The juxtaposition of "meta analysis" and "real-time" is problematic. The point of a meta analysis isn't merely to rapidly aggregate lots of data from multiple

The juxtaposition of "meta analysis" and "real-time" is problematic. The point of a meta analysis isn't merely to rapidly aggregate lots of data from multiple studies. It's also an analysis of the quality and applicability of the studies. The consensus of most (all?) regulatory bodies is that the clinical effectiveness of off-label Ivermectin for CoViD-19 has not been well established. A useful survey of many of the relevant studies can be found at https://www.covid19treatmentguidelines.nih.gov/tables/table-2c/ https://www.covid19treatmentguidelines.nih.gov/tables/table-.... "Real time" is not particularly compatible with things like peer-review and replication, and that's a big problem. They also seem to be aggregating a large amount of unpublished data that was not part of a relevant study. That needs to be accompanied with a detailed discussion about why the data (and population) in question provides good evidence. That's also not meta-analysis but original research, requiring independant review and assessment before it could be part of a meta study. An attempt to rapidly correlate the results of all available studies runs the risk of simply representing an automated version of p-hacking. Aggregating a bunch of low quality studies does not generate a good quality study, especially if (as in this case) many of them generate concerns about the study population selection, lack of controls, and comorbidities.