Rapid COVID-19 antigenic tests: Usefulness of a modified method for diagnosis.
Ontology highlight
ABSTRACT:
SUBMITTER: Soleimani R
PROVIDER: S-EPMC8242554 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The identification of viral RNA using reverse transcription quantitative polymerase chain reaction (RT-qPCR) is the gold standard for identifying an infection caused by SARS-CoV-2. The limitations of RT-qPCR such as requirement of expensive instruments, trained staff and laboratory facilities led to development of rapid antigen tests (RATs). The performance of RATs has been widely evaluated and found to be varied in different settings. The present systematic review aims to evaluate the pooled sensitivity and specificity of the commercially available RATs. This review was registered on PROSPERO (registration number: CRD42021278105). Literature search was performed through PubMed, Embase and Cochrane COVID-19 Study Register to search studies published up to 26 August 2021. The overall pooled sensitivity and specificity of RATs and subgroup analyses were calculated. Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) was used to assess the risk of bias in each study. The overall pooled sensitivity and specificity of RATs were 70% (95% CI: 69-71) and 98% (95% CI: 98-98), respectively. In subgroup analyses, nasal swabs showed the highest sensitivity of 83% (95% CI: 80-86) followed by nasopharyngeal swabs 71% (95% CI: 70-72), throat swabs 69% (95% CI: 63-75) and saliva 68% (95% CI: 59-77). Samples from symptomatic patients showed a higher sensitivity of 82% (95% CI: 82-82) as compared to asymptomatic patients at 68% (95% CI: 65-71), while a cycle threshold (Ct) value ≤25 showed a higher sensitivity of 96% (95% CI: 95-97) as compared to higher Ct value. Although the sensitivity of RATs needs to be enhanced, it may still be a viable option in places where laboratory facilities are lacking for diagnostic purposes in the early phase of disease.
| S-EPMC8774565 | biostudies-literature
Project description:The aim of our study was to evaluate the diagnostic performance of two antigen rapid diagnostic tests (Ag-RDTs) to diagnose severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We evaluated Panbio and SD-Biosensor Ag-RDTs. We employed 186 polymerase chain reaction (PCR) negative samples to evaluate the specificity and 170 PCR positive samples to assess the sensitivity. We evaluated their sensitivity according to Cycle threshold (C t ) values and days post onset of symptoms (d.p.o.). Tests were compared using the McNemar's test. Agreement was evaluated using the kappa score. Specificity was 100% for Panbio and 97.3% for SD-Biosensor. Sensitivity for samples with C t ≤ 20 was 100% for both assays and for samples with C t = 20-25 was 93.0% (Panbio) and 95.3% (SD-Biosensor) (p = 1.000). Sensitivity decreased for samples wit C t = 25-30 (Panbio: 41.3%, SD-Biosensor: 52.2%, p = 0.125) and samples with C t ≥ 30 (Panbio: 5.0%, SD-Biosensor: 17.5%, p = 0.063). Sensitivity within seven d.p.o. was 87.7% for Panbio and 90.4% for SD-Biosensor and notably decreased after seven d.p.o. Agreement with PCR was excellent for high viral load samples (C t ≤ 25): Panbio, 98.9%, kappa = 0.974; SD-Biosensor, 97.4%, kappa = 0.940. Agreement between Ag-RDTs was excellent (94.9%, kappa = 0.882). Panbio and SD-Biosensor Ag-RDTs showed excellent agreement and diagnostic performance results for samples with high viral loads (C t ≤ 25) or samples within seven d.p.o.
| S-EPMC8242635 | biostudies-literature
Project description:The antigen-based rapid diagnostic test (Ag-RDT) using saliva specimens is fast, noninvasive, and suitable for SARS-CoV-2 self-testing, unlike nasopharyngeal swab (NPS) testing. We evaluated a novel Beanguard gargle (BG)-based virus collection method that can be applied to Ag-RDT as an alternative to the current RT-PCR with an NPS for early diagnosis of COVID-19. This clinical trial comprised 102 COVID-19-positive patients hospitalized after a governmental screening process and 100 healthy individuals. Paired NPS and BG-based saliva specimens from COVID-19 patients and healthy individuals were analyzed using NPS-RT-PCR, BG-RT-PCR, and BG-Ag-RDTs, whose diagnostic performance for detecting SARS-CoV-2 was compared. BG-Ag-RDTs showed high sensitivity (97.8%) and specificity (100%) in 45 patients within 6 days of illness and detected all cases of SARS-CoV-2 Alpha and Delta variants. In 11 asymptomatic active COVID-19 cases, both BG-Ag-RDTs and BG-RT-PCR showed sensitivities and specificities of 100%. Sensitivities of BG-Ag-RDT and BG-RT-PCR toward salivary viral detection were highly concordant, with no discrimination between symptomatic (97.0%), asymptomatic (100%), or SARS-CoV-2 variant (100%) cases. The intermolecular interactions between SARS-CoV-2 spike proteins and truncated canavalin, an active ingredient from the bean extract (BE), were observed in terms of physicochemical properties. The detachment of the SARS-CoV-2 receptor-binding domain from hACE2 increased as the BE concentration increased, allowing the release of the virus from hACE2 for early diagnosis. Using BG-based saliva specimens remarkably enhances the Ag-RDT diagnostic performance as an alternative to NPS and enables noninvasive, rapid, and accurate COVID-19 self-testing and mass screening, supporting efficient COVID-19 management. IMPORTANCE An Ag-RDT is less likely to be accepted as an initial test method for early diagnosis owing to its low sensitivity. However, our self-collection method, Ag-RDT using BG-based saliva specimens, showed significantly enhanced detection sensitivity and specificity toward SARS-CoV-2 including the Alpha and Delta variants in all patients tested within 6 days of illness. The method represents an attractive alternative to nasopharyngeal swabs for the early diagnosis of symptomatic and asymptomatic COVID-19 cases. The evidence suggests that the method could have a potential for mass screening and monitoring of COVID-19 cases.
| S-EPMC8849053 | biostudies-literature
Project description:Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagnosis that was based and cross-validated on the routine blood tests of 5333 patients with various bacterial and viral infections, and 160 COVID-19-positive patients. We selected the operational ROC point at a sensitivity of 81.9% and a specificity of 97.9%. The cross-validated AUC was 0.97. The five most useful routine blood parameters for COVID-19 diagnosis according to the feature importance scoring of the XGBoost algorithm were: MCHC, eosinophil count, albumin, INR, and prothrombin activity percentage. t-SNE visualization showed that the blood parameters of the patients with a severe COVID-19 course are more like the parameters of a bacterial than a viral infection. The reported diagnostic accuracy is at least comparable and probably complementary to RT-PCR and chest CT studies. Patients with fever, cough, myalgia, and other symptoms can now have initial routine blood tests assessed by our diagnostic tool. All patients with a positive COVID-19 prediction would then undergo standard RT-PCR studies to confirm the diagnosis. We believe that our results represent a significant contribution to improvements in COVID-19 diagnosis.
| S-EPMC8144373 | biostudies-literature
Project description:WHO recommends a minimum of 80% sensitivity and 97% specificity for antigen-detection rapid diagnostic tests (Ag-RDTs), which can be used for patients with symptoms consistent with COVID-19. However, after the acute phase when viral load decreases, use of Ag-RDTs might lead to high rates of false negatives, suggesting that the tests should be replaced by a combination of molecular and serological tests. When the likelihood of having COVID-19 is low, such as for asymptomatic individuals in low prevalence settings, for travel, return to schools, workplaces, and mass gatherings, Ag-RDTs with high negative predictive values can be used with confidence to rule out infection. For those who test positive in low prevalence settings, the high false positive rate means that mitigation strategies, such as molecular testing to confirm positive results, are needed. Ag-RDTs, when used appropriately, are promising tools for scaling up testing and ensuring that patient management and public health measures can be implemented without delay.
| S-EPMC7906660 | biostudies-literature
Project description:Prompt diagnosis, patient isolation, and contact tracing are key measures to contain the coronavirus disease 2019 (COVID-19). Molecular tests are the current gold standard for COVID-19 detection, but are carried out at central laboratories, delaying treatment and control decisions. Here we describe a portable assay system for rapid, onsite COVID-19 diagnosis. Termed CODA (CRISPR Optical Detection of Anisotropy), the method combined isothermal nucleic acid amplification, activation of CRISPR/Cas12a, and signal generation in a single assay, eliminating extra manual steps. Importantly, signal detection was based on the ratiometric measurement of fluorescent anisotropy, which allowed CODA to achieve a high signal-to-noise ratio. For point-of-care operation, we built a compact, standalone CODA device integrating optoelectronics, an embedded heater, and a microcontroller for data processing. The developed system completed SARS-CoV-2 RNA detection within 20 min of sample loading; the limit of detection reached 3 copy/μL. When applied to clinical samples (10 confirmed COVID-19 patients; 10 controls), the rapid CODA test accurately classified COVID-19 status, in concordance with gold-standard clinical diagnostics.
| S-EPMC7846465 | biostudies-literature
Project description:Appropriate isolation guidelines for COVID-19 patients are warranted. Currently, isolating for fixed time is adopted in most countries. However, given the variability in viral dynamics between patients, some patients may no longer be infectious by the end of isolation, whereas others may still be infectious. Utilizing viral test results to determine isolation length would minimize both the risk of prematurely ending isolation of infectious patients and the unnecessary individual burden of redundant isolation of noninfectious patients. In this study, we develop a data-driven computational framework to compute the population-level risk and the burden of different isolation guidelines with rapid antigen tests (i.e., lateral flow tests). Here, we show that when the detection limit is higher than the infectiousness threshold values, additional consecutive negative results are needed to ascertain infectiousness status. Further, rapid antigen tests should be designed to have lower detection limits than infectiousness threshold values to minimize the length of prolonged isolation. Utilizing viral test results to determine isolation length would minimize both the risk of prematurely ending isolation of infectious patients and the unnecessary individual burden of redundant isolation of noninfectious patients. Here, the authors develop a framework to compute the population-level risk of different isolation guidelines with rapid antigen tests.
| S-EPMC9392070 | biostudies-literature
Project description:There is a need for understanding and establishment of the most appropriate testing algorithm for COVID-19 diagnosis in asymptomatic high-risk groups. Here, we present a retrospective analysis of RT-PCR results obtained from 412 cases tested negative for coronavirus disease 2019 (COVID-19) by rapid antigen testing method. Among 178 (43.2%) asymptomatic individuals, 44.9% of the high risk contacts, 12.2% of police custody individuals, 22.22% of the pregnant women and 33.33% of individuals hospitalised for preoperative or other medical conditions showed RT-PCR positivity. Our results suggest a need for focussed and intensive (multi-modality) testing in groups at high risk for SARS-CoV-2 infection.
| S-EPMC8143916 | biostudies-literature
Project description:Many previous studies claim to have developed machine learning models that diagnose COVID-19 from blood tests. However, we hypothesize that changes in the underlying distribution of the data, so called domain shifts, affect the predictive performance and reliability and are a reason for the failure of such machine learning models in clinical application. Domain shifts can be caused, e.g., by changes in the disease prevalence (spreading or tested population), by refined RT-PCR testing procedures (way of taking samples, laboratory procedures), or by virus mutations. Therefore, machine learning models for diagnosing COVID-19 or other diseases may not be reliable and degrade in performance over time. We investigate whether domain shifts are present in COVID-19 datasets and how they affect machine learning methods. We further set out to estimate the mortality risk based on routinely acquired blood tests in a hospital setting throughout pandemics and under domain shifts. We reveal domain shifts by evaluating the models on a large-scale dataset with different assessment strategies, such as temporal validation. We present the novel finding that domain shifts strongly affect machine learning models for COVID-19 diagnosis and deteriorate their predictive performance and credibility. Therefore, frequent re-training and re-assessment are indispensable for robust models enabling clinical utility.
| S-EPMC8960704 | biostudies-literature
Project description:During the Covid-19 pandemic, accurate PCR tests were augmented by the cheap, rapid, and logistically convenient, yet less sensitive antigen tests. In Israel, a testing policy shift was implemented due to limited availability of PCR tests during the Omicron surge. Thus, both PCR and antigen tests were used, as this was the only alternative for mass testing and surveillance at the time. Yet, evidence-based surveillance requires a robust understanding of the expected consequences of changing the testing policy. Using 41,065 paired tests performed by trained staff between January and April 2022 in Israel, we estimate how the sensitivity of antigen tests changes as a function of Ct value and other key covariates. The results reveal a logarithmic relationship between antigen detection probability and viral load, as quantified by Ct-values of the PCR tests. Further analysis shows a statistically significant association with an odds ratio of approximately 0.76 with each unit of Ct-value. The analysis suggests that in spite of their compromised sensitivity, antigen tests are a natural solution for routine use, while PCR tests should be considered in situations where a false negative result could have serious consequences. These findings are the foundations of policies that will utilize the strengths of the different tests, and achieve enhanced hybrid surveillance.
| S-EPMC10792091 | biostudies-literature