The authors used a huge database of people who'd been treated for COVID-19, and looked at the associations between mortality and 84 drugs or drug classes
They found that metformin, nicotine, fluticasone, SNRI, expectorants and ondasetron reduced the risk of death from COVID-19, but given the potential for residual confounding only focused on ondasetron
The main conclusion is that we should probably try ondasetron as a treatment for COVID-19 in RCTs, which I think is justifiable based on the study
But I think the really interesting part is the initial analysis. It looks like if you test 84 medications for benefit in COVID-19 mortality, 6 positive results will be found
Thing is, we've been using studies a LOT worse than this one to drive treatments for the whole pandemic. The initial use of ivermectin, HCQ etc in 2020 was based on much less robust evidence than this research
Why is this interesting?
I think it shows just how important RCTs of interventions for COVID-19 are
If you test a bunch of drugs, you'll see some positives
If 1,000 people run studies on their databases, and you only really see the positive results published, you'll get the false impression that these drugs work against coronavirus even when the evidence is not good at all
This is in no way a critique of this specific paper, whose authors appear to have done a fantastic job, but it is a pretty worrying note for the rest of us
Anyway, ondansetron is a cheap, low-side-effect drug available pretty much everywhere in the world, so if it works for COVID-19 it'd be a brilliant addition to the arsenal
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A fairly well-demonstrated fact about COVID-19 and lockdowns is that the more severe restrictions tend to have smaller marginal benefits once enacted
In practice, this means that the reduction in transmission for, say, limiting travel to 5km radius is probably quite small once you've already implemented other interventions such as stay-at-home orders
In other words, when we talk about 'hard' vs other lockdowns, the language often doesn't match the evidence. There's no strong reason to believe that adding small extra limits on behavior will have a large impact on the spread of COVID-19
This is a fascinating paper by @EpiEllie and team. The available high-quality evidence shows "no evidence to support the conclusion of the existence of a biological relationship" between blood type and COVID-19 risk medrxiv.org/content/10.110…
For those who remember, the headlines claiming that there was a relationship were numerous and, it appears, incredibly misleading
Just goes to show how easily bad science can cause serious, long-term beliefs and research investment, and it takes months of effort to even make a dent in terms of correction
So, @Covid19Critical does not agree with me, and says that the conclusions of meta-analyses do not change at all once excluding the retracted ivermectin study
Let's go over exactly why I said that removing the study makes a huge difference 1/n
2/n I went over this in my article, which you can find here, but I'll repeat the precise analysis I've done on twitter, because I think it's a fair question
To be clear - I'm not perfect, and not everything I say is right!
3/n Judge for yourself whether it is fair to argue that removing Elgazzar largely eliminates the benefit for mortality here, the headline finding and the primary analysis of the paper
This is not unexpected. If the authors of the retracted ivermectin study claim that the data was not really the data for their paper, they now need to explain:
1. Why did they upload fake data that quite clearly matched their results?
3. The implausible/impossible values remaining in the text
4. The incorrect and bizarre statistical tests
5. Why it is only NOW that we're told the data us fake. Was it a joke? A prank???
5. (cont.) Seriously, how do the authors explain the fact that they uploaded a dataset, said it was the data of their study, and now claim it wasn't? How do we reconcile that with what they claim now?
So, one of the biggest studies to date on ivermectin for COVID-19 has issues significant enough that, if not fraud, are so serious that it invalidates the study without further explanation
2/n Firstly, none of this would've been possible without @JackMLawrence, who uncovered this in the first place and investigated it himself well before any of us gronks got on board
3/n The basic story is pretty astonishing. I've previously written about this study, Elgazzar et al, and why there are some indications that it's low-quality and potentially very unreliable