG related to SARS-CoV-2 were collected. The positive rate, sensitivity (SEN), specificity (SPE), area under the curve (AUC) and corresponding 95% CIs were obtained by weighted quantitative mergence, and the source of heterogeneity was explored by performing a subgroup study and sensitivity analysis. RESULTS: A total of 30 studies were included, which were comprised of 3856 confirmed SARS-CoV-2 RNA positive cases, 368 suspected RNA negative cases, 1167 asymptomatic carriers, and 2526 RNA negative controls. The corresponding meta-analysis showed that in confirmed cases with 2019-nCoV, the positive rates of single IgM, single IgG and their joint detection related to SARS-CoV-2 were 61.2% (95% CI: 53.4%-69.0%), 58.8% (95% CI: 49.6%-68.0%) and 62.1% (52.7%-71.4%), respectively. In suspected RNA negative cases, the positive rates of single IgM, single IgG and their joint detection were 29.0% (95% CI: 14.0%-44.0%), 37.0% (95% CI: 20.0%-55.0%) and 55.0% (95% CI: 19.0%-90.0%), respectively. Interestingly, IgM/IgG detection also demonstrated a positive rate of 19% (95% CI: 10.0%-27.0%) in asymptomatic cases. Using RT-PCR test as reference, the AUCs of IgM, IgG and IgM/IgG in the diagnosis of 2019-nCoV infection were 0.9656, 0.9766, and 0.9838, respectively. The stratified analyses showed that among confirmed cases with 2019-nCoV, the positive rates of IgM and IgG were 27.3% (95%CI: 19.8%-34.8%) and 22.3% (95% CI: 11.3%-33.3%), respectively, 0-7days following the onset of symptoms, whereas the positive rate of parallel IgM/IgG testing attained 39.3% (95% CI: 24.2%-54.4%). Moreover, the efficacy of antibody testing based on CLIA (chemiluminescence enzyme immunoassays) in diagnosing 2019-nCoV infection was higher than that of LFIA (lateral flow immunoassays) and ELISA (enzyme linked immunosorbent assay). CONCLUSIONS: IgM, IgG and their joint testing exhibited high clinical value in the diagnosis of 2019-nCoV, which may assist in making up for the deficiency of throat swab RNA tests.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/diagnosis , COVID-19/virology , SARS-CoV-2/immunology , Serologic Tests/statistics & numerical data , COVID-19/blood , COVID-19/immunology , Humans , Immunoglobulin G/blood , Immunoglobulin M/blood , Pandemics , Sensitivity and Specificity , Seroepidemiologic Studies
9.
J Appl Lab Med ; 5(6): 1324-1336, 2020 11 01.
Article in English | MEDLINE | ID: covidwho-696756

ABSTRACT

BACKGROUND: COVID-19 is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel beta-coronavirus that is responsible for the 2019 coronavirus pandemic. Acute infections should be diagnosed by polymerase chain reaction (PCR) based tests, but serology tests can demonstrate previous exposure to the virus. METHODS: We compared the performance of the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays using 179 negative participants to determine negative percentage agreement (NPA) and in 60 SARS-CoV-2 PCR-confirmed positive patients to determine positive percentage agreement (PPA) at 3 different time frames following a positive SARS-CoV-2 PCR result. RESULTS: At ≥15 days, the PPA (95% CI) was 100 (86.3-100)% for the Diazyme IgM/IgG panel, 96.0 (79.7-99.9)% for the Roche total Ig assay, and 100 (86.3-100)% for the Abbott IgG assay. The NPA (95% CI) was 98.3 (95.2-99.7)% for the Diazyme IgM/IgG panel, 99.4 (96.9-100)% for the Roche total Ig assay, and 98.9 (96.0-99.9)% for the Abbott IgG assay. When the Roche total Ig assay was combined with either the Diazyme IgM/IgG panel or the Abbott IgG assay, the positive predictive value was 100% while the negative predictive value remained greater than 99%. CONCLUSIONS: Our data demonstrates that the Diazyme, Roche, and Abbott SARS-CoV-2 serology assays have similar clinical performances. We demonstrated a low false-positive rate across all 3 platforms and observed that false positives observed on the Roche platform are unique compared to those observed on the Diazyme or Abbott assays. Using multiple platforms in tandem increases the PPVs, which is important when screening populations with low disease prevalence.


Subject(s)
Antibodies, Viral/isolation & purification , Betacoronavirus/isolation & purification , Clinical Laboratory Techniques/instrumentation , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Serologic Tests/instrumentation , Antibodies, Viral/blood , Antibodies, Viral/immunology , Betacoronavirus/immunology , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/blood , Coronavirus Infections/immunology , Coronavirus Infections/virology , False Negative Reactions , False Positive Reactions , Humans , Immunoglobulin G/blood , Immunoglobulin G/immunology , Immunoglobulin G/isolation & purification , Longitudinal Studies , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/immunology , Pneumonia, Viral/virology , Predictive Value of Tests , Reagent Kits, Diagnostic/statistics & numerical data , SARS-CoV-2 , Serologic Tests/statistics & numerical data , Time Factors
11.
J Appl Lab Med ; 5(6): 1351-1357, 2020 11 01.
Article in English | MEDLINE | ID: covidwho-676460

ABSTRACT

BACKGROUND: While molecular techniques remain the gold standard for diagnosis of acute SARS-CoV-2 infection, serological tests have the unique potential to ascertain how much of the population has been exposed to the COVID-19 pathogen. There have been limited published studies to date documenting the performance of SARS-CoV-2 antibody assays. METHODS: We compared the DiaSorin Liaison SARS-CoV-2 S1/S2 IgG and Roche Diagnostics Elecsys Anti-SARS-CoV-2 assays using 228 samples spanning patients with positive PCR for SARS-CoV-2, patients with compatible symptoms but negative PCR, pre-COVID specimens, and potential cross-reactives. RESULTS: Both assays detected antibodies in 18/19 samples collected at least one week after a positive PCR result. Neither method consistently detected antibodies in specimens collected within one week of a positive PCR result (sensitivity < 50%), but antibodies were detected by only Roche in four samples in this time frame. Using 139 pre-COVID and 35 PCR-negative samples, the Roche and DiaSorin assays demonstrated specificities of 100.0% and 98.9%, respectively. Neither assay demonstrated cross-reactivity from other coronaviruses (229E, HKU1, NL63, OC43), respiratory pathogens (adenovirus, metapneumovirus, rhinovirus/enterovirus), or antibodies to other viruses (HIV, EBV, CMV, HBV, HCV, HAV). DISCUSSION: Overall, the qualitative interpretations afforded by the Roche and DiaSorin assays agreed for 97% of samples evaluated. Minor discrepancies in sensitivity and specificity were observed between methods, with the differences in specificity more clinically significant for our low-prevalence population. For the DiaSorin assay, all disagreements with the Roche assay occurred in samples with quantitative signals near the cut-off determining positivity.


Subject(s)
Antibodies, Viral/isolation & purification , Betacoronavirus/isolation & purification , Clinical Laboratory Techniques/instrumentation , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Serologic Tests/instrumentation , Antibodies, Viral/blood , Antibodies, Viral/immunology , Betacoronavirus/genetics , Betacoronavirus/immunology , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/blood , Coronavirus Infections/immunology , Coronavirus Infections/virology , Cross Reactions , False Positive Reactions , Humans , Immunoglobulin G/blood , Immunoglobulin G/immunology , Immunoglobulin G/isolation & purification , Limit of Detection , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/immunology , Pneumonia, Viral/virology , Polymerase Chain Reaction/statistics & numerical data , Predictive Value of Tests , RNA, Viral/isolation & purification , Reagent Kits, Diagnostic/statistics & numerical data , SARS-CoV-2 , Serologic Tests/statistics & numerical data , Time Factors
12.
J Appl Lab Med ; 5(6): 1313-1323, 2020 11 01.
Article in English | MEDLINE | ID: covidwho-676346

ABSTRACT

BACKGROUND: Little is known about the performance of the Roche novel severe acute respiratory syndrome coronavirus 2 antibody (anti-SARS-CoV-2) assay. We provide an extensive evaluation of this fully automated assay on Cobas e801/e602 immunoassay analyzers. METHODS: We assessed the linearity, precision, and throughput of the Roche anti-SARS-CoV-2 assay. Sensitivity was calculated from 349 SARS-CoV-2 polymerase chain reaction (PCR) positive samples; specificity was determined from 715 coronavirus disease 2019 (COVID-19)-naive samples. We examined cross-reactivity against other antibody positive samples [syphilis, rheumatoid factor (RF), antinuclear antibody (ANA), double-stranded DNA (ds-DNA), influenza, dengue, hepatitis B (HBV), hepatitis C (HCV)] and the anti-SARS-CoV-2 kinetics. RESULTS: The assay cut-off index (COI) was linear up to 90.8. The interassay precision was 2.9% for a negative control (COI = 0.1) and 5.1% for a positive control (COI = 3.0). Assay time is 18 min and results are available 1 min later; throughput for 300 samples was 76 min. Only 1 case positive for HBsAg tested falsely positive; specificity was 99.9%. The assay has a sensitivity of 97.1% 14 days after PCR positivity (POS) and 100% at ≥21 days POS; 48.2% of cases had anti-SARS-CoV-2 within 6 days POS. In 11 patients in whom serum was available prior to a positive antibody signal (COI ≥1.0) the interval between the last negative and first positive COI (time to "seroconversion") on average is 3 days (range 1-6 days) and 4 more days (range 1-7) for the anti-SARS-CoV-2 to plateau. CONCLUSION: The Roche anti-SARS-CoV-2 assay shows excellent performance with minimal cross-reactivity from other viral and confounding antibodies. Antibody development and seroconversion appears quite early.


Subject(s)
Antibodies, Viral/blood , Betacoronavirus/isolation & purification , Clinical Laboratory Techniques/instrumentation , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Serologic Tests/instrumentation , Adult , Aged , Aged, 80 and over , Antibodies, Viral/immunology , Betacoronavirus/genetics , Betacoronavirus/immunology , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/blood , Coronavirus Infections/immunology , Coronavirus Infections/virology , Cross Reactions/immunology , Female , Fluoroimmunoassay/instrumentation , Fluoroimmunoassay/statistics & numerical data , Humans , Immunoglobulin G/blood , Immunoglobulin G/immunology , Luminescent Measurements/instrumentation , Luminescent Measurements/statistics & numerical data , Male , Middle Aged , Pandemics , Pneumonia, Viral/blood , Pneumonia, Viral/immunology , Pneumonia, Viral/virology , Polymerase Chain Reaction/statistics & numerical data , Predictive Value of Tests , RNA, Viral/isolation & purification , Reagent Kits, Diagnostic , SARS-CoV-2 , Seroconversion , Serologic Tests/statistics & numerical data , Time Factors , Young Adult
13.
J Clin Microbiol ; 58(9)2020 08 24.
Article in English | MEDLINE | ID: covidwho-613360

ABSTRACT

In the coronavirus (CoV) disease 2019 (COVID-19) pandemic, highly selective serological testing is essential to define exposure to severe acute respiratory syndrome CoV 2 (SARS-CoV-2). Many tests have been developed, yet with variable speeds to first results, and are of unknown quality, particularly when considering the prediction of neutralizing capacity. The LIAISON SARS-CoV-2 S1/S2 IgG assay was designed to measure antibodies against the SARS-CoV-2 native S1/S2 proteins in a standardized automated chemiluminescence assay. The clinical and analytical performances of the test were validated in an observational study using residual samples (>1,500) with a positive or negative COVID-19 diagnosis. The LIAISON SARS-CoV-2 S1/S2 IgG assay proved to be highly selective and specific and offered semiquantitative measures of serum or plasma levels of anti-S1/S2 IgG with neutralizing activity. The assay's diagnostic sensitivities were 91.3% and 95.7% at >5 or ≥15 days from diagnosis, respectively, and 100% when assessed against a neutralizing assay. The assay's specificity ranged between 97% and 98.5%. The average imprecision of the assay was a <5% coefficient of variation. Assay performance at 2 different cutoffs was evaluated to optimize predictive values. The automated LIAISON SARS-CoV-2 S1/S2 IgG assay brings efficient, sensitive, specific, and precise serological testing to the laboratory, with the capacity to test large amounts of samples per day; first results are available within 35 min, with a throughput of 170 tests/hour. The semiquantitative results provided by the test also associate with the presence of neutralizing antibodies and may provide a useful tool for the large-scale screening of convalescent-phase plasma for safe therapeutic use.


Subject(s)
Antibodies, Viral/blood , Betacoronavirus/immunology , Clinical Laboratory Techniques , Coronavirus Infections/diagnosis , Pneumonia, Viral/diagnosis , Serologic Tests , Antibodies, Neutralizing/blood , Automation, Laboratory , COVID-19 , COVID-19 Testing , Clinical Laboratory Techniques/methods , Clinical Laboratory Techniques/standards , Clinical Laboratory Techniques/statistics & numerical data , Coronavirus Infections/immunology , Humans , Immunoglobulin G/blood , Pandemics , Pneumonia, Viral/immunology , Reproducibility of Results , SARS-CoV-2 , Sensitivity and Specificity , Serologic Tests/methods , Serologic Tests/standards , Serologic Tests/statistics & numerical data , Spike Glycoprotein, Coronavirus/immunology
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