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End-point RT-PCR: A potential alternative for diagnosing coronavirus disease 2019 (COVID-19).

ABSTRACT: Real-time reverse transcription-polymerase chain reaction (RT-qPCR) is considered the "gold standard" for the direct diagnosis of SARS-CoV-2 infections. However, routine diagnosis by RT-qPCR is a limitation for many laboratories, mainly due to the infrastructure and/or disproportionate relationship between demand and supply of inputs. In this context, and to increase the diagnostic coverage of SARS-CoV-2 infections, we describe an alternative, sensitive and specific one-step end-point RT-PCR for the detection of the SARS-CoV-2 E gene. The performance of the RT-PCR was evaluated in 43 clinical samples, of which 10 and 33 were previously identified as negative and positive, respectively, by RT-qPCR. Among the positive samples, 15 and 18 were from asymptomatic and symptomatic individuals, respectively. Here, 32/33 of the positive samples in the RT-qPCR, including from asymptomatic individuals, were found positive in the RT-PCR (Ct 15.94-34.92). The analytical sensitivity of the assay was about 7.15-9 copies of vRNA/?L, and nonspecific amplifications were not observed in SARS-CoV-2 negative samples. Importantly, the RT-PCR reactions were performed in a 10??L final volume. Finally, considering specificity, analytical sensitivity and cost reduction, we believe that the RT-PCR platform described here may be a viable option for the diagnostic of SARS-CoV-2 infections in laboratories in which RT-qPCR is not available.

SUBMITTER: Silva Junior JVJ

PROVIDER: S-EPMC7598561 | biostudies-literature | 2021 Feb

REPOSITORIES: biostudies-literature

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End-point RT-PCR: A potential alternative for diagnosing coronavirus disease 2019 (COVID-19).

Silva Júnior José Valter Joaquim JVJ Merchioratto Ingryd I de Oliveira Pablo Sebastian Britto PSB Rocha Lopes Thaísa Regina TR Brites Patrícia Chaves PC de Oliveira Elehu Moura EM Weiblen Rudi R Flores Eduardo Furtado EF

Journal of virological methods 20201029

Real-time reverse transcription-polymerase chain reaction (RT-qPCR) is considered the "gold standard" for the direct diagnosis of SARS-CoV-2 infections. However, routine diagnosis by RT-qPCR is a limitation for many laboratories, mainly due to the infrastructure and/or disproportionate relationship between demand and supply of inputs. In this context, and to increase the diagnostic coverage of SARS-CoV-2 infections, we describe an alternative, sensitive and specific one-step end-point RT-PCR for ...[more]

PMID: 33130151

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Project description:BackgroundCoronavirus disease 2019 (COVID-19) has emerged as a global pandemic. According to the diagnosis and treatment guidelines of China, negative reverse transcription-polymerase chain reaction (RT-PCR) is the key criterion for discharging COVID-19 patients. However, repeated RT-PCR tests lead to medical waste and prolonged hospital stays for COVID-19 patients during the recovery period. Our purpose is to assess a model based on chest computed tomography (CT) radiomic features and clinical characteristics to predict RT-PCR negativity during clinical treatment.MethodsFrom February 10 to March 10, 2020, 203 mild COVID-19 patients in Fangcang Shelter Hospital were retrospectively included (training: n = 141; testing: n = 62), and clinical characteristics were collected. Lung abnormalities on chest CT images were segmented with a deep learning algorithm. CT quantitative features and radiomic features were automatically extracted. Clinical characteristics and CT quantitative features were compared between RT-PCR-negative and RT-PCR-positive groups. Univariate logistic regression and Spearman correlation analyses identified the strongest features associated with RT-PCR negativity, and a multivariate logistic regression model was established. The diagnostic performance was evaluated for both cohorts.ResultsThe RT-PCR-negative group had a longer time interval from symptom onset to CT exams than the RT-PCR-positive group (median 23 vs. 16 days, p < 0.001). There was no significant difference in the other clinical characteristics or CT quantitative features. In addition to the time interval from symptom onset to CT exams, nine CT radiomic features were selected for the model. ROC curve analysis revealed AUCs of 0.811 and 0.812 for differentiating the RT-PCR-negative group, with sensitivity/specificity of 0.765/0.625 and 0.784/0.600 in the training and testing datasets, respectively.ConclusionThe model combining CT radiomic features and clinical data helped predict RT-PCR negativity during clinical treatment, indicating the proper time for RT-PCR retesting.

Project description:Background Chest CT is used in the diagnosis of coronavirus disease 2019 (COVID-19) and is an important complement to reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose To investigate the diagnostic value and consistency of chest CT as compared with RT-PCR assay in COVID-19. Materials and Methods This study included 1014 patients in Wuhan, China, who underwent both chest CT and RT-PCR tests between January 6 and February 6, 2020. With use of RT-PCR as the reference standard, the performance of chest CT in the diagnosis of COVID-19 was assessed. In addition, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative) was analyzed as compared with serial chest CT scans for those with a time interval between RT-PCR tests of 4 days or more. Results Of the 1014 patients, 601 of 1014 (59%) had positive RT-PCR results and 888 of 1014 (88%) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95% confidence interval: 95%, 98%; 580 of 601 patients) based on positive RT-PCR results. In the 413 patients with negative RT-PCR results, 308 of 413 (75%) had positive chest CT findings. Of those 308 patients, 48% (103 of 308) were considered as highly likely cases and 33% (103 of 308) as probable cases. At analysis of serial RT-PCR assays and CT scans, the mean interval between the initial negative to positive RT-PCR results was 5.1 days ± 1.5; the mean interval between initial positive to subsequent negative RT-PCR results was 6.9 days ± 2.3. Of the 1014 patients, 60% (34 of 57) to 93% (14 of 15) had initial positive CT scans consistent with COVID-19 before (or parallel to) the initial positive RT-PCR results. Twenty-four of 57 patients (42%) showed improvement on follow-up chest CT scans before the RT-PCR results turned negative. Conclusion Chest CT has a high sensitivity for diagnosis of coronavirus disease 2019 (COVID-19). Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. © RSNA, 2020 Online supplemental material is available for this article. A translation of this abstract in Farsi is available in the supplement. ترجمه چکیده این مقاله به فارسی، در ضمیمه موجود است.

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End-point RT-PCR: A potential alternative for diagnosing coronavirus disease 2019 (COVID-19).

Publications

End-point RT-PCR: A potential alternative for diagnosing coronavirus disease 2019 (COVID-19).

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