Another Flawed, Misleading, Biased Study to Promote Covid Shots in Kids
A science journal called The Lancet: Child & Adolescent Health recently published a paper entitled “Vascular and inflammatory diseases after COVID-19 infection and vaccination in children and young people in England: a retrospective, population-based cohort study using linked electronic health records“
Here is the citation:
Sampri A, Shi W, Bolton T, Ip S, Knight R, Walker V, Denholm R, Raffetti E, Keene S, Allara E, Jiang X, Kontopantelis E, Denaxas S, Khunti K, Conrad N, Pagel C, Hardelid P, Sterne JAC, Brown KL, Whiteley WN, Cezard G, Wood AM; CVD-COVID-UK/COVID-IMPACT Consortium and the Longitudinal Health Wellbeing COVID-19 National Core Study.
Vascular and inflammatory diseases after COVID-19 infection and vaccination in children and young people in England: a retrospective, population-based cohort study using linked electronic health records. Lancet Child Adolesc Health. 2025 Dec;9(12):837-847. doi: 10.1016/S2352-4642(25)00247-0. Erratum in: Lancet Child Adolesc Health. 2025 Nov 6:S2352-4642(25)00335-9. doi: 10.1016/S2352-4642(25)00335-9. PMID: 41198364.
The paper is being used by narrative-pushers around the world to promote COVID-19 shots for children as we enter the low vitamin D season in the northern hemisphere, which is when cases of colds and flus rise north of the equator.
Like so many other similar studies, this is a fatally flawed, misleading, biased, and even a notably hypocritical study. There are so many of these kinds of studies being published now that it is impossible to address them all.
So, I would like to highlight key flaws with this paper as an example of issues that are proving to be commonplace in the COVID-19 literature. When you see these kinds of flaws in other papers, you will know that their conclusions should also questioned, if not outright dismissed.
It Begins on the Wrong Foot
Let’s start with the red flag in the title: “Vascular and inflammatory diseases after COVID-19 infection“. One should always be cautious when the authors are unable to differentiate between infection and disease.
There is no such thing as ‘COVID-19 infection’. Laypeople are not expected to know this, but scientists publishing in these journals should not be making such mistakes.
COVID-19 is a disease that manifests in a subset of people that get infected with severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Indeed, the “D” in ‘COVID’ stands for ‘disease’; it is the coronavirus disease that was first identified in 2019.
Infection with SARS-CoV-2 does not equate to being diseased. I don’t mean to be facetious, but in this day and age things need to be stated explicitly in terms that an elementary student can understand: you must be diseased to have a disease.
In other words, you need to be ill; you need to have signs and symptoms of sickness to have a disease. A positive test result on its own does not convert a healthy person into a diseased person.
Once a person understands this simple concept, they can understand why almost all COVID-19 case-related data are fatally flawed. Simply put, cases of disease where rarely diagnosed properly.
A proper diagnosis requires a constellation of data that go well beyond a single result from an aid to diagnosis. Consequently, data sets are confounded beyond reliable interpretation.
To reiterate, one does not get infected with COVID-19. One gets infected with SARS-CoV-2 and then may or may not progress to develop COVID-19. In short, the authors of this paper highlighted right from the get-go, a flawed understanding that discredits their own study.
Studies on COVID-19 Will Forever be Fatally Confounded by the Fact that the Disease Was Inappropriately Defined Solely by Positive Results of Tests Intended to be Diagnostic Aids.
In this current study, the results are confounded beyond utility by the fact that COVID-19 was defined as someone having received a positive result from either a PCR test or a rapid antigen test.
Both are nonfunctional tests that are incapable of differentiating infectious viral particles with the potential for causing disease, from dead viral particles or even portions thereof.
Many people were infected with SARS-CoV-2 but never contracted COVID-19, especially children. Although the authors buried in the limitations section of their paper an acknowledgement of missing asymptomatic infected children in their COVID-19 case data set, they failed to highlight how fatal of a flaw this is.
The group of children and adolescents that got infected but never developed COVID-19 was likely substantial. But we’ll never know how large because no public health agency properly assessed seroconversion against SARS-CoV-2, perhaps because that would have required acknowledgement of the concept of naturally acquired immunity.
‘Seroconversion’ is when antibodies appear in the blood and are a sign that an infection had occurred. Seroconversion in the absence of overt disease suggests the infectious agent was non-pathogenic in that individual because their immune system was able to clear the infection prior to the onset of any signs or symptoms.
Addition Fatal Confounders in the Study
Many other confounders were neither incorporated or acknowledged in the study, such as differences in testing rates between those who took the shots and those who didn’t.
Note that where I live in Canada it was a public health policy that only asymptomatic people could take the antigen test, despite it being designed exclusively for use in people with symptoms.
Asymptomatic (i.e., healthy) people actually had to sign waivers indicating that they understood that the test they were being subjected to was not designed to be used on them. Looking harder for a disease in one demographic is going to bias the identification of cases towards that demographic.
Another fatal flaw is the inappropriate use of positive results from antigen tests to ‘diagnose’ people with COVID-19. As I said, this test was often used to test ASYMPTOMATIC people, which the test was never designed for.
These antigen tests were only ever designed to be used with symptomatic (i.e., diseased) individuals as an aid to diagnosis.
The reality is that the use of the antigen test in symptomatic people would have been a much better predictor of actual numbers of cases of COVID-19 because these results aligned with positive PCR tests at cycle thresholds below the cut-offs that correlated with samples containing replication-competent virions as per the gold standard virology assay assessing cytopathic effect in permissive cell lines.
So, this study included disease-free people with false-positive antigen tests in their diseased group. The way the antigen tests were deployed to test asymptomatic people completely invalidates the ability to assign people with these positive test results to a diseased group.
In short, the statistics for the diseased group in this paper are substantially overinflated, but to a degree that can never be properly ascertained. Further, they are confounded in a way that is irreparable.
Both of these invalidate the findings of this paper.
Remarkably, the study defined the vaccinated group as those who received a single dose only. Let me repeat that. In this study, receipt of a SINGLE COVID-19 shot was used to define the vaccinated group.
Among those who received a single shot, how many were defined as ‘vaccinated’ by public health officials? How many received a vaccine passport? They were defined as ‘not fully vaccinated’!
So, to hear the mainstream media promoting this study when they vilified those that never progressed to two or more doses is the ultimate in hypocrisy. One needs to ask why multi-dosing was not analyzed when the only accepted definition of ‘vaccinated’ was two or more doses.
The manufacturer themself clearly stated it was a two-dose regimen. I can’t even fathom the concept of a study that analyzes and then promotes an incorrectly defined medical procedure.
This is like promoting findings from a study that claims to support the administration of the recommended dose of a drug, but recruiting participants based on those that took at least half the dose.
In medicine, dose always matters.
Notably, many public health databases show anomalies in assessments of those who got the shots. Specifically, when the single-dose group is parsed out, it often shows the greatest effectiveness and safety over multi-dosing.
So, I hypothesize that including them with those who got two or more shots helped bias the already fatally flawed public health data in a way that would appear to favour the shots. Yet, out in the real world the single-dose group was lumped in with those who didn’t get a shot when it came to public health policies and subjected to equal vilification.
Additional Bias
Remarkably, the discussion section contains a warning that the data are not to be used to question the conclusion that the shots were awesome. It is going to become a major issue if these statements are allowed in publications and then regurgitated uncontested in courts.
I always promote readers to make their own independent assessment of the raw data in a paper before exposing themselves to potential author-infused biases in the discussion section. Authors never have a monopoly on interpreting data.
To think and promote such a concept is the antithesis of science and scientific discourse.
Final Thoughts
There are other flaws in the paper, but there is no use ‘flogging a dead horse’. These kinds of papers have become excessive time-sinks for too many scientists of integrity. They distract from much more positive usage of time and energy.
Overall, this paper is fatally flawed and irrelevant for numerous reasons. It is sad to see how soiled the research literature is getting with this kind of garbage masquerading as science.
The reality is that scientific studies of COVID-19 will be confounded by the fact that proper diagnoses were never made and most of the raw data in medical charts and elsewhere are insufficiently clear to go back and properly differentiate between true cases of COVID-19 versus people who merely had a positive result from what was only intended to be an aid to diagnosis.
As these fatally flawed papers keep accumulating, the peer-reviewed scientific literature progressively becomes more polluted. This will translate into more people being misled by where they perceive the overall weight of the scientific evidence to lie.
This will translate into even greater division of critical and non-critical thinkers, with simultaneous erosion of public trust in science.
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