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The COVID-19 pandemic has put a huge strain on governments and medical professionals all across the world. To identify acceptable treatments, many clinical studies from the Indian system of Traditional Medicines [Ayurveda, Yoga and Naturopathy, Unani, Siddha, and Homoeopathy (AYUSH)] have been conducted. Objective of the study is determine the efficiency of the Traditional System of Indian Medicine (AYUSH system) in lowering the incidence, duration, and severity of COVID-19 through a living systematic review and meta-analysis. We will search the following databases e.g; Pubmed; the Cochrane central register of controlled trials (CENTRAL); the Clinical Trials Registry - India (CTRI); Digital Helpline for Ayurveda Research Articles (DHARA): AYUSH research portal; WHO COVID-19 database etc. Clinical improvement, WHO ordinal scale, viral clearance, incidences of COVID-19 infection, and mortality will be considered as primary outcomes. Secondary outcomes will be use of O2 therapy or mechanical ventilator, admission to high dependency unit or emergency unit, duration of hospitalization, the time to symptom resolution, and adverse events. The review will be updated bi-monthly with two updates. It will provide practitioners, guideline developers, and authorities with up-to-date syntheses on interventions on a regular basis to help them make health-care decisions about AYUSH therapies for COVID-19 management. Study is supported by World Health Organization, South East Asia Regional Office, New Delhi, India. Here, we shared the result of our search strategy of our project and data extraction tool developed.
AYUSH, Systematic review and meta-analysis, COVID-19, Complementary therapies
AYUSH, Systematic review and meta-analysis, COVID-19, Complementary therapies
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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