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Johnson & Johnson vaccine linked to rare cases of autoimmune disorder:
The Food and Drug Administration announced a change to the fact sheet on Johnson & Johnson's COVID-19 vaccine Monday, warning of an increased risk of Guillain-Barré syndrome, a neurological disorder that damages the nerves and can lead to paralysis.
"Based on an analysis of Vaccine Adverse Event Reporting (VAERS) data, there have been 100 preliminary reports following vaccination with the Janssen vaccine after approximately 12.5 million doses administered," an FDA spokesperson said in a statement to CNET. Ninety-five of the cases were serious and required hospitalization, with one reported death, according to the FDA.
The cases of Guillain-Barré usually occurred about two weeks after vaccination and were typically found in males aged 50 and older, according to a statement by the Centers for Disease Control and Prevention. The CDC said it will discuss the link between the US's only single-dose COVID vaccine and the autoimmune disorder at an upcoming meeting of the Advisory Committee on Immunization Practices. It also said that most people fully recover from Guillain-Barré syndrome.
The known benefits of Johnson & Johnson's COVID-19 vaccine continue to outweigh the known risks, the FDA said. But those who got a Johnson & Johnson shot should seek medical attention if they develop the following symptoms, per the FDA: weakness or tingling sensations, especially in the legs or arms, that's worsening and spreading to other parts of the body; difficulty walking; difficulty with facial movements, including speaking, chewing or swallowing; double vision or inability to move eyes; or difficulty with bladder control or bowel function.
[...] Guillain-Barré can occur after infections with viruses such as the flu, Epstein Barr or Zika, the CDC reports. Guillain-Barré also occurs after infection with Campylobacter bacteria, which is the most common bacterial cause of diarrhea. It has also been been associated with other vaccines, such as those for the flu and shingles, according to the FDA. Although most people fully recover from Guillain-Barré syndrome, it can lead to severe nerve damage and paralysis. It's also most common in men and people over age 50.
Also at CNN.
Wikipedia entry on Guillain-Barré.
(Score: 2) by Socrastotle on Tuesday July 13 2021, @05:17PM (2 children)
Your #1 example fits the exact hypothetical I was offering. If you have 25 "units" chance for an event from the virus, but only 4 "units" chance for an event from the vaccine, then it seems reasonable to say you're more likely to get it from the virus than the vaccine. But you need to factor in the chance of getting the virus. That is going to vary based upon your own personal behaviors, but the one datum we have is that about 10% of America has been diagnosed* with COVID.
So if we assume your personal behaviors are about average for America, then we'll say you have a 10% chance of infection. So your weighted chance (in "units") of the event happening from the virus becomes 25 * 0.1 = 2.5 while it remains 4 for the vaccine. In other words, an unvaccinated individual is less likely to suffer said effect than a vaccinated individual. And when we're speaking of vaccines, this should not be even close which brings us to your second point.
And as for your second point, sample size is critical. It was based on a sample of 1,597 individuals and has a confidence interval that goes all the way down to 0% (as well as up to extremely high levels). That is complete and utter noise. I am almost certain that this paper would never have been published if it was using similar evidence to suggest a problem with the vaccines.
(Score: 1, Informative) by Anonymous Coward on Wednesday July 14 2021, @12:35AM (1 child)
I love how you tacitly and conveniently pick the lowest number from the confidence interval to try to make your point. The ratio is more likely to be around 8-10, not 4. You need to take into account the range for the CI of the vaccine too... and yes, that creates a wider potential range of potential risk ratios, but don't be a jerk and silently manipulate the numbers to your favor.
If you actually use the more likely estimate for the ratio, your argument doesn't actually work. You'd need to play with your own made-up numerical scenario and "for instance" nonsense to make the numbers work out.
Wow. You just made an argument just literally made up out of BS numbers you pulled out of your ass about likely chances of getting the virus in the long-term, but now you're critiquing a published study with 1600 participants and 37 actual cases of COVID coupled with heart inflammation?
I think you misread the study. The only place 0% seems to be mentioned is here: "Thirty-seven (including 27 men) were diagnosed with COVID-19 myocarditis (overall 2.3%; range per program, 0%-7.6%)" -- that 0% indicates some sports programs at some schools had a rate as low as 0%. It's not a confidence interval. It's just the range seen in programs at different schools, which also had vastly different experiences with COVID, so we'd expect some variation.
The confidence interval is stated elsewhere: "The prevalence of myocarditis per program ranged from 0% to 7.6% (overall, 2.3% [95% CI, 1.6%-3.2%]; model-based estimate, 2.1% [95% CI 1.1%-4.4%])"
Thus, again, a level a few orders of magnitude greater than such a side effect from the vaccine.
Well, if you actually understand what the paper says (or are you deliberately misrepresenting the paper and lying to try to argue your point?), the confidence interval shows likely evidence that COVID cases have a risk several orders of magnitude higher than the vaccine. Or are you suggesting that all of these cases (37 cases of myocarditis out of ~1600) among athletes with COVID are seriously just a coincidence?? The prevalence is a LOT greater than observed in random young people of that age who don't have a serious illness.
(Score: 2) by Socrastotle on Wednesday July 14 2021, @02:02PM
The point remains exactly the same with 39. It was the result of skimming your post. If you haven't realized yet, the audience for posts once we start to getting into actual numbers instead of sensationalism, emotionalism, and drama in general - approaches zero. We are mostly just talking to one another.
And as for the study, no I was not suggesting coincidence - I was suggesting p-hacking. It's a rather specifically selective sample where the outlier data was likely known ahead of time, with inexplicable variation even in your sample groups, seemingly zero effort to have a control group (such as testing a sample of non-COVID athletes from each sample, and that further inflated its figures by carrying out atypical operations. The paper acknowledges medical assessment based on symptoms alone would have resulted in a detection of only 0.31%. It was only inflated by carrying out a slew of tests, including cardiac MRIs on completely asymptomatic individuals. And you're now comparing that figure against the population at large, when needless to say a figure very close to 0% have undergone any sort of testing for myocarditis, let alone completely asymptomatic individuals having cardiac MRIs.
Put another way, imagine you test only people with red hair using a sophisticated detection method to determine whether or not they have somethingitis. And, lo and behold, you find far more cases of somethingitis among your sample than among the general population. Is this now because redheads genuinely have a higher rate of somethingitis, or is it because the general population has not been tested using your sophisticated somethingitis detection methods? This is where a control group comes in.