[drtournier]

I am an MD, Data Scientist and epidemiologist. There are three pieces of information which makes me feel something fishy about the study: 1. Sample sizes for all selected studies are very small, and even though they used mixed effects models to treat confounding, there is no way to check what the authors did, since they didn’t shared the code or the data, which is inadmissible since this is a meta analysis and there is no private data involved 2. Any tree chart of Risk Ratios or Odds Ratios that show drastic positive effects must raise one’s eyebrow about partiality in the authors 3. Real world data from Brazil, where they have great death data surveillance AND mass-distribution of ivermectin didn’t show any excitement. Brazil just crossed more than half million deaths as of Jun 19th 2021, and there is a high likelihood of surpass U.S. in deaths.

Based on what we already know about vaccine and PFF2/N95 mask efficacy and safety, it becomes hard to defend approaches such as ivermectin, instead of promoting practices and technologies that showed undeniable success in the real world, instead of doubtful medicines supported by obscure statistics and ideological discourse.

[vfclists]

> instead of promoting practices and technologies that showed undeniable success in the real world

What are the practices and technologies that showed undeniable success in the real world.

What is the "real world"?

Does anyone have to take your scientific credentials seriously when you make a "scientific" argument using the term "the real world"?

Is there some "alternate unreal world" where these trials were carried out?

[drtournier]

Thanks for the relevant comment - it must be intriguing for anyone who is not used with hearing about the “real world evidence” term in medical sciences.

Usually the highest level of evidence is attributed to randomized controlled trial studies. As the name says, they are performed in a high level of control, to evaluate in a more “insulated” way, the effects of a drug/intervention in a given outcome (reduce death, cure a disease, etc). Unfortunately, we can’t always relate these academic studies with the “real world”, due to an almost infinite number of confounding variables, or in the worst case scenario, if a scientist is manipulating the experiment environment (e.g. selecting a patient population with more likelihood for the desired effect).

This is one of the reasons why you will see with increasing frequency the terms “Real World Evidence (RWE) study” in reputable journals, such as the New England Journal of Medicine, or The Lancet.

These studies occur taking data from epidemiological surveillance, or patient medical records, and usually do a “reality check” on data found in these trials.

A lot of these RWE studies are famous to find problems that trials missed. Here is a classic example https://thalidomide.ca/en/what-is-thalidomide/