[croon]

70/100k is baseline. 5/100k is vaccination. 200/100k is unvaccinated with covid.

With vaccination you're at 75/100k.

Without vaccination at 0% chance of covid you're at 70/100k.

Without vaccination at 5% chance you're at 77/100k (worse than 75 here), at 10% 83, etc, etc.

> We're supposed to be doing science, right? Seems to me your premise is the one that's unrealistic. Mine is firmly grounded in evidence that we DO have. Not guesses and doomsday religion.

There are plenty of studies linked in this thread, that you're simply ignoring.

[trimethylpurine]

See section 2.4. The "unvaccinated" group includes people with a history of myocarditis and pericarditis who had an episode during the study, and coupled with the fact that cases "without an episode" were excluded, we should expect that the numbers are very much inflated.

There indeed are plenty of studies linked. I'm not ignoring them, I'm using them to point out that they don't carry the implications necessary to recommend vaccination for everyone.

To make the claim that the vaccine LOWERED incidence of myocarditis even for those without covid, counter to so much other research (e.g. [0]), we would like to see that the study excludes people with a history of myocarditis.

Including them is cheating, quite simply.

Regardless, even if we did go with this Spanish study, you still can't say that a 5% chance of infection is worse. You can say that a 5% of symptomatic infection is worse. There isn't any study in the thread that includes asymptomatic infection, which we know is MOST infection.

So at least so far, I don't see that you have the math to back what appears to be an unscientific claim.

And when faced with the counter research below [0], defining the mechanism of action, we should assume that the risks are a valid concern. You can't just sweep them under the rug.

Most people who tested positive had no symptoms. Most people who didn't get tested also had no symptoms but were likely infected. All of those people shouldn't take on additional risk in their own self interest. At best you can claim that they should take on the risk to try to achieve herd immunity so as to protect others. And actually I'm not sure that we have the data to determine that either.

[0] https://med.stanford.edu/news/all-news/2025/12/myocarditis-v...

[croon]

In retrospective cohort studies, researchers track newly occurring incidents during the study window.

If someone has a history, but suffers a new episode from covid, that is a medical event that should be counted.

> Regardless, even if we did go with this Spanish study, you still can't say that a 5% chance of infection is worse. You can say that a 5% of symptomatic infection is worse.

Yes you can. The mechanism for the side effect (as per your own source) is the same in both symptomatic and asymptomatic cases. Recipients of the vaccine do not get respiratory symptoms, and yet can contract the (very rare) side effects.

And as for your source, the author, Dr. Joseph Wu:

> “But COVID’s worse,” he added. A case of COVID-19 is about 10 times as likely to induce myocarditis as an mRNA-based COVID-19 vaccination, Wu said. That’s in addition to all the other trouble it causes.

[trimethylpurine]

You're not addressing the issue. 5% of what?

5% of symptomatic COVID cases. So now you have to compare that to only people with injuries from the vaccine.

Otherwise you're comparing apples to oranges.

If you want to compare people who got the vaccine to people who didn't, then you need to include ALL people who didn't. Not just the ones who were symptomatic.

And no, you can't include those people who had previous symptoms in the "everyone" group. Obviously those people are way more likely to return for treatment than the average Joe. They are skewing the sample because they are immediately nearly 100% likely to return for treatment. That is not representative of a random sample of people in the general population.

The question was about the general population, and they didn't sample the general population. They sampled people who come to the hospital. That is, only people with symptoms of some sort or another that are bad enough to warrant a journey to get treatment.

So all you can conclude is that people who come to the hospital have a higher frequency of heart conditions. And even that claim is not firmly established by the data, it's just a sensible inference. We expect that people who need treatment are more likely to seek treatment than those that don't need it. But there are countless counter examples there too. Hypochondria, etc.

No doubt if we had the data we'd find more problems there.

Wu's statement is fine, because again, it's not ALL people with COVID. His statement holds for people seeking treatment with COVID which is what they sampled.

Wu has no clue how many people have COVID asymptomatically and how to separate them from people without COVID altogether, and makes no claim about that.

You're simply making a claim that isn't in the research. Vaccination for people without COVID or with asymptomatic COVID is not researched or compared here.

This research, if you want to use it for a comparison, is for vaccination of people already coming to a hospital with symptoms of some kind.

EDIT: forgot to mention this was during a pandemic, so you might see significantly lower numbers for heart conditions if the study was repeated today. And it might be the case that during the pandemic it would have been a good idea to vaccinate everyone coming to a hospital from a statistical standpoint. But an even better take would be to identify what was common amongst the group with bad outcomes and vaccinate them, more specifically.

Regardless, nothing here implies better outcomes for everyone. It's not claimed by and it's not inferable from the research. And certainly not when there is a bunch of research showing contrary results to this study an example of which I linked earlier.

[croon]

No? It's population cohort study, not a hospital clinical sample. You're simply wrong in your assertions.

You can absolutely track asymptomatic infections through seroprevalence studies which we have been doing since 2020.

> forgot to mention this was during a pandemic, so you might see significantly lower numbers for heart conditions if the study was repeated today.

Yeah, that's making the point for me.

[trimethylpurine]

>Yeah, that's making the point for me.

Yeah, I'll help you make your point when it's accurate. That's called science.

Just fix the problems in your argument and I'll help you make it.

[trimethylpurine]

Respectfully, I think you've mistaken the definition of the word cohort . A cohort specifically does not include everyone. Please check the definition of cohort and then read section 2.4.

They tested people treated at a small collection of hospitals (the cohort).

And, you have made several other mistakes aside from that.

The 2020 studies are all retracted. They were over-spinning the centrifuges, I think by a factor of 10 or 100 maybe? They got insanely high positive numbers and the guidance was all updated to correct for that. You can ask an LLM to help you find the CDC publications on that. Don't use those numbers.

Additionally, even if your interpretation was accurate, it would fly in the face of thousands of other studies, just like the one I posted earlier in the thread.

Make sure your beliefs are based on peer reviewed research, that is not retracted, has been established long enough to withstand challenges from the scientific community, and that you're interpreting it honestly, using the established academic criteria for the scientific method and publication standards. Be careful to check the definition words that you're not familiar with, and even ones that you think you're familiar with. They might have a different meaning when used in a scientific context.

Out of curiosity, are you a journalist, college educated? I'm trying to understand where science has failed here. I would like our institutions to produce adults that can identify sound research and draw logical conclusions. There are some basic methods for doing that. I don't mean any offense by that. I'm just trying to understand what's broken. And more to the point, whether or not you are actually interested in science or you're just trying to prove that the media knows more than the scientists. Or maybe you just can't believe that journalists lie about what scientists say.

Is the media in the business of selling truth for profit, even if it means they won't profit? Do you believe that enough to take drugs that legally restrict you from taking legal action against the manufacturer when you're injured? (See CARES act)

Is your motivation to continue discussion political? Or scientific? If it's scientific, let's stick to the facts and follow the science. Don't try to make the science say what you want. You'll find that doesn't work in the broader forum.

[croon]

> Respectfully, I think you've mistaken the definition of the word cohort . A cohort specifically does not include everyone. Please check the definition of cohort and then read section 2.4.

> They tested people treated at a small collection of hospitals (the cohort).

In epidemiology, a cohort is simply a defined group of people followed over time. In a population-based cohort study (which this is), the cohort is the entire population of the health district (over 500,000 people).

The study did not just evaluate people treated at the hospital. It used the hospitals EHR to identify the numerator (the heart inflammation cases) out of the denominator (the entire regional population).

> The 2020 studies are all retracted. They were over-spinning the centrifuges, I think by a factor of 10 or 100 maybe? They got insanely high positive numbers and the guidance was all updated to correct for that. You can ask an LLM to help you find the CDC publications on that. Don't use those numbers.

You are confusing PCR testing with serology. The "over-spinning" you are referencing relates to PCR cycle thresholds (Ct values), which are used to detect active viral RNA swabs. Seroprevalence studies—which track historic asymptomatic spread—do not look for active RNA. They test blood serum for antibodies using immunoassays (like ELISA). They do not use PCR amplification, and they are absolutely not "all retracted." They are the standard of how we track the infection rate of a population.

> Is your motivation to continue discussion political? Or scientific? If it's scientific, let's stick to the facts and follow the science. Don't try to make the science say what you want.

This is... literally what I've been doing the entire time.