Were vaccine injured classified as unvaccinated?
And why Jikkyleaks vs Jeffrey Morris makes a strong case for RFK Jr's nomination
Summary:
The UK ONS data revealed an unexplained spike in unvaccinated mortality coinciding with vaccine availability, suggesting deaths among recently vaccinated were misclassified
Analysis of the NIH RECOVER Consortium dataset shows misclassification of just 1,050 people (<5% of unvaccinated cohort) could impact study results
Former nurse Gail MacRae disclosed that EPIC Electronic Health Record systems defaulted to "Unknown" vaccination status, which was counted as unvaccinated in analyses
Pfizer FOIA document analysis shows the company pressured trial investigators to classify post-vaccination adverse events as COVID-19 symptoms rather than vaccine reactions
Some trial sites resisted this pressure, with documented exchanges showing investigators insisting on recording events as vaccine-related rather than COVID-19 symptoms
Hospital text notes could reveal misclassifications, but accessing and auditing this data requires high-level authorization that the HHS Secretary could provide
The default settings in hospital systems and pressure to minimize vaccine adverse events may have led to systematic underreporting of serious injuries to VAERS
All this supports RFK Jr.'s potential nomination as Health Secretary, as he would ensure needed data transparency and proper pharmacovigilance
A couple of days back
wrote an article on his Substack where he mentioned this about the UK ONS dataWe now have a reasonable hypothesis for why there was a big jump in mortality among the unvaccinated at the same time the vaccines became available. Deaths among the recently vaccinated were being misclassified as unvaccinated deaths. Furthermore, deaths among those who recently received their second dose were grouped with those who were greater than three weeks out from their first dose. This is why the mortality rates in people who were jabbed recently were so low and why the mortality rates who were weeks or months out from a dose were so high.
In this article I provide the basis for why this was not only plausible in the US, but in fact quite probable.
In my previous article I pointed out that Prof Jeffrey Morris avoided commenting1 on one of my tweets where I asked him why someone with a vaccine injury was recorded as “unvaccinated” in the hospital systems.
What if the rate of “infection” depends on other factors?
In the same article, I mentioned that Jeffrey Morris provided a reply to my question about auditing the NIH RECOVER Consortium dataset
His response is as follows
2. I already mentioned we only included sites with closely matching vaccination rates with cdc vaccination rates so we excluded sites that would have the epic problem you are worrying about
3. Your numerical arguments are wrong. First of all, the total infections are not comparable because there are wildly different denominators (much lower person weeks in unvaccinated) so even if your speculative reassignment of 44% were valid (and it is completely not) then it still would not “reverse” study results
4. Your math and assumptions are not valid:
a. You presume 44% of the unvaccinated are in fact vaccinated ignoring the fact in the paper that we restricted to sites with matching vaccination proportions to cdc (which 44% misclassifications rate would be impossible)
b. based on this assumption you reassign 44% of the cases of infection and long COVID to the vaccinated group (numerator of infection or long COVID rate) but you do not reassign the person weeks from the denominator of unvaccinated to vaccinated
c. Further you presume without any reasoning or justification that all misclassified unvaccinated got infected or long COVID. If there was a 44% misclassification rate in unvaccinated then why would you not also reassign unvaccinated person years for those not getting infected or long COVID to vaccinated?
d. As mentioned above this point may be moot since you are somehow thinking you can claim results of study are “reversed” just looking at counts and not even considering denominators which of course is silly
Bottom line is, even ignoring the fact that we restricted to sites with matching vaccine frequencies to corresponding CDC numbers, even if there were substantial misclassification it would have to be unbelievably extreme differences between the infection/long covid incidence in the undocumented vaccinated relative to the documented vaccinated subset for this to “reverse the study” or even meaningfully attenuate the results. You have not provided any evidence or even rationale for why you would expect such an extreme bias here, and if there is no such bias and the documented and undocumented vaccinated have similar results this would actually attenuate the results and make the reported results conservative. And of course your arithmetic argument that the proposed misclassification could “reverse the results” is not valid.
I ignored point 1 because I already answered it in my previous article
Matching CDC vaccination rates
It is pretty clear from reading Jeff Morris’ tweet that he believes that I think 44% of the entire unvaccinated cohort in the NIH RECOVER Consortium dataset was wrongly classified.
First of all, that’s not what I meant2 and it is very clear if you simply see the calculations which I have provided. In fact, the reason I repeatedly asked Jeff Morris for the same information is because I wanted him to explicitly write out the numbers.
He did not deny that my numbers (estimates) were wrong, which means he does agree with them.
By the way, all I did was paste a screenshot of those same numbers from my previous Substack article.
But a misclassification of 44% of the unvaccinated who were marked as "infected" is only about 1050 people (and doesn’t imply there was a 44% misclassification across the entire dataset). And I intentionally put infected in quotes, because I think many of these infections were actually vaccine injuries. The question is - how many?Prof Morris’s paper mentions that there were a total of 23779 people in the unvaccinated cohort.
So this is only 1050/23779 < 5% of the total number of vaccinated and will hardly make a difference even if you “only included sites with closely matching vaccination rates with cdc vaccination rates“
The different denominators (person weeks of analysis) do not apply
“Your numerical arguments are wrong. First of all, the total infections are not comparable because there are wildly different denominators (much lower person weeks in unvaccinated) so even if your speculative reassignment of 44% were valid (and it is completely not) then it still would not “reverse” study results“
So what Jeff Morris has done here is to come up with a work around for the possibility that there was X% of misclassification of actually vaccinated people as unvaccinated, and then to repeat the analysis3 based on the different numbers within the cohorts.
But this misses the point completely!
The rate of “infection” now depends on how often a vaccine injury was reported as a COVID19 infection, which is independent of the actual real rate of infection for either vaccinated or unvaccinated cohortsAt that point all the analysis by Jeff Morris to do additional calculations to “deal with the misclassification” becomes entirely pointless.
How often did vaccine injuries get reported as COVID19?
First of all, we need to be clear on one thing.
If everyone has to be on the same page, there has to at least be an acknowledgment that vaccine injuries did get reported in some EHRs as COVID19 infections.
And we already have proof of at least one such case.
But was it more common?
Systemic misclassification of vaccinated as unvaccinated
In a very interesting interview with Steve Kirsch a former4 nurse Gail MacRae pointed out that the EPIC EHR had the default status as “Unknown” - which would be counted as unvaccinated - and this meant that the actual number was not correctly reflected in statistical analysis.
I created an OutScript for the interview.
Here is the relevant excerpt:
Cause of Hospitalizations
Now this would have to be something that's novel because it's never happened in 33 years. This would probably be something that, like it could be in the food that people were eating, maybe in your area, but it was only, but these hospitalizations, I bet, were only happening to people who were vaccinated. Would that be a fair statement? Do you even know?
[Gail Macrae]
Vaccine Injuries
Yeah, so during that week when my manager approached me and told me about that increase in hospitalizations, it was very telling because I ended up working a double either the day before or the day after he had said those things to me. And I was filling a position for patient care coordinator. So I was filling in as a patient care coordinator. And in that role, you get report on every single patient on the whole unit.
[01:01:01]
So since I was working a double, I worked as a PCT on two different units. And so I got report on about 60 patients in that one 16 hour period of time. And I went home from work that day and I spilled to my family how I had just discovered that these were all vaccine injuries.
[Steve Kirsch]
All Patients Had Vaccine Injuries
So those 60- Wait a minute, wait a minute, whoa, whoa, whoa, whoa. You're telling me that all of the patients, this is, we're talking 60 patients is not a small number. You're saying that all the 60 patients that you were taking care of were vaccinated?
[Gail Macrae]
So I wasn't able to ask them their vaccination status for all of them. Many of them I did.
Guillain-Barré Syndrome
Two of them in particular were patients who had been diagnosed with Guillain-Barré. So in my career of 10 years as a nurse, I'd seen two patients total who had been diagnosed with Guillain-Barré. And within about three weeks of the rollout of these shots, I had seen four patients diagnosed with Guillain-Barré.
[01:02:03]
And of those four, I got the opportunity to ask two of them directly what they thought was the cause of the onset of their symptoms. And two of the four of them reported to me that they had received the COVID shots within 24 hours of the onset of their symptoms.
[Steve Kirsch]
Wow, that's a coincidence, isn't it?
[Gail Macrae]
Yeah, in 10 years, two, and then in two weeks, four.
[Steve Kirsch]
It was very- Yeah, and it was, did you say within 24 hours? The ones that you asked were within 24 hours. I'm glad we're tracking this. I'm sure the CDC's on top of this. Well, and now- That's insane, right? You know, they're anecdotes. If it was one, you could say, ah, coincidence. Two? Within 24 hours? That is a, that's a train wreck. Let me tell you.
[Gail Macrae]
Reporting to VAERS
Both of those patients who reported that to me, so I then proceeded to suggest to them, have you told your doctor this and have they reported it to the VAERS system?
[01:03:10]
[Steve Kirsch]
Yep.
[Gail Macrae]
Patients told me that their doctors did not want to report it and that they could not conclusively prove that they thought that this was from the vaccines. So one of the women in particular was very vivacious and she basically insisted to her doctor that she was 100% certain that it was from the shots and that they needed to report it to VAERS. But I reminded her, and I also reminded my colleagues of this too, is that we have an oath to report.
Oath to Report
Practitioners have, we have, it is mandatory for us to report any adverse event. And it's not our position as staff members to judge whether or not it was factually caused by the vaccine.
[01:04:03]
It is only our job to report that it occurred and there is a potential that it could have been caused by the vaccine. And from there it's up to the researchers to determine what the cause was.
[Steve Kirsch]
Right, so the doctors basically said they didn't report it because they couldn't assess, it couldn't ascribe causality because just because it happened 24 hours after the shot doesn't mean the shot caused it and we don't want to cause alarm and we don't want to be fired either for making a VAERS report on this safe and effective vaccine. So that'll make sense.
Vaccination Status of Patients
Of the 60 people you said that were on your shift, you know, when you're having this, you know, huge number of people in the hospital, of the 60 people you said you didn't talk to all of them, how many did you, do you actually know the vaccination status of and was it all, were they all vaccinated?
[Gail Macrae]
There were six that I got the opportunity to ask, all six of them were vaccinated.
[01:05:04]
And I'll go into a little more detail on those 60 patients or 55 patients, it was between 55 and 60.
[Steve Kirsch]
So- Okay, so, but of the 60, then you only asked a small handful what their vaccination status was.
[Gail Macrae]
That's correct.
[Steve Kirsch]
And you can't tell from their charts.
[Gail Macrae]
No.
[Steve Kirsch]
Because the vaccination status typically will be considered unvaccinated by, almost by default, right?
[Gail Macrae]
Correct. I was basing my conclusions on their diagnoses because I'd never seen what I saw in that day ever before.As you can see, the EPIC EHR system could have contributed to a lot of systemic misclassification of vaccinated people as unvaccinated.
This still leaves us with a question - while the interview makes it very clear that the vaccination status of the people who had confirmed COVID19 infection was fairly likely to be misclassified when they went to the hospital5, and also that serious vaccine injuries such as hospitalizations were often not reported to VAERS6, this does not tell us much about vaccine injuries themselves being mislabeled as COVID19 complications.
Why is it even POSSIBLE to classify a vaccine injury as COVID19?
In his excellent analysis of the Pfizer FOIA documents a_nineties reads revealed something which is actually pretty shocking.
Pfizer was applying a lot of pressure on the trial Principal Investigators asking them to classify post vaccination adverse events as COVID19 symptoms!
Please read the following slowly and carefully:
While there is barely a site without lengthy query/response volleys, and perhaps due to the language barrier or due to a refusal to be gaslit, the trial direction of one Turkish site failed especially; otherwise, there are very few and far between glimpses of Pfizer not getting their way, in form of a “RELATED” here or a refusal to delete an AE there. Not without substantial coaxing, however.
Subject 12091014 is a tremendous mess, with a positive covid illness from 19.-20.12., yet discharged from hospital on the 25.12., and the swab dated 31.12. The adverse event log has an event of covid-19 from 18.-23.12. The CRF also shows receipt of an influenza vaccine on 16.12. and Remdesivir while in hospital, along with obvious liver damage in the covid illness lab result forms.
Subject 12101026 is remarkable due to the site directly ignoring Pfizer’s clinical direction with regards to covid illnesses and adverse event reporting. 15.12., an entry by the site: “Patient had no covid-19 positive PCR test. So AE need to be recorded”, to which Pfizer replies the next day “Medical monitor: This is no correct. ACUTE UPPER RESPIRATORY TRACT INFECTIONS should be documented ONLY on the ILLNESS DETAILS CRF form irrespective of any SARS-CoV-2 test result and should not be captured on the AE CRF page” but the site remains steadfast, replying five days later with: “According to Safety team, the SAE onset date should be the date when the first signs/symptoms started, even if they were non-serious. The symptoms started on 07 Nov 2020 as non serious and the AE should be remain.” at which point Pfizer concedes, resulting in the subject having two adverse events of “acute upper respiratory tract infections” from 7.-16.11. and 16.11.-7.12.
Subject 12141039 contains a fantastic exchange between Pfizer and the site in the audit trail of an adverse event of diarrhea: upon multiple Pfizer queries demanding an illness visit be completed, the site replies with : “PI confirmed that this subject had only diarrhea due to eating foods that upset the digestive system and evaluated diarrhea as not COVID symptoms. This patient is not COVID-19.Not every symptom is COVID-19.” which garners the Pfizer response of “Medical monitor: During this study every symptoms listed Per Prot Sect 8.1. should have please triggered a potential COVID Illness Visit irrespective of perceived etiology or clinical significance. A protocol deviation will be documented”, which sets off another volley of queries and responses.
German site 1194 displays a natural affinity to the “covid illness” loophole, with each of the three supplied CRF files having adverse events hidden that way.
Subject 1002 has 11 days of chills after dose 4 hidden in covid_a.
Subject 1033 had 2 days of symptoms in December, yet when Pfizer asks for a convalescent visit, the site simply stonewalls by repeating “No Covid diagnosis. Therefor no Convalescent visit was performed” until Pfizer stops querying. There is a convalescent visit for cov_a in the CRF, but they took the serum samples from visit 101 (dose 3). This subject’s second covid illness had the diagnosis of “Immunnisation reaction.” with fever, muscle pain and the “other” symptom of lymphadenopathy until Pfizer demanded that adverse events be entered into the record, after which the diagnosis was deleted; only lymphadenopathy made it onto the adverse event log. The site didn’t make a fuss about the second “illness” convalescent visit.
Subject 1058 has the adverse events of lymphadenopathy, headache, injection site pain and arthralgia after dose 4, yet the CRF reveals a concurrent covid illness with the additional symptoms of fever and chills. Remarkably, all three Site 1194 CRFs are placebo patients who developed lymphadenopathy after real vaccination.
If you read the full article, it is pretty clear that someone needs to have exceptional data analysis skills as well as a very skeptical view of clinical trials to be able to spot these kinds of anamolies.
Since vaccine pushers are usually pretty bad at both of these things, it is not surprising that they have such a cavalier attitude towards this finding.
But whatever be the reason why vaccine pushers are so incurious about this topic - we still need to ask why the same misclassification could not have happened within hospital systems across the world?
Why RFK Jr could make a difference
Some people clearly feel RFK Jr is too much of an “anti-vaxxer” to be allowed to become the Health Secretary in the US.
I think it helps to see what the “default setting” looks like :-)
Here is what the current Health Secretary Javier Becerra did recently.
Given that the entire system is so biased towards blanket immunity for vaccine manufacturers, selecting someone with a healthy contempt for this vaccines are magic attitude is probably a good thing!
What would first rate pharmacovigilance look like?
I have already made a request for the NIH RECOVER Consortium data, and I intend to do my own audit if/when I get the data.
I am fairly confident that if I look at the TEXT notes from EPIC EHR I will find a lot of stuff which contradicts the higher level statistics in the dataset.
Which Gail Macrae points out:
[01:16:10]
[Gail Macrae]
That's correct.
[Steve Kirsch]
How would you change that based on their- They don't know how to change it. Sorry, say again.
[Gail Macrae]
So the Kaiser Epic system would automatically populate as unvaccinated and we could not, it was a long, arduous process to change it to unvaccinated.
[Steve Kirsch]
You didn't even know how.
[Gail Macrae]
We're not taught how, correct. So we had to talk to some of the trained administrators who could, but I would say less than 1% of the medical staff ever learned how to. I didn't, so I did see. So what we would do is we'd end up just putting it in the note that the patient was vaccinated, but notes don't show up on the statistical data analysis.For me to be able to do an external audit at least three things need to happen:
The NIH RECOVER Consortium must approve my login request (still waiting on it)
They should agree to share text notes (extremely unlikely given all the privacy considerations)
If they agree to share text notes, it should not be redacted to the point where it is almost useless
However, I would imagine the HHS Secretary can do an internal audit of the same information without any of these problems. And that’s why we need someone who is actually serious about data transparency, which RFK Jr certainly is!
I would say someone doing a rigorous internal audit of the text notes7 within the hospital data across the US to identify these misclassifications would be a great start towards first rate pharmacovigilance.
As of 9th Jan 2025, he still hasn’t commented on it
It is possible I might have implied it in my wording somewhere, but Jeff Morris could have simply asked for a clarification. Why didn’t he, especially after seeing the calculations I provided?
This is a good example of what I am referring to when I say that the vaccine pushers are more interested in statistical techniques to handle missing data than in actually demanding the missing data
She lost her job because she refused to take the vaccine
Where Gail worked
This is also an obvious under-reporting factor to VAERS but this is due to the software system used in this case. In other words, previous (and often disputed) views on the true under-reporting factor to VAERS do not really apply here.
I am of the opinion that prior to COVID19, there wasn’t much under-reporting of serious adverse events. Given these anecdotes as well as what we know about EPIC EHR, I now think this changed for the COVID19 vaccines.
It is now possible to use LLMs to do these kinds of audits
So glad you are on the case with this subject. Great work!