The optimal diagnostic methods for COVID-19

Author:

Harahwa Tinotenda A.1,Lai Yau Thomas Ho2,Lim-Cooke Mae-Sing1,Al-Haddi Salah3,Zeinah Mohamed3,Harky Amer34

Affiliation:

1. St George’s Medical school, University of London , London , UK

2. Barts and the London School of Medicine and Dentistry, Queen Mary University of London , London , UK

3. Department of Cardiothoracic Surgery , Liverpool Heart and Chest Hospital , Liverpool , UK

4. Department of Integrative Biology , University of Liverpool , Liverpool , UK

Abstract

Abstract As the world continues to study and understand coronavirus disease (COVID-19), existing investigations and tests have been used to try and detect the virus to slow viral transmission and its global spread. A ‘gold-standard’ investigation has not yet been identified for detection and monitoring. Initially, computed tomography (CT) was the mainstay investigation as it shows the disease severity and recovery, and its images change at different stages of the disease. However, CT has been found to have limited sensitivity and negative predictive value in the early stages of the disease, and the value of its use has come under debate due to whether its images change the treatment plan, the risk of radiation, as well as its practicality with infection control. Therefore, there has been a shift to the use of other imaging modalities and tests, such as chest X-rays and ultrasound. Furthermore, the use of nucleic acid-based testing such as reverse-transcriptase polymerase chain reaction (RT-PCR) have proven useful with direct confirmation of COVID-19 infection. In this study, we aim to review and analyse current literature to compare RT-PCR, immunological biomarkers, chest radiographs, ultrasound and chest CT scanning as methods of diagnosing COVID-19.

Publisher

Walter de Gruyter GmbH

Subject

Biochemistry (medical),Clinical Biochemistry,Public Health, Environmental and Occupational Health,Health Policy,Medicine (miscellaneous)

Reference43 articles.

1. Tan, W, Zhao, X, Ma, X, Wang, W, Niu, P, Xu, W, et al.. Notes from the field a novel coronavirus genome identified in a cluster of pneumonia cases — Wuhan , China 2019 − 2020. China CDC Weekly 2020;2:61–2.

2. Wang, W, Xu, Y, Gao, R, Lu, R, Han, K, Wu, G, et al.. Detection of SARS-CoV-2 in different types of clinical specimens. JAMA 2020;323:1843–4. https://doi.org/10.1001/jama.2020.3786.

3. World Health Organisation (WHO). Laboratory testing for 2019 novel coronavirus (2019-nCoV) in suspected human cases; 2020. Available from: https://www.who.int/publications-detail/laboratory-testing-for-2019-novel-coronavirus-in-suspected-human-cases-20200117 [Accessed 26 May 2020].

4. ALNAP. Handbook of COVID-19 prevention and treatment; 2020. Available from: https://www.alnap.org/help-library/handbook-of-covid-19-prevention-and-treatment [Accessed 26 May 2020]. Accessed: 25 May 2020.

5. Ye, Z, Zhang, Y, Wang, Y, Huang, Z, Song, B. Chest CT manifestations of new coronavirus disease 2019 (COVID-19): a pictorial review. Eur Radiol 2020. https://doi.org/10.1007/s00330-020-06801-0 [Epub ahead of print].

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