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A contemporary insight of metabolomics approach for COVID-19: Potential for novel therapeutic and diagnostic targets.
Asim, Mohammad; Sathian, Brijesh; Banerjee, Indrajit; Robinson, Jared.
Afiliação
  • Asim M; Surgery Department, Trauma Surgery, Hamad General Hospital, Doha, Qatar.
  • Sathian B; Geriatrics and long term care Department, Rumailah Hospital, Hamad Medical Corporation, Doha, Qatar.
  • Banerjee I; Centre for Midwifery, Maternal and Perinatal Health, Bournemouth University, Bournemouth, England, United Kingdom.
  • Robinson J; Sir Seewoosagur Ramgoolam Medical College, Belle Rive, Mauritius.
Nepal J Epidemiol ; 10(4): 923-927, 2020 Dec.
Article em En | MEDLINE | ID: mdl-33495710
ABSTRACT
The Coronavirus disease 2019 (COVID-19) pandemic is caused by rapidly spreading pathogenic virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), that affects vast majority of population worldwide. Although, around 80% of the cases had mild infection but still remaining 20% had developed respiratory failure and dysfunction of other organs that necessitate urgent oxygen therapy or specific interventions. Therefore, it is imperative to establish novel prognostic approaches to screen patients at high-risk of developing severe complications. The primary focus of current research for COVID-19 is to discover safe and efficacious vaccine for prevention and effective treatment for better management of the patients to overcome the pandemic. To achieve this goal, it is imperative to have better understanding of the molecular pathways involved in the pathophysiology and progression of severe COVID-19. The surge for reliable diagnostics and therapeutics targets for COVID-19 highlighted the great potential of high-throughput approach like metabolomics which may enable the development of personalized medicine.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article