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      The Estimation of Diagnostic Accuracy of Tests for COVID-19: A Scoping Review

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          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Highlights

          • Many SARS-CoV-2 diagnostic tests are available for patient use with incomplete evidence as to their diagnostic accuracy.

          • Current publications on SARS-CoV-2 diagnostic accuracy have imperfect study design, heterogeneous methods, and a high risk for bias.

          Summary

          Objectives

          To assess the methodologies used in the estimation of diagnostic accuracy of SARS-CoV-2 real-time reverse transcription polymerase chain reaction (rRT-PCR) and other nucleic acid amplification tests (NAATs) and to evaluate the quality and reliability of the studies employing those methods.

          Methods

          We conducted a systematic search of English-language articles published December 31, 2019-June 19, 2020. Studies of any design that performed tests on ≥10 patients and reported or inferred correlative statistics were included. Studies were evaluated using elements of the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) guidelines.

          Results

          We conducted a narrative and tabular synthesis of studies organized by their reference standard strategy or comparative agreement method, resulting in six categorizations. Critical study details were frequently unreported, including the mechanism for patient/sample selection and researcher blinding to results, which lead to concern for bias.

          Conclusions

          Current studies estimating test performance characteristics have imperfect study design and statistical methods for the estimation of test performance characteristics of SARS-CoV-2 tests. The included studies employ heterogeneous methods and overall have an increased risk of bias. Employing standardized guidelines for study designs and statistical methods will improve the process for developing and validating rRT-PCR and NAAT for the diagnosis of COVID-19.

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          Most cited references56

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          A Novel Coronavirus from Patients with Pneumonia in China, 2019

          Summary In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.)
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            Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding

            Summary Background In late December, 2019, patients presenting with viral pneumonia due to an unidentified microbial agent were reported in Wuhan, China. A novel coronavirus was subsequently identified as the causative pathogen, provisionally named 2019 novel coronavirus (2019-nCoV). As of Jan 26, 2020, more than 2000 cases of 2019-nCoV infection have been confirmed, most of which involved people living in or visiting Wuhan, and human-to-human transmission has been confirmed. Methods We did next-generation sequencing of samples from bronchoalveolar lavage fluid and cultured isolates from nine inpatients, eight of whom had visited the Huanan seafood market in Wuhan. Complete and partial 2019-nCoV genome sequences were obtained from these individuals. Viral contigs were connected using Sanger sequencing to obtain the full-length genomes, with the terminal regions determined by rapid amplification of cDNA ends. Phylogenetic analysis of these 2019-nCoV genomes and those of other coronaviruses was used to determine the evolutionary history of the virus and help infer its likely origin. Homology modelling was done to explore the likely receptor-binding properties of the virus. Findings The ten genome sequences of 2019-nCoV obtained from the nine patients were extremely similar, exhibiting more than 99·98% sequence identity. Notably, 2019-nCoV was closely related (with 88% identity) to two bat-derived severe acute respiratory syndrome (SARS)-like coronaviruses, bat-SL-CoVZC45 and bat-SL-CoVZXC21, collected in 2018 in Zhoushan, eastern China, but were more distant from SARS-CoV (about 79%) and MERS-CoV (about 50%). Phylogenetic analysis revealed that 2019-nCoV fell within the subgenus Sarbecovirus of the genus Betacoronavirus, with a relatively long branch length to its closest relatives bat-SL-CoVZC45 and bat-SL-CoVZXC21, and was genetically distinct from SARS-CoV. Notably, homology modelling revealed that 2019-nCoV had a similar receptor-binding domain structure to that of SARS-CoV, despite amino acid variation at some key residues. Interpretation 2019-nCoV is sufficiently divergent from SARS-CoV to be considered a new human-infecting betacoronavirus. Although our phylogenetic analysis suggests that bats might be the original host of this virus, an animal sold at the seafood market in Wuhan might represent an intermediate host facilitating the emergence of the virus in humans. Importantly, structural analysis suggests that 2019-nCoV might be able to bind to the angiotensin-converting enzyme 2 receptor in humans. The future evolution, adaptation, and spread of this virus warrant urgent investigation. Funding National Key Research and Development Program of China, National Major Project for Control and Prevention of Infectious Disease in China, Chinese Academy of Sciences, Shandong First Medical University.
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              Correlation of Chest CT and RT-PCR Testing in Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

              Background Chest CT is used for diagnosis of 2019 novel coronavirus disease (COVID-19), as an important complement to the reverse-transcription polymerase chain reaction (RT-PCR) tests. Purpose To investigate the diagnostic value and consistency of chest CT as compared with comparison to RT-PCR assay in COVID-19. Methods From January 6 to February 6, 2020, 1014 patients in Wuhan, China who underwent both chest CT and RT-PCR tests were included. With RT-PCR as reference standard, the performance of chest CT in diagnosing COVID-19 was assessed. Besides, for patients with multiple RT-PCR assays, the dynamic conversion of RT-PCR results (negative to positive, positive to negative, respectively) was analyzed as compared with serial chest CT scans for those with time-interval of 4 days or more. Results Of 1014 patients, 59% (601/1014) had positive RT-PCR results, and 88% (888/1014) had positive chest CT scans. The sensitivity of chest CT in suggesting COVID-19 was 97% (95%CI, 95-98%, 580/601 patients) based on positive RT-PCR results. In patients with negative RT-PCR results, 75% (308/413) had positive chest CT findings; of 308, 48% were considered as highly likely cases, with 33% as probable cases. By analysis of serial RT-PCR assays and CT scans, the mean interval time between the initial negative to positive RT-PCR results was 5.1 ± 1.5 days; the initial positive to subsequent negative RT-PCR result was 6.9 ± 2.3 days). 60% to 93% of cases had initial positive CT consistent with COVID-19 prior (or parallel) to the initial positive RT-PCR results. 42% (24/57) cases showed improvement in follow-up chest CT scans before the RT-PCR results turning negative. Conclusion Chest CT has a high sensitivity for diagnosis of COVID-19. Chest CT may be considered as a primary tool for the current COVID-19 detection in epidemic areas. 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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                Author and article information

                Contributors
                Journal
                J Infect
                J. Infect
                The Journal of Infection
                The British Infection Association. Published by Elsevier Ltd.
                0163-4453
                1532-2742
                31 August 2020
                31 August 2020
                Affiliations
                [a ]Section of Infectious Diseases, Department of Internal Medicine, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
                [b ]Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA
                [c ]School of Social Sciences, Rice University, MS 272, 5620 Greenbriar Dr, Houston, TX, 77005, USA
                [d ]UTHealth School of Public Health, Houston, TX, USA
                [e ]Houston HSR&D IQuESt, Michael E. DeBakey VA Medical Center, 2450 Holcombe Blvd, Houston, TX, 77021, USA
                [f ]Department of Epidemiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St, Houston, TX, 77030, USA
                Author notes
                [* ]Corresponding author: Elizabeth Y. Chiao, MD, The University of Texas MD Anderson Cancer Center, 1155 Pressler St., Unit 1340, Houston, TX, 77030; ph. (office): +1 713-792-1860 eychiao@ 123456mdanderson.org
                Article
                S0163-4453(20)30577-6
                10.1016/j.jinf.2020.08.043
                7457918
                32882315
                e11bcb0f-f2e9-4dae-8df6-8970d98da019
                © 2020 The British Infection Association. Published by Elsevier Ltd. All rights reserved.

                Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.

                History
                : 27 August 2020
                Categories
                Article

                Infectious disease & Microbiology
                sars-cov-2,covid-19,diagnostic accuracy,sensitivity,specificity,quadas-2

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