Pharmacologic treatments for covid-19 patients

We are searching the literature every day and collecting data for each RCT of COVID-19 treatment identified.

Below you can access all the treatment comparisons where data are available as well as a table with the general characteristics of each trial. For each treatment comparison, you can access the forest plots for all the outcomes of interest available as well as the Summary of Findings (SoF) table (development in process).

We systematically stratified the results on the disease severity (mild/moderate vs moderate/severe/critical).

Each week we are updating the evidence synthesis.

Network diagrams

Mild/moderate patients

Moderate/severe patients

The nodes represent the interventions being compared in the available RCTs. Two interventions are connected with a line whenever there is at least one RCT comparing them directly. The size of the nodes is proportional to the total number of participants randomised in each intervention and the thickness of the line is proportional to the precision (i.e. the inverse of the variance) of the relative effect for the respective direct comparison. The color of the lines represents the overall risk of bias of the direct comparisons for the outcome that corresponds to each network diagram. When two or more RCTs compare the same pair of interventions, then the risk of bias of that comparison is calculated as the inverse variance weighted average of the study-specific overall risk of bias judgements.

The components included in the standard of care vary among the included studies. For example, the standard of care may include antiviral treatments in some studies, but not in others. We are in the process of contacting the study authors to obtain more information.

The overall risk of bias reported in the table corresponds to the highest risk of bias for the outcomes assessed for the systematic review.

We acknowledge that we may have been unable to extract some information from pre-prints, as they represent preliminary forms of scientific communication. We perform daily database searches to identify if an included pre-print has been published in a scientific journal, and we will use the published paper to update our extraction.

We recognize that our process might not be perfect. Please contact us if you identify an error.