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Sep 13, 2021 19 tweets 6 min read Read on X
This preprint looking at the risk of vaccine-related side-effects vs COVID-19 infections for children has received a lot of attention, and people have been asking my opinions on it. So, a few thoughts 1/n
2/n The preprint itself is pretty simple - comparing the calculated risk per million vaccines of having a VAERS report consistent with myo/pericarditis (CAE) with the number of COVID hospitalizations per 100,000 children aged 12-17
3/n The authors found that the rate of VAERS reports consistent with myocarditis was higher than the average rate of COVID hospitalizations per 100,000 children in a population where there was a reasonably high current prevalence of COVID-19
4/n To think about this, it's important to note what VAERS is - it is a passive reporting system (the acronym stands for Vaccine Adverse Event Reporting System) that anyone can enter in a report to cdc.gov/vaccinesafety/…
5/n Because this system is designed to be sensitive and pick up even quite rare harms, there are some caveats, most notably that (as the CDC points out) you cannot determine whether a vaccine caused a specific issue from VAERS alone
6/n So I'm a bit confused by the terminology here. As far as I can see, the authors have relied entirely on VAERS to determine case figures, which the sources they reference point out cannot be considered a causal link
7/n In other words, it's not the likelihood of experiencing a post-vaccination CAE, but the likelihood of having a post-vaccination REPORT of a CAE per million children
8/n This may sound like needless pedantry, but it isn't - media reporting and attention are a known confounder of passive reporting systems like VAERS. If you have a lot of news articles, you get more reports, even if those are not actually linked to the vaccines
9/n And it's interesting to note that, as the authors point out, the CDC (who use much more detailed information to calculate these rates) have a lower estimate of post-vaccine CAE than this preprint
10/n The second point that confuses me about the paper as it currently stands is comparing two numbers with very different denominators:

1. events per 1mil vaccines
2. events per 1mil children per 120 days
11/n One way to think about this disparity is to simply equalize the denominators. We could do this by calculating the 120-day risk of CAE following vaccination for males aged 16-17 in the United States
12/n Based on the numbers in table 1, that would be 110 total events (doses 1+2), and a population of about 3 million, so very crudely 37 CAEs per 120 days

This is lower than most of the calculated rates of COVID-19 related admissions in the paper
13/n Alternatively, we could compare the risk having a CAE after vaccination with the risk of hospitalization for kids per INFECTION

Fortunately, there's already a great resource for doing this in a recent preprint medrxiv.org/content/10.110…
14/n From this preprint, the likelihood that a child aged 16-17 will experience an infection severe enough to warrant hospitalization is about 1 in 500, and the risk of needing ICU is about 1 in 4,000
15/n So might reasonably compare the risk of 94-168 CAEs per million vaccinations posited by this paper with the risk of 2,400 hospitalizations expected per million infections with COVID-19
16/n Now, it is worth noting that this assumes that the risk of eventually contracting COVID-19 is 100% for children who are not vaccinated, however as time moves on that is not, I think, entirely unreasonable
17/n I think weighing the competing risks of vaccination vs infection is a very challenging thing to do, so I commend the authors on the preprint. I think these might be things to consider when updating it for future versions
18/n That being said, I'm not sure I agree that this preprint shows vaccination to be riskier than immunization for these age groups/genders. Not an easy question to answer!
19/n This piece from @dfreedman7 is a fairly startling addition to the discussion. The implication appears to be that even the basic case definition the authors used was entirely useless, which is less than ideal

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More from @GidMK

Mar 4
The final large published trial on ivermectin for COVID-19, PRINCIPLE, is now out. Main findings:

1. Clinically unimportant (~1-2day reduction) in time to resolution of symptoms.
2. No benefit for hospitalization/death. Image
Now, you may be asking "why does anyone care at all any more about ivermectin for COVID?" to which I would respond "yes"

We already knew pretty much everything this study shows. That being said, always good to have more data!
The study is here:

For me, the main finding is pretty simple - ivermectin didn't impact the likelihood of people going to hospital or dying from COVID-19. This has now been shown in every high-quality study out there.pubmed.ncbi.nlm.nih.gov/38431155/
Read 8 tweets
Feb 20
Fascinating study.

What's particularly interesting is a finding that the authors don't really discuss in their conclusion. These results appear to show that gender affirming care is associated with a reduction in suicide risk 1/n
2/n The paper is a retrospective cohort study that compares young adults and some teens who were referred for gender related services in Finland with a cohort that was matched using age and sex. The median age in the study was 19, so the majority of the population are adults. Image
3/n The study is very limited. The authors had access to the Finnish registries which include a wide range of data, but chose to only correct their cohorts for age, sex, and number of psychiatric appointments prior to their inclusion in the cohort.
Read 11 tweets
Oct 26, 2023
These headlines have to be some of the most ridiculous I've seen in a while

The study tested 18 different PFAS in a tiny sample of 176 people. Of those, one had a barely significant association with thyroid cancer

This is genuinely just not news at all Image
Here's the study. I'm somewhat surprised it even got published if I'm honest. A tiny case-control study, they looked at 88 people with thyroid cancer and 88 controls thelancet.com/journals/ebiom…
Here are the main results. There was a single measured PFAS which had a 'significant' association with the cancer, the others just look a bit like noise to me Image
Read 7 tweets
Oct 11, 2023
A new study has gone viral for purportedly showing that running therapy had similar efficacy to medication for depression

Which is weird, because a) it's not a very good study and b) seems not to show that at all 1/n
Image
Image
2/n The study is here. The authors describe it as a "partially randomized patient preference design", which is a wildly misleading term. In practice, this is simply a cohort study, where ~90% of the patients self-selected into their preferred treatment sciencedirect.com/science/articl…
3/n This is a big problem, because it means that there are likely confounding factors between the two groups (i.e. who is likely to choose running therapy over meds?). Instead of a useful, randomized trial, this is a very small (n=141) non-randomized paper
Read 15 tweets
Oct 6, 2023
This is SO MISLEADING

The study showed that COVID-19 had, if anything, very few long-term issues for children! As a new father, I find this data very reassuring regarding #LongCovid in kids 1/n Image
2/n The study is here, it's a retrospective cohort comparing children aged 0-14 who had COVID-19 to a matched control using a database of primary care visits in Italy
onlinelibrary.wiley.com/doi/10.1111/ap…
3/ The authors found that there was an increased risk of a range of diagnoses for the kids with COVID-19 after their acute disease, including things like runny noses, anxiety/depression, diarrhoea, etc Image
Read 13 tweets
Sep 20, 2023
This study has recently gone viral, with people saying that it shows that nearly 20% of highly vaccinated people get Long COVID

I don't think it's reasonable to draw these conclusions based on this research. Let's talk about bias 1/n Image
2/n The study is here. It is a survey of people who tested positive to COVID-19 in Western Australia from July-Aug 2022 medrxiv.org/content/10.110…
3/n This immediately gives us our first source of bias

We KNOW that most cases of COVID-19 were missed at this point in the pandemic, so we're only getting the sample of those people who were sick enough to go and get tested
Read 12 tweets

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