What should be audited in the NIH RECOVER dataset
Three kinds of misclassifications
In my previous article I mentioned that vaccine injuries were often1 recorded as COVID19 infections.
I got confirmation of this from Gail Macrae on Twitter (I had cited her video interview with Steve Kirsch in my previous article).
Please read the thread carefully because it has many implications for an audit
This satisfies two of the three kinds of misclassifications I had discussed in my previous article.
someone who got admitted to the hospital after getting the vaccine was still classified as “unvaccinated”
a vaccine injury is recorded as a COVID19 infection even if it was incidental2
The third type of misclassification (which happened in the case of Cody) would probably just be outright fraud3 - someone who did not even test positive for COVID19 was labeled as “hospitalized due to COVID19”
This is Gail’s explanation for how this could have happened
What if the injury was actually a COVID19 complication?
This would be the obvious question on the minds of the vaccine pushers. In fact I would probably be asking the same question if I had not done a lot of vaccine safety data analysis before this.
But here is the thing - Gail was a nurse who treated COVID19 patients all through 2020 and had a fairly good idea of when something presents like a vaccine injury and when something is just a complication of COVID19 itself.
Also, the cohort studied in Prof Morris’s paper were all under 20 years of age, a cohort which rarely got COVID19 which was severe enough to hospitalize them. But it is now well known that they did get cardiac complications from taking the mRNA vaccines. And if a misclassification of a vaccine injury as a COVID19 complication is plausible, then the “cardiac cluster” numbers in the paper which were attributed to COVID19 could well be due to vaccine injuries.
In other words, we already have good reasons to do a rigorous audit of the NIH RECOVER Consortium dataset.
What should be audited?
The following types of misclassifications need to be audited:
were people who were actually vaccinated labeled as unvaccinated? If yes, how often did this happen?
were vaccine injuries recorded as COVID19 complications? If yes, how often did this happen?
was the patient outcome (such as hospitalization) labeled as being due to COVID19 even though the COVID19 tests themselves were negative? If yes, how often did this happen? While this seems pretty rare, it is still good to know how often this happened?
While there could also be other issues with the dataset, these directly impact the calculation of both safety and efficacy in many publications
Often, as a percentage of how frequently the injuries occured
After the vaccination rollout, there was an effort to portray COVID19 hospitalizations as “incidental” and so we found out that there was “no good measure that can reliably distinguish between cases where COVID-19 is the primary reason for hospitalization (non-incidental admission) and cases where COVID-19 is incidental to the hospitalization”. Cynics might point out that this kind of distinction was rarely used until it was necessary to defend vaccine efficacy.
“Despite the importance of hospitalizations as a measure of the public health burden of COVID-19, there is no good measure that can reliably distinguish between cases where COVID-19 is the primary reason for hospitalization (non-incidental admission) and cases where COVID-19 is incidental to the hospitalization. As we discuss below, the two principal measures in current use undercount non-incidental hospitalizations, especially during the Omicron period that began in December 2021.“
And till now I haven’t seen an explanation from the vaccine pushers how this could have even happened. So let us just table this particular misclassification as “possible but not widespread” unless someone comes forward with more information