{"id":328375,"date":"2026-06-27T05:30:43","date_gmt":"2026-06-27T05:30:43","guid":{"rendered":"https:\/\/www.thetruthseeker.co.uk\/?p=328375"},"modified":"2026-06-28T07:36:34","modified_gmt":"2026-06-28T07:36:34","slug":"worst-science-ever-this-new-covid-vaccine-study-is-totally-meaningless","status":"publish","type":"post","link":"https:\/\/www.thetruthseeker.co.uk\/?p=328375","title":{"rendered":"Worst \u201cScience\u201d EVER: This New Covid \u201cVaccine\u201d Study is Totally Meaningless"},"content":{"rendered":"

Kit Knightly \u2013 Off-Guardian June 26, 2026<\/strong><\/h1>\n

Headlines are praising<\/a> a new study which claims that the Covid \u201cvaccine\u201d reduces the risk of \u201cCovid-related\u201d heart attacks and strokes by 40%:<\/p>\n

A new study finds the vaccine was linked with nearly 40 percent lower risk of events linked to covid-19 like heart attack and stroke<\/p>\n

This is a moral lie in the great tradition of \u201cdamned lies and statistics\u201d.<\/p>\n

Beyond the headline, the ugly reality is this \u201cstudy\u2019 is meaningless dross. A collection of numbers with no real-life application, which contains ZERO unvaccinated people<\/strong>, ignores vaccine harms<\/strong> and shows precisely ZERO alleged benefit at all to people under 75<\/strong>.<\/p>\n

And that\u2019s just the start. In addition:<\/p>\n

The sample was flawed<\/em><\/p>\n

The control group non-existent<\/em><\/p>\n

The definitions insane, <\/em><\/p>\n

And the \u2018diagnostic test\u2019 unfit for purpose.<\/em><\/p>\n

But that hasn\u2019t stopped it being met with predictable frothing excitement from the pro-vaccine shills in all corners, either because that\u2019s what they\u2019re paid for, or because they don\u2019t bother actually reading past the headline.<\/p>\n

Let\u2019s get into some details.<\/p>\n

1. No control group<\/strong><\/h2>\n

Firstly, we need to tackle the word \u201cstudy\u201d. People see the word \u201cstudy\u201d, and that it was published in the Journal of the American Medical Association (JAMA), and will be led to believe these are doctors<\/em> doing science<\/em>.<\/p>\n

That\u2019s not the case, they\u2019re just statisticians doing statistics. It\u2019s a data review, nothing more.<\/p>\n

They collated medical records and sorted them by some variables to look for trends. It\u2019s not really science, it\u2019s just maths.<\/p>\n

And since the data they collected was all based on military veterans getting vaccinated, it presents us with the biggest flaw in the study: The total absence of a control group.<\/em><\/p>\n

The paper has been pitched by mainstream science writers and vaccine shills on social media as a case of \u201cvaccinated vs unvaccinated\u201d, but that\u2019s just NOT TRUE.<\/p>\n

There\u2019s not a single unvaccinated person in the sample. None. Literally zero.<\/strong><\/p>\n

The two groups studied are \u201cflu shot\u201d and \u201cflu shot + 2025 Covid booster\u201d.<\/p>\n

So every single person<\/em> got at least one vaccine.<\/p>\n

But it gets worse \u2013 in fact, over 91% of participants had the original Covid booster in 2021<\/em>.<\/p>\n

The table below actually lists eight other vaccines<\/em> as well, including RSV and pneumococcal vaccines, all taken by between 70% and 10% of the sample:<\/p>\n

\"\"<\/a><\/div>\n

So,\u00a0 every person<\/em> in both<\/em><\/strong> study groups<\/em> had at least one vaccine. The vast, vast majority had at least<\/em> two and some potentially had as many as TEN.<\/p>\n

This study isn\u2019t comparing unvaccinated vs vaccinated at all, it\u2019s comparing people who got the flu shot, the 2025 booster and maybe<\/em> eight other vaccines, with people who \u201conly\u201d got the flu shot and maybe<\/em> eight other vaccines.<\/p>\n

Right there, they have rendered their data meaningless.<\/p>\n

There\u2019s also this curious disclaimer in the \u201cstrengths and limitations\u201d section\u2026<\/p>\n

We assumed no interaction between COVID-19 and influenza vaccines.<\/p>\n

\u2026now why would they assume that?<\/p>\n

And why not add that they also assumed no interaction between the RSV vaccine and the original Covid vaccine from 2021.<\/p>\n

And assumed no interaction between the 2024 flu shot and the zoster vaccine, and the 2022 Covid booster and the pneumococcal vaccines.<\/p>\n

Or any and all of the thousands of potential combinations of one or more vaccines that may or may not interact in ways they assumed they didn\u2019t.<\/p>\n

You get the point.<\/p>\n

2. Ridiculous definitions<\/strong><\/h2>\n

Having established the sample and design of the study is pure nonsense; let\u2019s move on to their hypothesis.<\/p>\n

The authors claim to be testing whether or not the 2024-25 Covid \u201cvaccine\u201d formulation protects against \u201cCOVID-19\u2013associated major adverse cardiovascular event\u201d<\/em> (MACE).<\/p>\n

So what is<\/strong> a \u201cCOVID-19\u2013associated major adverse cardiovascular event\u201d<\/em>?<\/p>\n

The primary analysis included a composite COVID-19\u2013associated MACE outcome consisting of 4 individual outcomes: (1) COVID-19\u2013associated cardiovascular death; (2) COVID-19\u2013associated myocardial infarction; (3) COVID-19\u2013associated stroke; and (4) COVID-19\u2013associated hospitalization for heart failure.<\/p>\n

So, a \u201cmajor adverse cardiovascular event\u201d is a heart attack, stroke, heart failure or death resulting from same.<\/p>\n

But how are they \u201cassociated\u201d with Covid19?<\/p>\n

Well\u2026<\/p>\n

COVID-19\u2013associated cardiovascular death was defined as death within 30 days after a laboratory-confirmed SARS-CoV-2 infection and accompanied by a diagnosis code for MACE within the preceding 30 days.<\/p>\n

A \u201cCovid-associated cardiac death\u201d is dying of a heart attack or stroke within 30 days of testing positive for Covid.<\/strong><\/p>\n

This will be resoundingly familiar to any veteran Covid sceptics. During the \u201cpandemic\u201d, a \u201cCovid death\u201d was a \u201cdeath from any cause within 30 days of a positive test\u201d.<\/a> This is taken straight from that playbook.<\/p>\n

Which is pretty damning, obviously, but it gets worse. Much, much<\/em> worse [emphasis added]:<\/p>\n

COVID-19\u2013associated myocardial infarction and COVID-19\u2013associated stroke were defined as an emergency department or urgent care encounter within 24 hours before<\/strong> or after a laboratory-confirmed SARS-CoV-2 infection<\/strong> or an inpatient admission 2 days before<\/strong> through 30 days after a laboratory-confirmed SARS-CoV-2 infection<\/strong>, with a corresponding diagnosis code for myocardial infarction or stroke. COVID-19\u2013associated hospitalization for heart failure was defined as a hospitalization with either a primary diagnosis code for heart failure or an admission diagnosis field documented as heart failure, occurring from 2 days before<\/strong> through 30 days after a laboratory-confirmed SARS-CoV-2 infection<\/p>\n

Did you spot the magic word?<\/p>\n

A \u201cCovid-associated\u201d cardiovascular event is any heart attack or stroke resulting in hospitalization, in which the patient tests positive for Covid 30 days before OR 2 days AFTER<\/strong> the event.<\/p>\n

In other words, they included people who didn\u2019t test positive for Covid19 until after they were in hospital<\/em>.<\/p>\n

Now, even if you chose to live in the fantasy-reality where \u201cCovid\u201d actually exists, this is remedially bad science because it throws out the linear nature of causation.<\/p>\n

Theoretically, according to this methodology, you could be feeling perfectly well, have a heart attack, be in hospital, catch \u201cCovid\u201d from another patient, and suddenly your heart attack is \u201cCovid-associated\u201d .<\/p>\n

Even on their own flawed terms this is anti-rational.<\/p>\n

Let\u2019s remember that in the created world these \u201cscientists\u201d occupy, \u201cnosocomial\u201d (hospital-acquired) Covid19 makes up anything between 18%<\/a> and 56%<\/a> of all cases. Meaning \u2013 again, by their own logic \u2013 anybody, or indeed everybody,<\/em> who tests positive after entering a hospital may have been infected while in hospital.<\/p>\n

It really shouldn\u2019t need to be said \u2013 but if you don\u2019t know something was there before the heart attack<\/em>, you can\u2019t possibly say it caused the heart attack<\/em>.<\/p>\n

That\u2019s basic cause-and-effect, and this paper chooses to ignore it.<\/p>\n

This is, of course, the reason they opt for the weasel-word \u201cassociated\u201d. Not \u201ccaused\u201d, not \u201cinduced\u201d but only \u201cassociated\u201d.<\/p>\n

But all becomes doubly meaningless when we add reality back in, because of course there is nothing to \u201cassociate\u201d those cardiac events with the thing called\u00a0 \u201cCovid\u201d except a positive test \u00a0\u2013 and we all know (or should know)\u00a0 what that means.<\/p>\n

3. PCR tests. Again.<\/strong><\/h2>\n

In the past six years, we have talked about PCR tests a LOT. Dozens of articles, probably hundreds of thousands of words. We know how they work, or rather how they don\u2019t<\/a>.<\/p>\n

I have written about how creative application of tests that don\u2019t work can create a pandemic out of almost thin air<\/a>.<\/p>\n

Anything that relies on PCR tests as reliable data is fatally flawed from its inception.<\/p>\n

But let\u2019s put a pin in that, and again pretend to live in the world where Covid exists and PCR tests are somehow useful at detecting it.<\/p>\n

A large percentage \u2013 anything from 40 to 80 per cent<\/a> \u2013 of\u00a0 so-called \u201cCovid cases\u201d are defined as \u201casymptomatic\u201d. Meaning the only evidence for the presence of the virus is a positive test.\u00a0 But of course PCR tests can, and very often do, produce false positive results <\/a>\u2013 and this is not a fringe conspiracy theorist idea, it\u2019s\u00a0 broadly accepted mainstream \u201ctruth\u201d by the type of establishment people running this study.<\/p>\n

So, do they claim it\u2019s possible, in any way, to differentiate between a false positive test and an asymptomatic case?<\/p>\n

No. Not at all. They are essentially two different descriptors for the same exact thing \u2013 a positive test without symptoms.<\/p>\n

Nowhere in this paper do they claim their alleged \u2018positive cases\u2019 were symptomatic; they only describe them as \u201claboratory confirmed\u201d.\u00a0 Which means even by their own flawed and delusional rationale, all<\/em> their positive cases could be false positives.<\/p>\n

Does the paper attempt to account for this? <\/em><\/p>\n

Of course it doesn\u2019t.<\/p>\n

But there\u2019s more. Eg \u2013 nowhere is it noted how many times, or by whom, or at what cycle threshold these patients were tested.<\/p>\n

Nor do they say which group was tested more or which group had a higher percentage of positive tests.<\/p>\n

Does the paper attempt to account for this variable?<\/em><\/p>\n

Of course it doesn\u2019t.<\/p>\n

What about negative tests? Eg \u2013 did the people with non-COVID-associated cardiovascular events test negative? Or were they just never tested?<\/p>\n

Do you think they tell us?<\/em><\/p>\n

Of course they don\u2019t.<\/p>\n

And what if, after<\/em> they test positive and before<\/em> their cardiac event, they test negative? Or what if they tested negative multiple times? Are those cases discounted?<\/p>\n

Do you think they tell us?<\/em><\/p>\n

Of course they don\u2019t.<\/p>\n

In fact, the study never mentions any such thing happening, which \u2013 with a sample of over a million people \u2013 seems very, very unlikely.<\/p>\n

Misrepresenting Results<\/strong><\/h2>\n

So we\u2019ve established that the sample was flawed, the control group non-existent, the definitions insane, and the diagnostic test unfit for purpose.<\/p>\n

What about the results?<\/p>\n

Well, the graph they most heavily feature \u2013 and the one doing the rounds on social media and in the papers \u2013 is this one\u2026<\/p>\n

\"\"<\/a><\/div>\n

\u2026and it is, in multiple ways, quite simply a lie<\/strong>.<\/p>\n

Let\u2019s start with the labels: \u201cCovid19 vaccine\u201d vs \u201cno Covid19 vaccine\u201d.<\/p>\n

That\u2019s a lie.<\/p>\n

We know at least<\/em> 89%, and potentially 100%, of the \u201cno Covid19 vaccine\u201d group got at least<\/em> one Covid vaccine.<\/p>\n

We know at least<\/em> 58%, and potentially 100%, of the \u201cno Covid19 vaccine\u201d group got at least<\/em> two Covid vaccines.<\/p>\n

We know some of the \u201cno Covid19 vaccine\u201d group got as many as FOUR Covid vaccines.<\/p>\n

Labelling them \u201cno Covid19 vaccine\u201d is dishonest. We can assume to some extent cynically done to help make their chart go viral on social media and own the anti-vaxxers.<\/p>\n

Then there\u2019s the pretty crucial matter of ages.<\/p>\n

We know they split their group into three age sets (under 65, 65-75, and over 75), so why not plot three separate lines to show the results for each separate set?<\/p>\n

Well, because then their graph would look a LOT less impressive, since as they admit\u2026<\/p>\n

Vaccine effectiveness for COVID-19\u2013associated MACE was statistically significant only in individuals older than 75 years<\/strong>\u2026No statistically significant vaccine effectiveness for COVID-19\u2013associated MACE was observed among those younger than 65 years or aged 65 to 75 years.<\/p>\n

One more time, for those at the back:<\/p>\n

No statistically significant vaccine effectiveness for COVID-19\u2013associated MACE was observed among those younger than 65 years or aged 65 to 75 years.<\/p>\n

So, even on their own flawed, insane and deeply dishonest terms\u00a0\u2013 when it comes to preventing \u201cCovid-associated\u201d cardiovascular events, the 2025 vaccine is\u00a0100% useless for those under 75.<\/p>\n

5. Gaps in Data<\/strong><\/h2>\n

To put it nicely, the study seems to have gone for a breadth- not-depth approach to data, hoping that a big sample with big numbers makes it look exhaustive, but there\u2019s a shockingly small amount of detail in their data.<\/p>\n

They have a sample of ~1 million people, but the total number of alleged \u201cCovid-associated major adverse cardiovascular events\u201d (MACEs) is only 411.<\/p>\n

That\u2019s a relatively tiny data pool that would benefit by some simple examination.<\/p>\n

For example, it would be the easiest thing in the world to graph those 411 incidents by age, and report which group (vaxxed vs \u201cunvaxxed\u201d) was experiencing incidents at a younger average age.<\/p>\n

Or, since we know they assumed an \u201cassociation\u201d\u00a0 between \u201ccovid\u201d and these MACEs based solely on a PCR test administered anything from 30 days before to two days after<\/em> the MACE, they could tell us when<\/em> each of these tests was administered, and how many were done after the fact.<\/p>\n

They could have split the 411 by vaccine status \u2013 across all the 10 potential vaccines \u2013 to look for patterns there.<\/p>\n

Or they could have split them by Moderna vs Pfizer (instead of chucking them all together, as they admit to doing).<\/p>\n

They could have graphed the 411 by comorbidities. Or gender. Or race. Or homelessness.<\/p>\n

All of this would enable them to look for trends.<\/p>\n

For example, maybe the \u201cvaccinated\u201d group experience a lower overall\u00a0 rate of MACEs, but the people who experienced them were all younger and had no previous history of heart problems \u2013 or vice versa.<\/p>\n

This is all potentially interesting data, no?<\/p>\n

But no \u2013 they don\u2019t bother with any of this \u2013 or with any analysis that might have real-world meaning. Instead, they\u00a0 just tell you the basic percentages of these things in each massive group, without ever actually trying to apply them to the results.<\/p>\n

Since we know they have this data, and it certainly wouldn\u2019t be hard to have examined it for all these potential patterns, we must conclude either that the authors were too lazy, too incompetent, or found the results didn\u2019t fit their desired conclusion.<\/p>\n

Either way, we\u2019re left with a wide but very shallow data pool that tells us nothing of any value at all. It\u2019s just a mass of numbers with no application.<\/p>\n

5. Absolute Risk vs Relative Risk<\/strong><\/h2>\n

This is an old story in scientific literature, but absolute risk reduction vs relative risk reduction is a very important difference.<\/p>\n

Early coverage of the paper, from places like the Washington Post boasted \u201c40% reduction in heart attacks, strokes and heart failure\u201d:<\/p>\n

\n

><\/p>\n

\n

The coronavirus vaccine reduced the risk of major cardiovascular events linked to covid-19 \u2014 strokes, heart attacks, and hospitalization from heart disease \u2014 by about 40 percent, according to new research. https:\/\/t.co\/cQjvi8EMpX<\/a><\/p>\n

\u2014 The Washington Post (@washingtonpost) June 16, 2026<\/a><\/p><\/blockquote>\n