When investigators have a personal stake in whether a product appears to be safe and effective, then they can go through mental gyrations to convince themselves or others that the proverbial house is not on fire, or that the Titanic is not actually sinking. When accidental, it could be called something like Observer Bias, or something.
But some “oversights” are so improbably-coincidental that they raise suspicion that the researchers are “gaming” the science, or massaging the data, in order to get it to say what they want it to say — instead of having it tell the truth of the matter, like good science is supposed to do.
These researchers tested out “self-amplifying RNA” injections aimed at producing a physiologically-toxic, organ- and tissue-harming compound that we have become familiar with: SARS-CoV-2 Spike Glycoprotein:
They ended up with two experimental groups, one group of 30 seropositives (immunologic evidence of prior COVID), and the other group of 12 seronegatives. But their subjective interpretation, regarding the extreme lab results, defies probability. Lab abnormalities come in five grades and Grade 3 means severe deviation from normal:
After the first dose, 7 of the 30 seropositives had a Grade 3 or higher lab abnormality, and 2 of the 12 seronegatives did also. But look at the result after the second dose: 27 (90%) out of 30 seropositives developed one of these super-rare lab abnormalities, and all 12 of the 12 seronegatives developed one of these super-rare lab abnormalities.
Then the researchers say that those super-rare abnormalities are just a string of sequential coincidences which can be explained by the common causes of variation in the world — rather than being due to the special cause of variation that had been introduced to the subjects: novel biologic products with no safety history in humans.
Here are a few Grade 3 lab abnormalities for perspective:
Hypoglycemia (low blood sugar) is highlighted and the second column in from the right is Grade 3 hypoglycemia. It goes down to 45 mg/dL which is serious, because levels lower than 45 mg/dL can put you into a diabetic coma:
Something like 98% of healthy people never get that low, however, because it is well beyond what is deemed to be the “lower limit of normal.” A Grade 3 lab abnormality for an enzyme like CPK could be something like 3x the “upper limit of normal” — and, again, it is super-rare to find (~98% of healthy people never reach it).
Check out these Grade 3 or worse lab abnormalities that subjects were interpreted as having just by being unlucky, rather than because they had just been injected with a substance with no safety history in humans:
Four of those were hypoglycemias that were Grade 3 or worse. But if the highest baseline chance to get a Grade 3 abnormality is a paltry 2%, then what are the chances that 90% of the seropositives had one and all 12 of the 12 seronegatives had one (note this assumes each instance is in a new person, rather than multiple ones in one person)?
Let’s put the data through our trusty “online graphing calculator” to find out …
The top row shows the result of a binomial test that looks at 30 trials (the # of seropositives) and uses a baseline probability of “coincidental” Grade 3 lab abnormality of 2% in decimal form (0.02), and then takes the probability of getting up to 26 “hits” out of 30 — when each has an independent chance of 2% — from a total of one.
The probability was so low that it “broke” the TI84, and the TI84 ended up reporting it as zero (because it couldn’t handle all of the decimals after zero). The second line tests the outcome of 12 “hits” in 12 people who were seronegative, also returning a probability of “zero” for that to happen by coincidence.
Now, at this point, resident Substack math gurus such as the prestigious Norman Fenton or the iconoclast William Briggs (or even the “bad cat”) may come on here, harping on me for missing something: Each person had an independent 2% chance on each of the 14 lab tests performed — so I have seriously understated the probability.
Fine then, I’ll perform the comprehensive analysis, giving each person the same chance on each and every test. Let’s use the 12 events in the 12 seronegatives — with a 2% “hit rate” — but applied to all 14 tests in all 12 persons (14 * 12 = 168 trials):
There were 16 chances in 100,000 for those 12 people to have come up with those 12 Grade 3 lab abnormalities by “coincidence” (the second line is a “trick” to pull the number out of scientific notation). That’s less serious. But now let’s separately test the 30 seropositives with the 27 “hits” they got (420 total tests performed, and 27 “hits”):
Uh-oh, the researchers appear to be “super-dishonest” again, because the probability of those 27 “hits” (those lab abnormalities) happening by “coincidence” — and NOT attributed to the injections given to the subjects— was just 175 chances in a billion. Let’s turn over a new leaf in America, and Make Science Honest Again (MSHA).
No more of this printed tomfoolery where we are asked (insultingly) to believe that things which do not happen even one time in a million (less probability than that for getting hit by lightning) were coincidentally a part of the experiments which were performed, and we are just supposed to accept that they were a coincidental part.
Reference
[COVID shot researchers ask you to believe in a 175-chances-in-a-billion coincidence] — https://www.mdpi.com/2076-393X/13/6/553
[some of their subjects were almost put into diabetic coma after the shots] — https://my.clevelandclinic.org/health/diseases/16628-diabetic-coma
[Grade 3 lab abnormalities] — https://www.fda.gov/media/73679/download
[online TI84 graphing calculator] — https://ti84calc.com/ti84calc