2/n The paper is here. The authors and ethics approval are essentially identical, and the text is very similar. There are, however, some really odd differences between the publication and preprint academic.oup.com/jcem/advance-a…
3/n First off, the published version doesn't mention that this study was preprinted then retracted as far as I can tell
That's, um, not great. Less than ideal
4/n Secondly, the study type has changed. The preprint claimed to be "randomized", the published study identifies itself as an observational trial
5/n This is a pretty big issue, because being a randomized trial was what made this study go viral in the first place
As an observational paper, it's really not very strong
6/n In essence, people who were assigned to different wards in a hospital were either given or not given calcifediol based on which ward they were sent to. People sent to the calcifediol wards had a lower chance of going to ICU
7/n The authors controlled for some comorbidities and a few other things in their analysis, but at a basic level there are many potential confounding factors in this sort of trial design that make it hard to draw conclusions from the results
8/n So as an observational trial, it was fine but not particularly conclusive
But then you start looking at the numbers, and things get weird
9/n Firstly, the authors changed the sample between the preprint and publication. They report excluding 10% of their total sample because they'd received treatment before the study, which was not true in the preprint
10/n Now, it's a bit weird to exclude people who've taken vitamin D supplements 3 months ago from this sample anyway - most of the people were deficient in vitamin D despite the supplements - but there's also more that's strange here
11/n For one thing, even though people have been EXCLUDED from the trial, the control group has...increased?
379 in the preprint, 391 in the publication
12/n This is not explained - the only thing mentioned is that 92 people were excluded ~prior to the trial~
Were people moved from treatment to control? How does that happen in a prospective cohort study?
13/n Table 1 also has some mistakes. For example, the obesity numbers and percentages have been copied in wrong
14/n The figures in Table 1 are also just a bit...odd? 20% diabetes, 30% dyslipidemia, but only 9% of people with BMI>30? Are those obesity values just an error perhaps?
15/n There are also tons of strange small differences between the preprint and the published study. 80/379 died in the control group in the preprint, but 82/391 died in the publication
None of this is explained 🤔
16/n At this point I just honestly don't know what to make of the research. As an observational study, it's not very meaningful (if nothing else, there's no control for or discussion of how patients were allocated to the wards)
17/n As a randomized study that was retracted from SSRN after being rejected from the Lancet, it is pretty problematic that the preprint isn't mentioned at all in the published work, and that the differences aren't really explained
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Fascinating thread. It's wrong in numerous ways - the methodology is pretty trivially incorrect, many of the statements are wrong based even on a quick google
But it's face-plausible so people jump on board. Very interesting
Taking one basic error in the thread as an example, the tables only work if you assume that the proportions in each age group are identical across these countries, which is very trivially wrong
Another basic mistake - the US had patchy lockdowns that weren't all in place for most of the year, so it's boringly incorrect to compare to Sweden in this way
The simple fact is that our current system for generating and correcting evidence has not handled the incredibly tight timeframes of Covid in any reasonable way
I think this story about a paper in Scientific Reports exemplifies the issue
The authors and editors did everything RIGHT as far as traditional academia goes. And yet, it was a massive failure in many ways
Study: cross-sectional survey-based investigation of an online sample of healthcare workers shows some interesting associations
The headlines are wildly silly 1/n
2/n The study is here, and fun for a quick read. Basically, a group of researchers surveyed healthcare workers in July-Sept 2020 and asked them stuff about their diet and COVID nutrition.bmj.com/content/early/…
3/n This appears to be the 3rd or 4th study published from that survey. The authors basically found that, after controlling for a couple of confounders, there was an association between self-reported diet and risk of severe COVID-19
If you want to consider the travesty of medical advice vs evidence during COVID-19, vitamin D is an amazing example
100s of millions of people have self-medicated/been treated with vit D for COVID. The evidence base is trash
A living Cochrane systematic review last updated May 2021 gives you an idea of this - as of 14 months into the global pandemic, there are 3 published RCTs on vitamin D
And look, it's never been tremendously likely that vitamin D was the key ingredient to banishing COVID-19, but it is wild that so many people have taken it for the disease and we still don't even know if there are harms to that or not
People on Tiktok are drinking lettuce water because of a rumour it helps you sleep
This is all apparently based on a 2013 study that looked at lettuce leaf/seed extracts IN MICE @justsaysinmice
Now, I should say that the original rumour that started on Tiktok may not be entirely due to this study. The Pedestrian article says that this is the research backing up the claim, but there's no evidence that's true
Nevertheless, this study is BRILLIANT:
- extracted substances from lettuce leaf/seeds
- gave extract to mice
- sedated mice
- measured sleep times (slight difference)