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.@kevinault my DMs are open so just drop in there if you want to ask me questions.
Better than loitering around a private facebook group run by Pharma for you to push their untested drugs onto pregnant women.
Did ACIP know you were doing this?
And who TF is "Jiffyleaks"?
Better than loitering around a private facebook group run by Pharma for you to push their untested drugs onto pregnant women.
Did ACIP know you were doing this?
And who TF is "Jiffyleaks"?
@kevinault Well it's going to be difficult to drop into my DMs if you blocked me. Oh well, you made your choice.
You'll have to go back to that dodgy Pharma-sponsored private facebook group and ask your buddies there.
You'll have to go back to that dodgy Pharma-sponsored private facebook group and ask your buddies there.
Was it something I said?
It was, wasn't it?
If you want to see the interactions between Kevin Ault and me follow the #ACIPKevin hashtag
It was, wasn't it?
If you want to see the interactions between Kevin Ault and me follow the #ACIPKevin hashtag
MORE STINKY CHEESE 🧀🧀🧀
#thalidomideViki quotes the discredited @thelancet again, because it suits her agenda.
This study should be completely disregarded as real because data sharing is declined - again.
Every study Viki posts is not verifiable.
But there's more...
#thalidomideViki quotes the discredited @thelancet again, because it suits her agenda.
This study should be completely disregarded as real because data sharing is declined - again.
Every study Viki posts is not verifiable.
But there's more...
Immediate red flags are differences in the groups, such as the higher prevalence of smoking in the "COVID" group which hasn't been seen in real world studies. And the smoker group had the exact same educational history - you don't usually see that.
Always worth looking at the supplementary to look for inconsistencies in published data.
These figures on a test negative design show that the "effectiveness" was only 9%. Bearing in mind miscategorisation bias, this means there was negative efficacy against infection.
These figures on a test negative design show that the "effectiveness" was only 9%. Bearing in mind miscategorisation bias, this means there was negative efficacy against infection.
