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A rapid and cost-effective diagnostic algorithm for the detection of SARS-CoV-2 infection in the emergency area by combining highly sensitive antigenic test and RT-PCR.

ABSTRACT: A diagnostic algorithm for SARS-CoV-2 infection in patients admitted to the emergency area, based on a combination of rapid antigen and molecular testing, has been evaluated with 3070 nasopharyngeal swabs. Compared to molecular test alone, the proposed algorithm allowed to significantly reduce costs and average time to results.

SUBMITTER: Salvetti S

PROVIDER: S-EPMC9126613 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature

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A rapid and cost-effective diagnostic algorithm for the detection of SARS-CoV-2 infection in the emergency area by combining highly sensitive antigenic test and RT-PCR.

Salvetti Sara S Lavinia Federica F Rosi Nico N Vanni Simone S Masotti Luca L Tarquini Roberto R Guarducci Silvia S Rossolini Gian Maria GM Montenora Iolanda I

Diagnostic microbiology and infectious disease 20220523 4

A diagnostic algorithm for SARS-CoV-2 infection in patients admitted to the emergency area, based on a combination of rapid antigen and molecular testing, has been evaluated with 3070 nasopharyngeal swabs. Compared to molecular test alone, the proposed algorithm allowed to significantly reduce costs and average time to results. ...[more]

PMID: 35700658

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Rapid antigenic test (TRA) versus RT-PCR: Experience of CHU IBN ROCHD Casablanca.

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COVID-19 in Neonates with Positive RT-PCR Test. Systematic Review.

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| S-EPMC8919773 | biostudies-literature

Development of an RT-PCR diagnostic test for an avian astrovirus.

Project description:Astroviruses are small round viruses that cause enteric disease in the young of several species. Detection and diagnosis of astrovirus infection in non-human hosts relies heavily on electron microscopy and fluorescent antibody tests. Recently, our laboratory isolated and sequenced an avian astrovirus from poult enteritis mortality syndrome affected turkeys. These studies describe the development of RT-PCR methods, which specifically detect regions of the viral capsid and polymerase genes, and demonstrate their use in detecting astrovirus infection in commercial turkey flocks.

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An accurate model for SARS-CoV-2 pooled RT-PCR test errors.

Project description:Pooling is a method of simultaneously testing multiple samples for the presence of pathogens. Pooling of SARS-CoV-2 tests is increasing in popularity, due to its high testing throughput. A popular pooling scheme is Dorfman pooling: test N individuals simultaneously, if the test is positive, each individual is then tested separately; otherwise, all are declared negative. Most analyses of the error rates of pooling schemes assume that including more than a single infected sample in a pooled test does not increase the probability of a positive outcome. We challenge this assumption with experimental data and suggest a novel and parsimonious probabilistic model for the outcomes of pooled tests. As an application, we analyse the false-negative rate (i.e. the probability of a negative result for an infected individual) of Dorfman pooling. We show that the false-negative rates under Dorfman pooling increase when the prevalence of infection decreases. However, low infection prevalence is exactly the condition when Dorfman pooling achieves highest throughput efficiency. We therefore urge the cautious use of pooling and development of pooling schemes that consider correctly accounting for tests' error rates.

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An effective tri-clustering algorithm combining expression data with gene regulation information.

Project description:MotivationBi-clustering algorithms aim to identify sets of genes sharing similar expression patterns across a subset of conditions. However direct interpretation or prediction of gene regulatory mechanisms may be difficult as only gene expression data is used. Information about gene regulators may also be available, most commonly about which transcription factors may bind to the promoter region and thus control the expression level of a gene. Thus a method to integrate gene expression and gene regulation information is desirable for clustering and analyzing.MethodsBy incorporating gene regulatory information with gene expression data, we define regulated expression values (REV) as indicators of how a gene is regulated by a specific factor. Existing bi-clustering methods are extended to a three dimensional data space by developing a heuristic TRI-Clustering algorithm. An additional approach named Automatic Boundary Searching algorithm (ABS) is introduced to automatically determine the boundary threshold.ResultsResults based on incorporating ChIP-chip data representing transcription factor-gene interactions show that the algorithms are efficient and robust for detecting tri-clusters. Detailed analysis of the tri-cluster extracted from yeast sporulation REV data shows genes in this cluster exhibited significant differences during the middle and late stages. The implicated regulatory network was then reconstructed for further study of defined regulatory mechanisms. Topological and statistical analysis of this network demonstrated evidence of significant changes of TF activities during the different stages of yeast sporulation, and suggests this approach might be a general way to study regulatory networks undergoing transformations.

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Estimating the false-negative test probability of SARS-CoV-2 by RT-PCR.

Project description:BackgroundReverse-transcription PCR (RT-PCR) assays are used to test for infection with the SARS-CoV-2 virus. RT-PCR tests are highly specific and the probability of false positives is low, but false negatives are possible depending on swab type and time since symptom onset.AimTo determine how the probability of obtaining a false-negative test in infected patients is affected by time since symptom onset and swab type.MethodsWe used generalised additive mixed models to analyse publicly available data from patients who received multiple RT-PCR tests and were identified as SARS-CoV-2 positive at least once.ResultsThe probability of a positive test decreased with time since symptom onset, with oropharyngeal (OP) samples less likely to yield a positive result than nasopharyngeal (NP) samples. The probability of incorrectly identifying an uninfected individual due to a false-negative test was considerably reduced if negative tests were repeated 24 hours later. For a small false-positive test probability (<0.5%), the true number of infected individuals was larger than the number of positive tests. For a higher false-positive test probability, the true number of infected individuals was smaller than the number of positive tests.ConclusionNP samples are more sensitive than OP samples. The later an infected individual is tested after symptom onset, the less likely they are to test positive. This has implications for identifying infected patients, contact tracing and discharging convalescing patients who are potentially still infectious.

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Serum miRNA profiling by quantitative RT PCR [RT-PCR Array 2]

Project description:Initial screening, the expression of 125 mature miRNA was compared between pooled control and autism samples by two microarray analysis. The differential expression of 14 miRNA was further validated by SYBR green quantitative PCR of Individual samples. Thirteen miRNAs were differetially expressed in autistic individuals compared to the controls (8 upregulated and 5 down regulated). miR-151a-3p, miR-181b-5p, miR-320a, miR-328, miR-433, miR-489, miR-572, and miR-663a were downregulated, while miR-101-3p, miR-106b-5p, miR-130a-3p, miR-195-5p, and miR-19b-3p were upregulated. We have identified a set of serum miRNAs that could be used as non-invasive biomarkers for autism.

2014-06-27 | GSE58848 | GEO

Serum miRNA profiling by quantitative RT PCR [RT-PCR Array 1]

2014-06-27 | GSE58847 | GEO

An optimized stepwise algorithm combining rapid antigen and RT-qPCR for screening of COVID-19 patients.

Project description:Background & aimWe investigated the combination of rapid antigen detection (RAD) and RT-qPCR assays in a stepwise procedure to optimize the detection of COVID-19.MethodsFrom August 2020 to November 2020, 43,399 patients were screened in our laboratory for COVID-19 diagnostic by RT-qPCR using nasopharyngeal swab. Overall, 4,691 of the 43,399 were found to be positive, and 200 were retrieved for RAD testing allowing comparison of diagnostic accuracy between RAD and RT-qPCR. Cycle threshold (Ct) and time from symptoms onset (TSO) were included as covariates.ResultsThe overall sensitivity, specificity, PPV, NPV, LR-, and LR+ of RAD compared with RT-qPCR were 72% (95%CI 62%-81%), 99% (95% CI95%-100%), 99% (95%CI 93%-100%), and 78% (95%CI 70%-85%), 0.28 (95%CI 0.21-0.39), and 72 (95%CI 10-208) respectively. Sensitivity was higher for patients with Ct ≤ 25 regardless of TSO: TSO ≤ 4 days 92% (95%CI 75%-99%), TSO > 4 days 100% (95%CI 54%-100%), and asymptomatic 100% (95%CI 78-100%). Overall, combining RAD and RT-qPCR would allow reducing from only 4% the number of RT-qPCR needed.ConclusionsThis study highlights the risk of misdiagnosing COVID-19 in 28% of patients if RAD is used alone. A stepwise analysis that combines RAD and RT-qPCR would be an efficient screening procedure for COVID-19 detection and may facilitate the control of the outbreak.

| S-EPMC8460002 | biostudies-literature

Real-life clinical sensitivity of SARS-CoV-2 RT-PCR test in symptomatic patients.

Project description:BackgroundUnderstanding the false negative rates of SARS-CoV-2 RT-PCR testing is pivotal for the management of the COVID-19 pandemic and it has implications for patient management. Our aim was to determine the real-life clinical sensitivity of SARS-CoV-2 RT-PCR.MethodsThis population-based retrospective study was conducted in March-April 2020 in the Helsinki Capital Region, Finland. Adults who were clinically suspected of SARS-CoV-2 infection and underwent SARS-CoV-2 RT-PCR testing, with sufficient data in their medical records for grading of clinical suspicion were eligible. In addition to examining the first RT-PCR test of repeat-tested individuals, we also used high clinical suspicion for COVID-19 as the reference standard for calculating the sensitivity of SARS-CoV-2 RT-PCR.ResultsAll 1,194 inpatients (mean [SD] age, 63.2 [18.3] years; 45.2% women) admitted to COVID-19 cohort wards during the study period were included. The outpatient cohort of 1,814 individuals (mean [SD] age, 45.4 [17.2] years; 69.1% women) was sampled from epidemiological line lists by systematic quasi-random sampling. The sensitivity (95% CI) for laboratory confirmed cases (repeat-tested patients) was 85.7% (81.5-89.1%) inpatients; 95.5% (92.2-97.5%) outpatients, 89.9% (88.2-92.1%) all. When also patients that were graded as high suspicion but never tested positive were included in the denominator, the sensitivity (95% CI) was: 67.5% (62.9-71.9%) inpatients; 34.9% (31.4-38.5%) outpatients; 47.3% (44.4-50.3%) all.ConclusionsThe clinical sensitivity of SARS-CoV-2 RT-PCR testing was only moderate at best. The relatively high false negative rates of SARS-CoV-2 RT-PCR testing need to be accounted for in clinical decision making, epidemiological interpretations, and when using RT-PCR as a reference for other tests.

| S-EPMC8139477 | biostudies-literature

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