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:: Volume 9, Issue 3 (10-2020) ::
Int J Med Invest 2020, 9(3): 1-4 Back to browse issues page
An early Bayesian Network Meta-analysis of Coronavirus Diseases 2019 (COVID-19) clinical trials
Farshid Javdani *, Mohammad Hashem Abdi, Samaneh Abiri, Marzieh Haghbeen, Ahmad Rastgarian, Mohammad Hasan Damshenas, Pouyan Keshavarz, Mohammad Amin Akbarnejad, Naser Hatami, Sayyed Reza Ahmadi, Seyed Reza Habibzadeh, Neema John Mehramiz, Mahdi Foroughian, Navid Kalani
Student Research Committee, Jahrom University of Medical Sciences, Jahrom, Iran.
Abstract:   (1765 Views)
In this paper, we conducted a Bayesian Network Meta-analysis of the latest COVID-19 clinical trials including 5 studies on 591 patients receiving 4 different agents of Arbidol, Favipiravir, lopinavir- ritonavir, and Hydroxychloroquine and standard treatment protocol. We ranked the best agent based on patient improvement using Markov-Monte-Carlo-Chain. Hydroxychloroquine showed the best efficiency following the Favipiravir, Arbidol, lopinavir-ritonavir, and standard regimen in the first week of treatment. In the second week, with excluding Hydroxychloroquine arm (as some reporting studies hadn't addressed its efficacy in the second week), Favipiravir was the best treatment following by lopinavir-ritonavir, standard care, and Arbidol. As we saw a huge change in the ranking of the drugs by evaluating outcomes in the second week of treatment, we think that COVID-19 randomized clinical trials should be performed based on a standard study protocol worldwide, that could help  policy makers to make a decision on the treatment protocol.
Keywords: Network Meta-analysis, Favipiravir, SARS-CoV-2, COVID-19, lopinavir-ritonavir.
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Type of Study: Research | Subject: General
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Javdani F, Abdi M H, Abiri S, Haghbeen M, Rastgarian A, Damshenas M H, et al . An early Bayesian Network Meta-analysis of Coronavirus Diseases 2019 (COVID-19) clinical trials. Int J Med Invest. 2020; 9 (3) :1-4
URL: http://intjmi.com/article-1-517-en.html

Volume 9, Issue 3 (10-2020) Back to browse issues page
International Journal of Medical Investigation
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