scholarly journals Evaluation of the automated LIAISON® SARS-CoV-2 TrimericS IgG assay for the detection of circulating antibodies

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Fabrizio Bonelli ◽  
Frank A. Blocki ◽  
Tina Bunnell ◽  
Edward Chu ◽  
Arriel De La O ◽  
...  
Keyword(s):  
New York ◽  
New Mexico ◽  
Vaccine Development ◽  
False Negative ◽  
Area Under The Curve ◽  
High Specificity ◽  
Epidemiological Studies ◽  
Youden Index ◽  
Characteristic Analysis ◽  
Highly Sensitive

Abstract Objectives COVID-19 has brought about tests from many manufacturers. While molecular and rapid antigen tests are targeted for early diagnosis, immunoassays have a larger role in epidemiological studies, understanding longitudinal immunity, and in vaccine development and response. Methods The performance of the LIAISON® SARS-CoV-2 TrimericS IgG assay was evaluated against the Beckman ACCESS SARS-CoV-2 IgG assay in New Mexico, and against the Siemens ADVIA Centaur COV2G assay in New York. Discordant samples were parsed using a microneutralization assay. Results A SARS-CoV-2 antibody positivity rate of 23.8% was observed in the samples tested in New York (September 2020), while in the same month the positivity rate was 1.5% in New Mexico. Positive and negative agreement were 67.6% (95% CI 49.5–82.6%) and 99.8% (95% CI 99.5–99.9%), respectively, with the Beckman test, and 98.0% (95% CI 95.7–99.3%) and 94.8% (95% CI 93.4–96.0%), respectively, with the Siemens test. Receiver operating characteristic analysis for the detection of SARS-CoV-2 antibodies discloses an AUC, area under the curve, of 0.996 (95% CI 0.992–0.999) for the LIAISON® SARS-CoV-2 TrimericS IgG assay. The criterion associated to the Youden Index was determined to be >12.9 kAU/L with a sensitivity of 99.44% and a specificity of 99.82%. Conclusions The LIAISON® SARS-CoV-2 TrimericS IgG assay is highly sensitive and specific. The balance of these parameters, without emphasis on high specificity alone, is particularly important when applied to high prevalence populations, where a highly sensitive assay will result in reporting a lower number of false negative subjects.

scholarly journals Sensitive Blood-Based Detection of Asbestos-Associated Diseases Using Cysteine-Rich Angiogenic Inducer 61 as Circulating Protein Biomarker

2020 ◽  
Author(s):  
Kai Bartkowiak ◽  
Swaantje Casjens ◽  
Antje Andreas ◽  
Lucija Ačkar ◽  
Simon A Joosse ◽  
...  
Keyword(s):  
Large Scale ◽  
Mononuclear Cells ◽  
Area Under The Curve ◽  
Immunofluorescent Staining ◽  
Youden Index ◽  
Enzyme Linked Immunosorbent Assay ◽  
Characteristic Analysis ◽  
Clinical Sensitivity ◽  
Associated Diseases ◽  
Healthy Control

Abstract Background Detection of asbestos-associated diseases like asbestosis or mesothelioma is still challenging. We sought to improve the diagnosis of benign asbestos-associated disease (BAAD) by detection of the protein cysteine-rich angiogenic inducer 61 (Cyr61) in human plasma. Methods Plasma Cyr61 was quantified using an enzyme-linked immunosorbent assay. Plasma samples from males diagnosed with BAAD, but without a malignant disease (n = 101), and malignant mesothelioma (n = 21; 15 males, 6 females), as well as nonasbestos-exposed healthy control participants (n = 150; 58 males, 92 females) were analyzed. Clinical sensitivity and specificity of Cyr61 were determined by receiver operating characteristic analysis. Results The median plasma Cyr61 concentration for healthy control participants was 0.27 ng/mL. Cytoplasmic Cyr61 in peripheral blood mononuclear cells from healthy control participants was evenly distributed, as detected by immunofluorescent staining. The increase in plasma Cyr61 concentrations in the BAAD study group was statistically significant compared to the healthy control participants (P < 0.0001). For the detection of BAAD vs male healthy control participants, clinical sensitivity was 88% and clinical specificity 95% with an area under the curve of 0.924 at maximal Youden Index. For a predefined clinical specificity of 100%, the clinical sensitivity was 76%. For male mesothelioma patients vs male healthy control participants, the clinical sensitivity at maximal Youden Index was 95% with a clinical specificity of 100% (area under the curve, 0.997) and for a predefined clinical specificity of 100%, the clinical sensitivity was 93%. Conclusions In our study, plasma Cyr61 protein concentrations showed to be a new biomarker for asbestos-associated diseases like BAAD and mesothelioma in men, which deserves further investigation in large-scale cohort studies.

scholarly journals New Latex Bead Agglutination Assay for Differential Diagnosis of Cattle Infected with Mycobacterium bovis and Mycobacterium avium subsp. paratuberculosis

2004 ◽  
Vol 11 (6) ◽  
pp. 1070-1074 ◽  
Author(s):  
Hye Cheong Koo ◽  
Yong Ho Park ◽  
Jongsam Ahn ◽  
W. Ray Waters ◽  
Mary Jo Hamilton ◽  
...  
Keyword(s):  
Differential Diagnosis ◽  
Mycobacterium Bovis ◽  
Mycobacterium Avium ◽  
Present Report ◽  
Area Under The Curve ◽  
High Specificity ◽  
Culture Method ◽  
Latex Bead ◽  
Characteristic Analysis ◽  
Agglutination Assay

ABSTRACT Extensive studies have shown that the current assays used to identify cattle infected with Mycobacterium bovis or Mycobacterium avium subsp. paratuberculosis are not sufficiently sensitive and specific to detect all infected animals, especially animals recently infected with the pathogens. In the present report we show that these limitations might be overcome with a latex bead agglutination assay (LBAA). With the specific immunodominant epitope (ESAT6-p) of M. bovis, we developed an LBAA and enzyme immunoassay (EIA) for that purpose and compared them with the “gold standard” culture method and skin test for their efficacy in detecting bovine tuberculosis. When sera from control healthy cows (n = 10), M. avium subsp. paratuberculosis-positive cattle (naturally infected, n = 16; experimentally infected, n = 8), and M. bovis-positive cattle (naturally infected, n = 49;experimentally infected, n = 20) were applied to an EIA and an LBAA developed with ESAT6-p, the two tests showed similar sensitivity (97.1% by EIA, 95.7% by LBAA), high specificity (94.2% by EIA, 100% by LBAA), and a positive correlation (kappa value, 0.85; correlation rate, 93.2%; correlation coefficient, 0.64). Receiver operating characteristic analysis of EIA results and comparison with the culture method determined a suitable cutoff value at 0.469, with an area under the curve of 0.991 (95% confidence interval, 0.977 to 1.0). As LBAA didn't show any positive reactions with sera from uninfected control cows or M. avium subsp. paratuberculosis-infected cattle, which were confirmed to be free of M. bovis by culture or PCR, LBAA using the ESAT6-p can be a rapid and useful M. bovis diagnostic assay. The data suggest that rapid, sensitive, and specific assays can be developed with peptides containing immunodominant epitopes present in proteins uniquely expressed in M. bovis or M. avium subsp. paratuberculosis for differential diagnosis of cattle infected with M. bovis or M. avium subsp. paratuberculosis.

scholarly journals Cutoff Point of TyG Index for Metabolic Syndrome in Brazilian Farmers

2021 ◽  
Vol 5 (Supplement_2) ◽  
pp. 1031-1031
Author(s):  
Júlia Ferreira ◽  
Eliana Zandonade ◽  
Olívia Bezerra ◽  
Luciane Salaroli
Keyword(s):  
Metabolic Syndrome ◽  
Area Under The Curve ◽  
Epidemiological Studies ◽  
Cutoff Point ◽  
Youden Index ◽  
Roc Curve Analysis ◽  
Cross Sectional ◽  
Insulin Resistant ◽  
Tyg Index ◽  
Unified Health System

Abstract Objectives The determination of Insulin Resistance (IR) requires sophisticated and costly methods, for this reason the TyG Index was proposed. However, there are still no studies in Brazil using Metabolic Syndrome (MetS) as a predictor of IR. Thus, the aim of this study was to determine the cutoff point for TyG as one of the indirect indices for MetS in a rural Brazilian population. Methods Cross-sectional observational epidemiological study conducted in a rural municipality in Brazil. The study population were 790 adult family farmers. The TyG index was calculated: Ln [fasting triglycerides (mg/dL) x fasting glycemia (mg/dL)]/2, and MetS was defined using the NCEP-ATPIII and IDF criteria. To describe the study variables, measures of central tendency and dispersion measures were used. For association analysis, the Mann-Whitney U test was used and the comparison between means was made using the Kruskal-Wallis test. For correlations, Spearman's correlation test was used. The cutoff values of TyG Index for MetS were obtained using the Receiver Operating Characteristic (ROC) curve analysis with the area under the curve (AUC) and the Youden Index. Results The median TyG values were higher among individuals diagnosed with MetS (P < 0.001), and increased according to the aggregation of the components of MetS. All MetS components were correlated with TyG (P < 0.001). The AUC for NCEP was 0.873 (0.848–0.896; P < 0.001), with Youden's cutoff point of Ln 4.52 (sensitivity: 84.30%; specificity: 75.75%). The AUC for IDF was 0.867 (0.842–0.890; P < 0.001), with Youden's cutoff point of Ln 4.55 (sensitivity: 80.0%; specificity: 79.82%). A cutoff point of Ln 4.52 was defined. Conclusions The TyG Index is a reliable marker for identifying insulin-resistant individuals, and correlates with the metabolic changes present in MetS. A cutoff point of Ln 4,52 has good sensitivity and specificity in both diagnostic criteria of MetS, being useful both in clinical practice and epidemiological studies, and can represent an important tool for the creation of protocols for promotion, protection and recovery health of rural populations. Funding Sources Research Program of the Unified Health System (PPSUS), through the notice FAPES/CNPq/Decit-SCTIE-MS/SESA No. 05/2015 – PPSUS.

scholarly journals A novel specific artificial intelligence-based method to identify COVID-19 cases using simple blood exams

2020 ◽  
Author(s):  
Felipe Soares ◽  
Aline Villavicencio ◽  
Flávio Sanson Fogliatto ◽  
Maria Helena Pitombeira Rigatto ◽  
Michel José Anzanello ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Predictive Value ◽  
Missing Values ◽  
False Negative ◽  
High Specificity ◽  
Healthcare Systems ◽  
Emergency Rooms ◽  
Predictive Values ◽  
Link Type ◽  
Highly Sensitive

BackgroundThe SARS-CoV-2 virus responsible for COVID-19 poses a significant challenge to healthcare systems worldwide. Despite governmental initiatives aimed at containing the spread of the disease, several countries are experiencing unmanageable increases in the demand for ICU beds, medical equipment, and larger testing capacity. Efficient COVID-19 diagnosis enables healthcare systems to provide better care for patients while protecting caregivers from the disease. However, many countries are constrained by the limited amount of test kits available, lack of equipment and trained professionals. In the case of patients visiting emergency rooms (ERs) with a suspect of COVID-19, prompt diagnosis may improve the outcome and even provide information for efficient hospital management. In such a context, a quick, inexpensive and readily available test to perform an initial triage in ERs could help to smooth patient flow, provide better patient care, and reduce the backlog of exams.MethodsIn this Case-control quantitative study, we developed a strategy backed by artificial intelligence to perform an initial screening of suspect COVID-19 patients. We developed a machine learning classifier that takes widely available simple blood exams as input and classifies samples as likely to be positive (having SARS-CoV-2) or negative (not having SARS-CoV-2). Based on this initial classification, positive cases can be referred for further highly sensitive testing (e.g. CT scan, or specific antibodies). We used publicly available data from the Albert Einstein Hospital in Brazil from 5,644 patients. Focusing on simple blood exam figures as main predictors, a sample of 599 subjects that had the fewest missing values for 16 common exams were selected. From these 599 patients, 81 tested positive for SARS-CoV-2 (determined by RT-PCR). Based on the reduced dataset, we built an artificial intelligence classification framework, ER-CoV, aiming at determining if suspect patients arriving in ER were likely to be negative for SARS-CoV-2, that is, to predict if that suspect patient is negative for COVID-19. The primary goal of this investigation is to develop a classifier with high specificity and high negative predictive values, with reasonable sensitivity.FindingsWe identified that our AI framework achieved an average specificity of 85.98% [95%CI: 84.94 – 86.84] and negative predictive value (NPV) of 94.92% [95%CI: 94.37% – 95.37%]. Those values are completely aligned with our goal of providing an effective low-cost system to triage suspect patients in ERs. As for sensitivity, our model achieved an average of 70.25% [95%CI: 66.57% – 73.12%] and positive predictive value (PPV) of 44.96% [95%CI: 43.15% – 46.87%]. The area under the curve (AUC) of the receiver operating characteristic (ROC) was 86.78% [95%CI: 85.65% – 87.90%]. An error analysis (inspection of which patients were misclassified) identified that, on average, 28% of the false negative results would have been hospitalized anyway; thus the model is making mistakes for severe cases that would not be overlooked, partially mitigating the fact that the test is not highly sensitive. All code for our AI model, called ER-CoV is publicly available at https://github.com/soares-f/ER-CoV.InterpretationBased on the capacity of our model to accurately predict which cases are negative from suspect patients arriving in emergency rooms, we envision that this framework may play an important role in patient triage. Probably the most important outcome is related to testing availability, which at this point is extremely low in many countries. Considering the achieved specificity, we could reduce by at least 90% the number of SARS-CoV-2 tests performed in emergency rooms, with around 5% chance of getting a false negative. The second important outcome is related to patient management in hospitals. Patients predicted as positive by our framework could be immediately separated from other patients while waiting for the results of confirmatory tests. This could reduce the spread rate within hospitals since in many of them all suspect cases are kept in the same ward. In Brazil, where the data was collected, rate infection is starting to quickly spread and the lead time of a SARS-CoV-2 may be up to 2 weeks.FundingThe University of Sheffield provided financial support for the Ph.D. scholarship for Felipe SoaresProf. Fogliatto’s research is funded by CNPq [Grant # 303509/2015-5].Prof. Anzanello’s research is funded by CNPq [Grant # 306724/2018-9].

scholarly journals Diagnostic and Prognostic Performance of Liquid Biopsy-Derived Exosomal MicroRNAs in Thyroid Cancer Patients: A Systematic Review and Meta-Analysis

Cancers ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 4295 ◽  
Author(s):  
Eman A. Toraih ◽  
Rami M. Elshazli ◽  
Lily N. Trinh ◽  
Mohammad H. Hussein ◽  
Abdallah A. Attia ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Meta Analysis ◽  
False Negative ◽  
Area Under The Curve ◽  
High Sensitivity ◽  
High Specificity ◽  
Likelihood Ratios ◽  
Discriminative Ability ◽  
Exosomal Mirnas ◽  
True False

Circulatory tumor-derived exosomal microRNAs (miRNAs) play key roles in cancer development/progression. We aimed to assess the diagnostic/prognostic value of circulating exosomal miRNA in thyroid cancer (TC). A search in PubMed, Scopus, Web of Science, and Science Direct up to 22 May 2021 was performed. The true/false positive (TP/FP) and true/false negative (TN/FN) rates were extracted from each eligible study to obtain the pooled sensitivity, specificity, positive/negative likelihood ratios (PLR/NLR), diagnostic odds ratio (DOR), and their 95% confidence intervals (95%CIs). The meta-analysis included 12 articles consisting of 1164 Asian patients and 540 controls. All miRNAs were quantified using qRT-PCR assays. The pooled sensitivity was 82% (95%CI = 77–86%), pooled specificity was 76% (95%CI = 71–80%), and pooled DOR was 13.6 (95%CI = 8.8–21.8). The best biomarkers with high sensitivity were miR-16-2-3p (94%), miR-223-5p (91%), miR-130a-3p (90%), and miR182-5p (94%). Similarly, they showed high specificity, in addition to miR-34c-5p. Six panels of two to four exosomal miRNAs showed higher diagnostic values with an area under the curve (AUC) ranging from 0.906 to 0.981. The best discriminative ability to differentiate between cancer and non-cancer individuals was observed for miR-146b-5p + miR-223-5p + miR-182-5p (AUC = 0.981, sensitivity = 93.8% (84.9–98.3), specificity = 92.9% (76.5–99.1)). In conclusion, the expression levels of exosomal miRNAs could predict TC.

Comparison Study of the Rates of Manual Peripheral Blood Smear Review From 3 Automated Hematology Analyzers, Unicel DxH 800, ADVIA 2120i, and XE 2100, Using International Consensus Group Guidelines

2012 ◽  
Vol 136 (11) ◽  
pp. 1408-1413 ◽  
Author(s):  
Sue Jung Kim ◽  
Yoonjung Kim ◽  
Saeam Shin ◽  
Jaewoo Song ◽  
Jong Rak Choi
Keyword(s):  
New York ◽  
Peripheral Blood ◽  
False Positive ◽  
Clinical Laboratory ◽  
False Negative ◽  
High Sensitivity ◽  
High Specificity ◽  
Peripheral Blood Smear ◽  
International Consensus ◽  
Consensus Group

Context.—In the clinical laboratory, it is important both to reduce the number of peripheral blood slide reviews to save time and money and to avoid reporting false results. Objective.—To determine differences in the slide review rates of 3 widely used automated hematologic analyzers, the Unicel DxH 800 (Beckman Coulter Inc, Fullerton, California), ADVIA 2120i (Siemens Diagnostics, Tarrytown, New York), and XE 2100 (Sysmex, Kobe, Japan), using International Consensus Group for Hematology Review guidelines. Design.—A total of 1485 samples were tested, and 300 were manually reviewed. Slide review rates, sensitivity, specificity, and false-positive and false-negative rates were estimated using consensus group rules and compared using χ2 tests, Fisher exact tests, or generalized estimating equations. Results.—Unicel DxH 800, ADVIA 2120i, and XE 2100 showed 22.8%, 20.2%, and 28.6% slide review rates; 14.3%, 14.3%, and 9.7% false-negative rates; and 13.7, 11.3%, and 17.3% false-positive rates, respectively. All analyzers showed significantly higher false-negative rates than that of the consensus group (2.9%). Conclusions.—False-negative rates were higher than the recommended levels. Among 3 automated hematologic analyzers, XE 2100 showed the highest rate of slide review. Because the present study clearly shows that the slide review rates have distinct characteristics among the studied analyzers, each individual laboratory should consider selecting the most appropriate analyzer according to clinical characteristics. Analyzers with high sensitivity may be advantageous in outpatient settings for screening patients, whereas analyzers with high specificity may be beneficial in inpatient settings for efficient patient care.

scholarly journals Novel Prehospital Triage Scale for Detecting Large Vessel Occlusion and Its Cause

2021 ◽  
Author(s):  
Jianan Wang ◽  
Xiaoxian Gong ◽  
Wansi Zhong ◽  
Ying Zhou ◽  
Min Lou
Keyword(s):  
Atrial Fibrillation ◽  
Predictive Value ◽  
Validation Cohort ◽  
Area Under The Curve ◽  
Large Vessel ◽  
Basilar Artery Occlusion ◽  
Youden Index ◽  
Large Vessel Occlusion ◽  
Characteristic Analysis ◽  
Vessel Occlusion

Background Patients with large vessel occlusion stroke (LVOS) need to be rapidly identified and transferred to comprehensive stroke centers. However, current prehospital evaluation and strategies still remain challenging. Methods and Results We retrospectively reviewed our prospectively collected database of patients with acute ischemic stroke (AIS). Based on the items of National Institutes of Health Stroke Scale and medical history that had a strong association with LVOS, we designed the 4‐item Stroke Scale (4I‐SS) and validated it in multi‐centers. The 4I‐SS incorporated gaze, level of consciousness, arm weakness, and atrial fibrillation. Receiver operating characteristic analysis was used to compare the 4I‐SS with previously established prehospital prediction scales. Finally, 1630 and 11 440 patients were included in the derivation and validation cohort, respectively. In the validation cohort, Youden Index, area under the curve, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of the 4I‐SS≥4 to predict LVOS were 0.494, 0.800, 0.657, 0.837, 0.600, 0.868, and 0.788, respectively, and that of the 4I‐SS≥7 to predict basilar artery occlusion were 0.200, 0.669, 0.229, 0.971, 0.066, 0.974, and 0.899, respectively. Youden Index and area under the curve were higher than previously published scales for predicting LVOS. Further analysis showed that for predicting whether cardiogenic embolism was the cause, its accuracy was 0.922 when the 4I‐SS score, including atrial fibrillation, was ≥6, and its accuracy of predicting the occluded vessel was intracranial internal carotid artery or M1 segment of the middle cerebral artery when it was ≥7 was 0.590. Conclusions The 4I‐SS is an effective and simple tool that can identify LVOS and its cause. Registration URL: https://www.clinicaltrials.gov ; Unique identifier: NCT03317639.

scholarly journals Effect of Environmental Pollutants PM2.5, CO, NO2, and O3 on the Incidence and Mortality of SARS-CoV-2 Infection in Five Regions of the USA

2021 ◽  
Vol 18 (15) ◽  
pp. 7810
Author(s):  
Sultan Ayoub Meo ◽  
Abdulelah Adnan Abukhalaf ◽  
Omar Mohammed Alessa ◽  
Abdulrahman Saad Alarifi ◽  
Waqas Sami ◽  
...  
Keyword(s):  
New York ◽  
New Mexico ◽  
Los Angeles ◽  
Environmental Pollution ◽  
Environmental Pollutants ◽  
Daily Basis ◽  
First Case ◽  
Incidence And Mortality ◽  
Unit Increase ◽  
The Usa

In recent decades, environmental pollution has become a significant international public problem in developing and developed nations. Various regions of the USA are experiencing illnesses related to environmental pollution. This study aims to investigate the association of four environmental pollutants, including particulate matter (PM2.5), carbon monoxide (CO), Nitrogen dioxide (NO2), and Ozone (O3), with daily cases and deaths resulting from SARS-CoV-2 infection in five regions of the USA, Los Angeles, New Mexico, New York, Ohio, and Florida. The daily basis concentrations of PM2.5, CO, NO2, and O3 were documented from two metrological websites. Data were obtained from the date of the appearance of the first case of (SARS-CoV-2) in the five regions of the USA from 13 March to 31 December 2020. Regionally (Los Angeles, New Mexico, New York, Ohio, and Florida), the number of cases and deaths increased significantly along with increasing levels of PM2.5, CO, NO2 and O3 (p < 0.05), respectively. The Poisson regression results further depicted that, for each 1 unit increase in PM2.5, CO, NO2 and O3 levels, the number of SARS-CoV-2 infections significantly increased by 0.1%, 14.8%, 1.1%, and 0.1%, respectively; for each 1 unit increase in CO, NO2, and O3 levels, the number of deaths significantly increased by 4.2%, 3.4%, and 1.5%, respectively. These empirical estimates demonstrate an association between the environmental pollutants PM2.5, CO, NO2, and O3 and SARS-CoV-2 infections, showing that they contribute to the incidence of daily cases and daily deaths in the five different regions of the USA. These findings can inform health policy decisions about combatting the COVID-19 pandemic outbreak in these USA regions and internationally by supporting a reduction in environmental pollution.

scholarly journals Measles Virus IgG Avidity Assay for Use in Classification of Measles Vaccine Failure in Measles Elimination Settings

2012 ◽  
Vol 19 (11) ◽  
pp. 1810-1817 ◽  
Author(s):  
Sara Mercader ◽  
Philip Garcia ◽  
William J. Bellini
Keyword(s):  
Measles Virus ◽  
Area Under The Curve ◽  
Epidemiological Data ◽  
Diagnostic Tools ◽  
High Avidity ◽  
Characteristic Analysis ◽  
Vaccine Failure ◽  
Avidity Assay ◽  
Igg Avidity

ABSTRACTIn regions where endemic measles virus has been eliminated, diagnostic assays are needed to assist in correctly classifying measles cases irrespective of vaccination status. A measles IgG avidity assay was configured using a commercially available measles-specific IgG enzyme immunoassay by modifying the protocol to include three 5-min washes with diethylamine (60 mM; pH 10.25) following serum incubation; serum was serially diluted, and the results were expressed as the end titer avidity index. Receiver operating characteristic analysis was used for evaluation and validation and to establish low (≤30%) and high (≥70%) end titer avidity thresholds. Analysis of 319 serum specimens expected to contain either high- or low-avidity antibodies according to clinical and epidemiological data indicated that the assay is highly accurate, with an area under the curve of 0.998 (95% confidence interval [CI], 0.978 to 1.000), sensitivity of 91.9% (95% CI, 83.2% to 97.0%), and specificity of 98.4% (95% CI, 91.6% to 100%). The assay is rapid (<2 h) and precise (standard deviation [SD], 4% to 7%). In 18 samples from an elimination setting outbreak, the assay identified 2 acute measles cases with low-avidity results; both were IgM-positive samples. Additionally, 11 patients (15 samples) with modified measles who were found to have high-avidity IgG results were classified as secondary vaccine failures; one sample with an intermediate-avidity result was not interpretable. In elimination settings, measles IgG avidity assays can complement existing diagnostic tools in confirming unvaccinated acute cases and, in conjunction with adequate clinical and epidemiologic investigation, aid in the classification of vaccine failure cases.

scholarly journals SARS-CoV-2 specific antibody and neutralization assays reveal the wide range of the humoral immune response to virus

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mikail Dogan ◽  
Lina Kozhaya ◽  
Lindsey Placek ◽  
Courtney Gunter ◽  
Mesut Yigit ◽  
...  
Keyword(s):  
Specific Antibody ◽  
Neutralizing Antibodies ◽  
Vaccine Development ◽  
High Specificity ◽  
Spike Protein ◽  
Humoral Immune ◽  
Specificity And Sensitivity ◽  
Wide Range ◽  
Specific Igg ◽  
Negative Controls

AbstractDevelopment of antibody protection during SARS-CoV-2 infection is a pressing question for public health and for vaccine development. We developed highly sensitive SARS-CoV-2-specific antibody and neutralization assays. SARS-CoV-2 Spike protein or Nucleocapsid protein specific IgG antibodies at titers more than 1:100,000 were detectable in all PCR+ subjects (n = 115) and were absent in the negative controls. Other isotype antibodies (IgA, IgG1-4) were also detected. SARS-CoV-2 neutralization was determined in COVID-19 and convalescent plasma at up to 10,000-fold dilution, using Spike protein pseudotyped lentiviruses, which were also blocked by neutralizing antibodies (NAbs). Hospitalized patients had up to 3000-fold higher antibody and neutralization titers compared to outpatients or convalescent plasma donors. Interestingly, some COVID-19 patients also possessed NAbs against SARS-CoV Spike protein pseudovirus. Together these results demonstrate the high specificity and sensitivity of our assays, which may impact understanding the quality or duration of the antibody response during COVID-19 and in determining the effectiveness of potential vaccines.

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