None of the study results were robust, but many of the study outcomes were positive. So they were counting up positive outcomes and saying that more often than not, it was evidence that Ivermectin was effective.
This is a good means of generating a hypothesis, but a bad means of generating a conclusion.
Most of these studies were not in any way controlled or comparable in their conditions, and some had a very low number of observations. It didn't seem plausible that the data could be aggregated together.
It will be very interesting to see the results of the larger RCTs underway. Regardless of the outcome there _has_ to be a lesson for at least some people who arrived at fervent conclusions about what a miracle/scam this particular drug is. Unfortunately it seems unlikely that it will be a lesson that endures.
I don't think we can trust "doctors" anymore.
There were a bunch of doctors (aka America's Frontline Doctors) that were trying to go around and say Ivermectin works. Same with HCQ. The "needle rape" doctor in Idaho said the vaccine is dangerous, but Ivermectin saves lives.
In Idaho, I assure you, doctor's are prescribing patients Ivermectin in the ICU. If it really did work Boise would be the groundswell of Ivermectin miracles, where people are walking out of the ICU, ending the crisis.
Unfortunately, that's not happening. ICU's are primarily being freed up from death now it seems like. ICU's are in the high 90's capacity.
https://idahocapitalsun.com/2021/09/22/today-in-idaho-hospit...
https://www.hhs.gov/hipaa/for-professionals/privacy/special-...
Double-blind is important for a reason, researchers are exceedingly good at proving what they want to prove even if subconscious, can meta-analysis studies ever overcome this?
Often it is impractical to perform large studies. Partially by logistics and often by funding. But if there are lots of smaller studies you can aggregate the data to check for overall significant results. But mainly they are helpful to give a "survey" of the current research instead of having to link to 10 different studies and hope someone else sorts out what the data says.
But as you point out, there are two major flaws in the assumptions. First, that the scientific procedure is sound. Secondly, that the data is handled properly, and thus you can take the summary and back out the underlying data.
Unfortunately trying to fix the first is really, really hard.
The second is somewhat mitigatable. As the Nature article suggests, you could publish the underlying data (anonymized of course). This would help in two ways. First, the meta-analysis could check for confounding variables to control across all of the data. The second major one is it would help people spot fraudulent data.
However, as anyone who handles datasets knows, publishing and wrangling data into a useable state from multiple sources is a serious pain in the neck. Plus a lot of concerns about how de-anonymized the data would be. As we've known, with enough metadata it can be used to identify individuals. And publicly publishing dais data would definitely allow for some serious sleuthing work to be done.